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FMC fast chat takes you inside the news so you can be
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in the know in 30 minutes. Hosted by Fair Media Council CEO
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and executive director Jackie Clement, Fastchat features notables in
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news, media and business.
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Hey, everyone. Welcome back to FMC Fast Chat, where media
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meets influence. I'm your host, Jackie Klimet,
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and today's episode is all about transforming the
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way we work, lead, and innovate. We're going
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to talk about what it takes to shift from a typical business mindset and
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culture to something much more forward thinking and
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media savvy. I've got the perfect guest to break it
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all down for us. Rocky Ozaki,
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founder of now of Work. Rocky has been leading the
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charge in helping businesses move into the future, and his AI
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adoption program has already transformed companies in
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Canada and throughout the US. Plus,
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Rocky is sharing the stage with folks like Arnold Schwarzenegger and Gary
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Vaynerchuk when he's doing keynote addresses. So,
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you know, he's bringing serious insights on leadership,
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innovation and the future of work. Now,
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let's find out the latest from Rocky Ozaki.
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Let's go, Rocky. It's so great to have you back with us. I think
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the last time we spoke was early in the pandemic, if I'm not mistaken.
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It's true. I actually, Jackie, I look back, it was June 2021.
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Okay. All right, so it's another different world that we're living
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in. I'm wondering if we can start kind of with a broad question
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and you break it down however you want. I'm wondering,
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you know, from what you do with leading and transforming companies,
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you go all over the place. You're typically all over North America working
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with businesses. What are you actually seeing on the ground?
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Like what? How big of a gap is there between what
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businesses are doing versus where they should be and where their mindset
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should be? Okay, so that is a great segue
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that when we last talked, because in 2021, June, we were
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replying or responding to the impact of lockdown and
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challenging assumptions of work and life and how everything was changed
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post pandemic. So it's timely because now it's AI.
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And I think that's a lot of our conversation today. But the
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gap is pretty big. So when I
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would say that if we focus just on AI for a second,
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when chat CPT dropped almost two years ago,
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the world kind of like, it was like, oh, my gosh, I think the fastest
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to 100 million users, everyone started using it, but then it kind of slowed down
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or they weren't using it in ways strategically which I'm sure we'll talk about.
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So from the contents of AI, what we're seeing, absolutely, is that there was a
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shiny new object. People jumped on the bang bandwagon.
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A lot of them jumped off or just started shotgunning, and it's actually
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put them further behind Jackie. So AI to me,
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actually is real. It is not a fad. It's going to be the fabric of
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every organization. But the chasm grew up.
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I don't know why we're still trying to figure this out too, but it's a
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pretty big gap, at least in the context of AI in the modern company.
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Yeah. I'm wondering, though, it just seems like everything changed
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very quickly and a lot of technology came at us very fast.
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Do you credit that with the pandemic and the technologists
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and having nothing else to do? Well, it's part of that, and you can
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think back. And so when the pandemic hit, what did
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we see? We saw that supply chain broke down. We saw
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that organizations who used to say, we'll never go virtual and we'll never always
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have offices, well, they had no choice. And so in the back of the
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scenes, what happened was all of a sudden now companies, the leading companies,
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were starting to say we need to double down on what we call Horizon two
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of innovation, which is like this three to five year timeframe. So we had
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to accelerate automation because we saw supply chain issues.
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We saw how now talent, well, you know, pretty much every jurisdiction around North America
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is having a tough time finding talent,
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like, even if for the corner store, in the small shop. So now we had
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to look at way automating things, even at the grocery store, whatever. AI for
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web three, spatial computing, this whole idea of VR,
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Mister XRD, part of it was, you're right, we were in lockdown,
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but part of it was out of necessity. And we all again said, as I
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said before, we challenge our assumptions of work
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life and business. And so that accelerated these technologies.
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Okay, all right, tell me a little bit about web three,
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because that's something we started to hear about and then suddenly dropped off
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the radar. It certainly has. And I think a lot of the
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web three component of being in the metaverse and stuff like that is just the
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use cases are very, a lot of it's in gaming or a lot of it's
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in very small niches. I think it's going to blow up.
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But there's this notion that in web one,
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it was like Internet. We created a website,
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and then in web two, you might call it that, and then all of a
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sudden we were building communities. We were starting to be able to contribute
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onto the Internet. We were allowed to bring our own content and conversation. There's a
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lot more to this, by the way. I'm dumbing it down. And now web three
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is saying, well, a lot of things like who owns the data and
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where do we actually live in web three and virtual worlds?
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And this is why it's more than just web three, why it's blockchain,
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and why it's spatial computing and all these different components of it is
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that there is this next step of how we're going to interact in
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the Internet. Who owns data in this world?
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And so it's a pretty interesting place, but I think it definitely is lagging behind
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AI, for example. Okay, so let's focus on
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Aih. You have an AI adoption program, and. I say this
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kind of jokingly, but it's true. So many companies like,
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oh, we're AI, we use AI, we use chat,
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GPT, and we have a meeting, you know, meeting, recording device
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or some, some kind of, like, I won't promote any particular company, but we
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record our meetings, our virtual meetings, we get summaries and all of a sudden we
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use AI. So what our program was built to show with them
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is, number one, there's three stages, in our opinion, on adopting
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AI initially, and the first one, and really quickly,
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is AI readiness. So in the first part
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of our program is, it's a twelve week program, by the way, and we're going
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to actually talk about governance, responsible use of AI.
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What are your objectives of using AI? Is your team members
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even ready for it? We've seen, Jackie,
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a lot of organizations adopt AI without proper communications,
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without proper governance. You can call that, and team members
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quit, customers leave, because like,
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what the heck is going on? So our first part is like,
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are you actually AI ready? And then the second part is around AI
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experimentation. And so we do a couple things. We can break these down if any
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of these are interesting to you, but one is use cases. And so
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we try to democratize that process throughout the organization.
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So we teach you to say across your whole organization, what friction points
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are there? What problems are you trying to solve as someone working with customers,
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building an AI backlog and then trying to prioritize
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where there's potential impact and value versus,
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let's go use this meeting recording software because our buddy told
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us to use it. That's not strategic and it's not aligned to strategy and other
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things. And the third part of our component is around scaling
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AI. And so that's around building roadmaps, around building repeatable
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and predictable ways in which you're going to use Aih. And so that's the
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way the program is formed and that's the problem we're trying to solve, is use
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AI properly and create a culture
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where it's embraced and people understand the impact and purpose and all that
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sort of things. And they use it responsibly, which is key.
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My perspective, too. Well, it certainly aligns to the value
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proposition of what you and your teams do. Yes. And it's
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big. And every, in the United States, like every state, has different regulations.
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And I, there are things happening that people may not know about.
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So, Jack, you may recall at GDPR in the UK,
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we're talking about, they're sort of the leaders in how we protected
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data. Well, what we're thinking, Jackie, is that,
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and no one watching this quote me on this. I'm not,
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this is what I'm observing is that we are going to start
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to see, because governments are listening and they're really
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interested in AI, obviously. And just anecdotally,
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when I'm sitting in webinars or conferences, what I'm hearing, for example,
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I'm based in Canada right now. Most of, well, actually most of our business
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is us, but in Canada, we're taking a very,
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very cautious approach. And United
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States is very pro innovation right now.
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And if you were to talk about GDPR sort of being the standard
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in the middle, the US is biasing one way. Canada,
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for example, is biasing the other ways. And this is going to have some implications
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on responsible use when you're bringing it to your customers and
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your team members is what is your government looking at in
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terms of regulations? These things, I think are around the corner.
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Okay. All right. That's going to be interesting and something to watch
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for as that rolls out. Tell me,
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let's go on the flip side of the equation. What organizations do you
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see that have either adopted,
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were early adopters, have their act together when it comes
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to AI or the ones that you can point people to, to say,
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here's a good example of what you should be doing.
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They don't really exist.
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And I was thinking indictment, maybe it's the people that we interact with.
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It's just so new. Right, Jackie? And many companies
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aren't big enough. And so we play mostly in SMB.
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Right. So that's context there. And we had a few big, big organizations
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as clients, but the most is SMB. And so why that matters
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is, in my view, the context of our interaction with
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clients is they don't have ctos. CIO's always like,
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they may have some head of technology, they don't have those roles or
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chief innovation officers and risk officers that large enterprise
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do. And so in our world, in the SMB
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world, under 100 million in revenue,
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they even 50 million in revenue, for that matter, they don't,
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they're shotgunning. This is new to them. And even if
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you are a large organization, Jackie, this law, the playbook,
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is just still being written on the fly. And so when you ask me,
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like, who's doing it right, I would say, broadly speaking, the ones
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that are doing it right are the ones that are using the playbook
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I described. Let's just pause for a second and let's just think about
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what kind, what is our purpose of using AI, what are our objectives?
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What kind of responsibility does that look like? Let's slowly
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adopt AI, socialize it really well with our organization,
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and continue to gain value through that. And the other
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big piece of what we train in our program, Jackie, is around metrics.
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So if you're going to adopt, actually, you know what, there are companies that do
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it well, now that I talk, because I don't know what you're going to ask
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me. So what I would describe as a company is doing it well,
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are ones that say, listen, let's go back to the meeting software,
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the AI, okay, you can adopt that, pilot it.
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The winning company is saying, let's pilot it for three months. What is
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the problem we're trying to solve? It is trying to get good summaries
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of meetings for those that weren't in attendance. It is. The problem
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to solve is I'm missing 20% of the meetings and I'm a
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busy executive. I like to get a summary. So we're really understanding why.
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Okay. And then bacon metrics, Jackie, over those three months of pilot,
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whatever that pilot period is. So getting feedback from the users,
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how accurate are the summaries and actually measurable outcomes that,
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say, at the end of the pilot, do we pivot,
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persevere or punt? These are the three P's that we
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always talk about. Persevere quickly means or pivot the story. Pivot.
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It's getting some value, but we need to make some changes, but we're going
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to stay the course. Persevere says it's working, it gets solving
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the problems, it's hitting our metric. Let's cascade this further or
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unlock more features, whatever it is. And punt says it's not
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doing what we thought it would do. Let's fail fast, punt it
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and try something different. So winning companies are following the
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framework again that we teach. Got it. Now,
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as I'm listening to you talk, and by the way, I should point out,
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you don't know the questions I'm going to ask.
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Standard format with us, the guests we have on, they know
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their stuff we don't deal with. They don't,
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you know, the ones that want questions in advance are the ones we don't want.
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Because if you can't answer the questions on what you
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do every day, then you're not the person who should be interviewed from my
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perspective. So you're game. I appreciate
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it. Our listeners and viewers should appreciate it as well.
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So thank you for doing that. But as I listen to you
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talk, what's coming to mind is another digital divide happening.
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Old school it was who had the Internet and who doesn't?
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And what are the ramifications of that? Is this new
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era going to be who adopts AI and just, you know,
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catapults into the future versus those who don't and are
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just slogging along? I don't think that exists anymore.
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And if we could play back our initial.
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Our first time we were on together, Amia talked about how the
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modern company is democracy. It's personalization,
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and democratization are keywords every organization has to understand.
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And so, you know, back in the day, we want to democratize access to
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water. Everyone should get water. We want to democratize access to
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education, you know, real media, like real storytelling.
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And so we're working on those things. That's continued.
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So when you think about that divide, I don't, again,
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don't quote me on this, but what we're starting to see out there, like,
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data is coming back, right? There is a belief,
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actually, Jackie, that more people in the world have
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access to a device and AI than
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that have clean, portable water and sanitation.
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Wow. So that's one thing.
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And so access, actually, if you have a smartphone, and so doesn't mean if
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you're in the Philippines or in Africa or in the United States, if you
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have a smartphone, you have access to AI. So that's one piece.
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The second piece is now we've also democratized leveraging or
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building on AI. So if you go to, for instance,
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like chats, you're, if you go to OpenAI, for example, we launched our first GPT
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in January of this year. So that was almost nine months ago.
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So built on that GPT,
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we do a lot of work in strategy and okrs.
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We built a GPT in which anyone in the world can use to
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help them craft okrs. We built it for free.
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It's take a lot of learning, but we built it. It's less than a
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day and anyone can do that. But anyone,
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Jackie, now with a little bit of dollars just to pay for your
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premium subscriptions, can build powerful GPTs,
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can start building solutions in AI. In fact, tech AI
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itself is allowing anyone to be able to code and build their own AI solution.
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So I'm not certain the way, if some people frame that
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the divide is actually big. It's whether or not you have the appetite,
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the courage and the discipline and the rigor to leverage
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this technology that's at your fingertips. Okay? So it's not like it's
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a young person's game. Anyone can learn this stuff, is what you're saying?
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100%. Okay. Because that brings to mind when
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we had Gary Vee on the show. He was talking about how he
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goes around to companies and, you know, he talks to the senior VP
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or who's ever in trouble. And they're saying they rely on staff
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to do the research and tell them what things mean because they're out
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of date with the technology and they don't understand it.
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And Gary's basic response is, anyone can learn this, sit down and do it,
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you know? So you're saying the same thing with AI. I am.
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Okay, now let's, let's. And can I give you a quick story,
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Jackie? And you know, I like to tell stories, so I use.
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I can use a lot, but let me just use one. Do you remember?
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It was probably about when I first started getting on stages. It was around 2017,
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and one of the things I talked about was saying, and this is when particularly
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sorry to pick on baby boomers, but baby boomers and older, we're poo pooing
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on the millennial lazy entitled,
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our world's like, we're done. These millennials are going to destroy
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the world. And here was the narrative. They're all stuck on this
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smartphone device thingy on this app called Facebook,
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soul sucking and wasting all their time. Within two
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years after that time, whenever it was 2017, whatever it was, I was getting on
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stages. Who became the biggest adopters of Facebook?
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The baby boomer. Why? Because they finally
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saw the value proposition of connecting with high school friends,
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old college sweethearts, getting pictures and videos of their
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grandkids selling stuff on marketplace. They were now
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getting value. The millennials went on to Instagram, Snapchat,
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TikTok, etcetera. So the story here is that as soon as
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you derive value, you're going to adopt. And AI
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is going to derive value in people faster than Facebook or the
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smartphone did. And most people are going to learn that AI is all around them
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anyway. They're using it. It's being machine learning.
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Everything they're using every app they use, the phone, they use, the gps,
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everything. And so when they figure that out and they start playing
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around with some AI tools, they're going to see it. They're going to say,
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I don't care if you're 40 years old or 80 years old,
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I want on this bandwagon. I think. All right,
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well, it's encouraging, and I like to think that that
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will happen. And it's interesting, as we're seeing from the
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pandemic, that older demographic, the baby boomers,
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are having a tough time disengaging from technology because
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they learned how to spend so much time on it during when we
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were all shut down pandemic. So that's kind of interesting and
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kind of funny, too, for the way they denounced it in the beginning.
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Exactly. And so AI, understandably,
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when your reference point is Terminator and irobot and
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matrix, your first inclination for older generation
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might be it's the end of the world and it's becoming a less human world
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where I have a stance, Jackie, that AI actually will
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help to create a more human world. And I'm happy to talk about that,
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too. Yeah, I was just going to say, can you.
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So let's. Let's just have a conversation between the two of us. Right.
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And, and hopefully resonates with the audience. If I asked you,
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Jackie, you were getting, having to
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take some kind of a scan, like a health scan, like you're seeing if there's
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any sinister disease within you. Yeah. And I told you that
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the human who is looking at that reading the report is
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85% accurate at detecting disease.
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And the robot was 95%. Who are you choosing?
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Yeah, you're going to go with the robot. Okay. So of course
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you would. The 10% delta. But what if I told you the next few years,
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as we're all coexisting with AI, that together,
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it would be 99%. Okay, so the first story
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is, AI is not about just killing all of our jobs. 100% is
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going to take away jobs. It's going to create more jobs. But if we can
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learn to embrace it and work together, we're going to get better outcomes.
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Let's keep the story going, Jackie. Okay. What if you
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were unfortunately diagnosed with that said sinister disease?
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Who do you want helping you through treatment and recovery. A human
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or a robot? Okay, well, here's a little bit gray area
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for me, because I'm thinking the robot may be
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more accurate, but the human would be able to employ,
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well, what ifs in a more gray area, or am I wrong?
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I think it's a human. I think most people want a human experience in
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times like that. And so AI, if most
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people said a human, right? This is probably one of our biggest complaints in the
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healthcare system, is that we're just numbers. We go and we get bad diagnosis,
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we don't get right treatment. We're just a number. Things are wrong. And then the
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nurses and doctors are always rushing, well, what if technologies,
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including AI, could be better at diagnosing and getting
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prognosis and treatment where you could actually have a relationship
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with your physicians and nurses to help create a human experience
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when you need it most? That's the future, in my opinion.
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And if you take almost any job out there, imagine if you could get AI
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and other technology to do the work. The day to day tasks no one
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likes to do, no one's good at, no one's perfectly accurate.
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Let them do that. What will it allow you to do? Create better relationships
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with your customers and better relationships with your team members and
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all your other stakeholders. Like, we're so bogged down on make work
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and other meaningless work that robots can do. We fell away from what
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we all need inherently, which is human connection, and I think
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that's what's going to happen. Okay. Any thoughts on why
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we're not hearing about this in the news media?
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Well, maybe there are. I don't know.
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I think that it's not. I think generally, media speaking, I'm not media
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savvy like you are, but my understanding is media generally
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is the doom and gloom and the scare things, and it's like that basic
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fight or flight stuff. And we want to hear about the car crashes and AI
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taking over the world and saying that, going out there
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and saying, no, actually, there are less people in poverty today,
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that the world is safer today, that AI is not misfor
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bad. I don't think that just generally gets pressed. That's just my observation
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as a consumer of content. But other than that,
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I have no. I don't know why. And maybe it's not even. You know what,
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Jack? Maybe it's not even a prevailing thought. That's just what I think and what
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I believe strongly and why we do what we do in
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my company. Yeah. Okay. Fair enough.
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Everyone's observations about what's in the news is
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always interesting to me because no one's wrong. You're bringing your
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own lens to it. So to hear someone else explain
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what they're seeing is always educational.
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That brings me to the next point I want to bring up, which is education.
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One thing we know for sure is technology moves
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fast, education moves slow.
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So there's a big gap there between
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what even the teachers know in terms of what they need to
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teach the kids in terms of advanced technologies.
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Any idea on how that's playing out now that we've
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really ramped things up with AI? So it's a concern of mine for
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sure. I think the statement is it's education is slow, at least in North
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America context for sure. I think if you look at some other places,
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like in Tel Aviv or Singapore, there's other jurisdictions around the world, countries around the
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world who are adopting it much faster and are less,
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have much, a little bit more risk tolerance, maybe, if you want to call it
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that. So I'm not, it's not global, but that is a risk generally, by the
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way, to North America. I think we're falling behind in a lot of, it's not
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just math and science. We're falling behind in other areas.
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So I think that there's a problem, and it's something that I have a 14
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year old daughter. She's now in high school, and people ask
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me all the time, like, what kind of career is she going to get into?
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Is she being set up for success there? And then I have
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nieces, nephews, etcetera, even younger. So anyway, to get back to the
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question, I think that theres absolutely a disconnect. We believe strongly
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in all contexts of innovation to work as an
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ecosystem. And this is part of the challenge, I believe what would
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happen if we actually forget about these four year terms
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and self serving agendas, et cetera. Let's actually bring
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together the stakeholders of an ecosystem, education, which are parents,
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which are the students, which of course our government, which is other
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bodies. Get them together and actually try to solve this problem together.
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We don't do enough of that. And I recognize, Jack, it's a
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big nut to crack. But what's the opposite or what's the alternative?
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The alternative is keep doing what we've always done.
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Yeah. Not being able to find any employees that are qualified. Jeff.
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No. And then you. And then, and so now we go down this rabbit hole.
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So, like, you can think about immigration and what happens if the talent
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that we organizations need don't exist in our own countries
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and we have to go overseas to bring them here. Well, that doesn't always go
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over well with everyone. And I'm not making it's a political conversation. But what
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are we doing to upskill reskill, and redeploy talent in
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our own country? It is a pretty big concern, I think, for me, because this
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world's moving fast, and we're not digitally savvy enough.
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Now you're getting me excited about this. Oh, my gosh.
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I hear people. I've got another goddaughter in university.
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They're not allowed to use AI in their course. Really? And I think,
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yeah. And I think, okay, so what are you preparing them for in the future?
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So you go do it. Doesn't matter what the course is. Agnostic to the course.
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Maybe there's some that. Maybe they're outliers. But you're
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gonna continue to go through four years or the next two years for her.
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No use of AI. And then when she graduates, the employer's gonna
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ask her, how might you use AI? Or what are you.
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Are you up to speed with how we're using AI in her company? You failed
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her. Yeah. You failed. Bringing her the experiences she
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needs for. The real world, it's kind of scary.
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It can be, but the alternative is scary, too,
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right? So there's. And I. And again, I love it. This is just my perspective.
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Right. I'm more of a technology guy. I'm a glass half full guy. I'm about
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full throttle, modern throttle, like, modernize your business
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guy. So I may be on an extreme,
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but, hey, look, if you worry, if you have anyone
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in the educational system, I would really challenge yourself
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to say, are we preparing our youth for the future
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that is here? The future is now. That's the name of my company.
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And we can't just wait for some future to arrive,
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particularly in government, in education, where historically,
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we're just slow to move. All right, pros and cons,
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large corporations versus, you know, scrappy startup,
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who would you give the edge? Oh, the edge goes to scrappy startup
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ten times out of ten. But it's not as. It's not as close as people
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think, as some people think. So there's lots of pros.
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What's the pros of the startup? Well, they're solving real problems.
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The startup exists to disrupt the incumbent, so they have
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to be innovative. They got to do something different. They've got to be agile.
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These are all the things that we. We believe and train on the. And they
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have to be laser focused on a customer. Right. Like, we have
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to solve a problem for a user, a customer,
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whoever, using the most innovative ways. And we got to be agile and we're
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going to do as quickly as we can. So there's benefits to that. They're going
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to deploy modern technology, they can adopt things quickly. Now, what's on the flip side?
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The flip side is they don't have customers, they don't have proof of concept,
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they don't have any like long term, even a bank account.
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You go to the enterprise, what are the pros and cons there?
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Let's start with the pros. They have customers,
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they have intelligent people who have built in systems
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and processes and all these things. They have cash flow and all that
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stuff. What's the negative? They can get complacent.
453
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It's hard to move the ship. They're not naturally innovative.
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They're most certainly not agile. And so what we're seeing, so there's
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pros and cons of both. I give the edge to startup just by
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a margin. But what's happening now in the enterprise world we're seeing
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is that if we can't keep up with them, and we used to try
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to create the accelerator, the incubator, the startup, the ventures in
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our company, and it's just not helping. They're just going to acquire these startups anyway.
460
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So they're kind of connected. Right? It's like, which one gets the edge?
461
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Well, like we, can we.
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Yeah. Anyway, so it's a very fascinating question.
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I just have to like the startup model. Okay. All right. So tell
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me though, when your name is now of work, how do
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you, ahead of the curve, what are you looking at?
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Well, technology is so there's three components that I believe every
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company, when a company's struggling to stay modern. Jackie, there's a couple
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of things here. One is the people and culture, for sure.
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And the culture is bottom up. The people
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to me is top down, meaning that without modern leaders with
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a growth mindset who are staying abreast of what's happening,
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your company is never going to stay afloat because they're the decision makers and you're
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going to lose talent because of them. So number one, the people, the leadership,
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have to change and reframe what it means to be a leader, operating at level,
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all these things. And let's create a culture that's really, truly bottom
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up and let's be aligned the second two pieces around innovation
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and agility. And so what we're seeing on the innovation side is you've got
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to constantly be scanning your environment. What are your contemporaries
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doing? What are the technologies that might disrupt your business?
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And are we constantly testing new things and challenging our assumptions and all
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that? That's part of being innovative and even having a strategy.
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And then the agile piece is really how we train about what's a modern strategy
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look like? What is it planning annually, quarterly,
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executing in two weeks, sprints and all that things. And so when
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we're looking at any company agnostic to sector,
486
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if you do those three things, you're going to find your path
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of where that future is going. Because I can't tell you what it is,
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but I can tell you the frameworks and provide the frameworks for you to figure
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that out, or at least guess with more certainty of where
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that future is going. And it's different for everybody.
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Okay, can you tell me what a healthy culture looks like?
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Oh, man. Like, okay. In my context, it's definitely
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inclusive. You know, I'm very big on. I think diversity wins
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in all contexts, and that doesn't mean how people look. I'm big
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more on diversity of thought and experience and backgrounds. And so
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if we can have companies that value diversity,
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regardless of what you look like, do we dissent?
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Do we bring varying degrees of insight? And do we challenge each other
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like that? That's diversity to me. I think that they have
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to democratize the business. We pay the leaders
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to make tough decisions, but we want the bottom
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up insights of those who are talking with customers who actually
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know the problem to solve, to be able to at least share and opine into
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the process. They're not the decision makers, but let them. Allow them be part of
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that business, I think is a big piece of that. And then that culture
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again, I keep going back to what I believe in, that culture of agility.
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We've got to create cultures where people are.
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The Fair Media Council is a 501 nonprofit organization
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00:30:12,346 --> 00:30:16,314
advocating for quality news and working to create a media savvy
510
00:30:16,362 --> 00:30:19,554
society. For more information about the Fair Media council
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00:30:19,642 --> 00:30:24,050
and upcoming fast chat shows, check out fairmediacouncil.org.
00:00:01,240 --> 00:00:04,758
FMC fast chat takes you inside the news so you can be
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00:00:04,774 --> 00:00:08,990
in the know in 30 minutes. Hosted by Fair Media Council CEO
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00:00:09,070 --> 00:00:13,294
and executive director Jackie Clement, Fastchat features notables in
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news, media and business.
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Hey, everyone. Welcome back to FMC Fast Chat, where media
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meets influence. I'm your host, Jackie Klimet,
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and today's episode is all about transforming the
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way we work, lead, and innovate. We're going
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to talk about what it takes to shift from a typical business mindset and
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culture to something much more forward thinking and
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media savvy. I've got the perfect guest to break it
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all down for us. Rocky Ozaki,
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founder of now of Work. Rocky has been leading the
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charge in helping businesses move into the future, and his AI
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adoption program has already transformed companies in
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Canada and throughout the US. Plus,
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Rocky is sharing the stage with folks like Arnold Schwarzenegger and Gary
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Vaynerchuk when he's doing keynote addresses. So,
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you know, he's bringing serious insights on leadership,
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innovation and the future of work. Now,
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let's find out the latest from Rocky Ozaki.
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Let's go, Rocky. It's so great to have you back with us. I think
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the last time we spoke was early in the pandemic, if I'm not mistaken.
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It's true. I actually, Jackie, I look back, it was June 2021.
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Okay. All right, so it's another different world that we're living
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in. I'm wondering if we can start kind of with a broad question
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and you break it down however you want. I'm wondering,
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you know, from what you do with leading and transforming companies,
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you go all over the place. You're typically all over North America working
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with businesses. What are you actually seeing on the ground?
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Like what? How big of a gap is there between what
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businesses are doing versus where they should be and where their mindset
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should be? Okay, so that is a great segue
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that when we last talked, because in 2021, June, we were
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replying or responding to the impact of lockdown and
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challenging assumptions of work and life and how everything was changed
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post pandemic. So it's timely because now it's AI.
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And I think that's a lot of our conversation today. But the
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gap is pretty big. So when I
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would say that if we focus just on AI for a second,
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when chat CPT dropped almost two years ago,
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the world kind of like, it was like, oh, my gosh, I think the fastest
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to 100 million users, everyone started using it, but then it kind of slowed down
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or they weren't using it in ways strategically which I'm sure we'll talk about.
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So from the contents of AI, what we're seeing, absolutely, is that there was a
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shiny new object. People jumped on the bang bandwagon.
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A lot of them jumped off or just started shotgunning, and it's actually
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put them further behind Jackie. So AI to me,
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actually is real. It is not a fad. It's going to be the fabric of
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every organization. But the chasm grew up.
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I don't know why we're still trying to figure this out too, but it's a
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pretty big gap, at least in the context of AI in the modern company.
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Yeah. I'm wondering, though, it just seems like everything changed
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very quickly and a lot of technology came at us very fast.
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Do you credit that with the pandemic and the technologists
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and having nothing else to do? Well, it's part of that, and you can
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think back. And so when the pandemic hit, what did
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we see? We saw that supply chain broke down. We saw
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that organizations who used to say, we'll never go virtual and we'll never always
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have offices, well, they had no choice. And so in the back of the
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scenes, what happened was all of a sudden now companies, the leading companies,
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were starting to say we need to double down on what we call Horizon two
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of innovation, which is like this three to five year timeframe. So we had
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to accelerate automation because we saw supply chain issues.
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We saw how now talent, well, you know, pretty much every jurisdiction around North America
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is having a tough time finding talent,
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like, even if for the corner store, in the small shop. So now we had
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to look at way automating things, even at the grocery store, whatever. AI for
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web three, spatial computing, this whole idea of VR,
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Mister XRD, part of it was, you're right, we were in lockdown,
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but part of it was out of necessity. And we all again said, as I
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said before, we challenge our assumptions of work
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life and business. And so that accelerated these technologies.
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Okay, all right, tell me a little bit about web three,
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because that's something we started to hear about and then suddenly dropped off
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the radar. It certainly has. And I think a lot of the
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web three component of being in the metaverse and stuff like that is just the
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use cases are very, a lot of it's in gaming or a lot of it's
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in very small niches. I think it's going to blow up.
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But there's this notion that in web one,
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it was like Internet. We created a website,
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and then in web two, you might call it that, and then all of a
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sudden we were building communities. We were starting to be able to contribute
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onto the Internet. We were allowed to bring our own content and conversation. There's a
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lot more to this, by the way. I'm dumbing it down. And now web three
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is saying, well, a lot of things like who owns the data and
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where do we actually live in web three and virtual worlds?
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And this is why it's more than just web three, why it's blockchain,
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and why it's spatial computing and all these different components of it is
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that there is this next step of how we're going to interact in
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the Internet. Who owns data in this world?
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And so it's a pretty interesting place, but I think it definitely is lagging behind
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AI, for example. Okay, so let's focus on
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Aih. You have an AI adoption program, and. I say this
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kind of jokingly, but it's true. So many companies like,
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oh, we're AI, we use AI, we use chat,
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GPT, and we have a meeting, you know, meeting, recording device
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or some, some kind of, like, I won't promote any particular company, but we
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record our meetings, our virtual meetings, we get summaries and all of a sudden we
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use AI. So what our program was built to show with them
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is, number one, there's three stages, in our opinion, on adopting
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AI initially, and the first one, and really quickly,
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is AI readiness. So in the first part
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of our program is, it's a twelve week program, by the way, and we're going
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to actually talk about governance, responsible use of AI.
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What are your objectives of using AI? Is your team members
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even ready for it? We've seen, Jackie,
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a lot of organizations adopt AI without proper communications,
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without proper governance. You can call that, and team members
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quit, customers leave, because like,
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what the heck is going on? So our first part is like,
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are you actually AI ready? And then the second part is around AI
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experimentation. And so we do a couple things. We can break these down if any
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of these are interesting to you, but one is use cases. And so
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we try to democratize that process throughout the organization.
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So we teach you to say across your whole organization, what friction points
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are there? What problems are you trying to solve as someone working with customers,
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building an AI backlog and then trying to prioritize
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where there's potential impact and value versus,
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let's go use this meeting recording software because our buddy told
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us to use it. That's not strategic and it's not aligned to strategy and other
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things. And the third part of our component is around scaling
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AI. And so that's around building roadmaps, around building repeatable
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and predictable ways in which you're going to use Aih. And so that's the
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way the program is formed and that's the problem we're trying to solve, is use
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AI properly and create a culture
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where it's embraced and people understand the impact and purpose and all that
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sort of things. And they use it responsibly, which is key.
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My perspective, too. Well, it certainly aligns to the value
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proposition of what you and your teams do. Yes. And it's
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big. And every, in the United States, like every state, has different regulations.
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And I, there are things happening that people may not know about.
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So, Jack, you may recall at GDPR in the UK,
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we're talking about, they're sort of the leaders in how we protected
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data. Well, what we're thinking, Jackie, is that,
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and no one watching this quote me on this. I'm not,
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this is what I'm observing is that we are going to start
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to see, because governments are listening and they're really
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interested in AI, obviously. And just anecdotally,
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when I'm sitting in webinars or conferences, what I'm hearing, for example,
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I'm based in Canada right now. Most of, well, actually most of our business
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is us, but in Canada, we're taking a very,
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very cautious approach. And United
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States is very pro innovation right now.
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And if you were to talk about GDPR sort of being the standard
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in the middle, the US is biasing one way. Canada,
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for example, is biasing the other ways. And this is going to have some implications
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on responsible use when you're bringing it to your customers and
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your team members is what is your government looking at in
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terms of regulations? These things, I think are around the corner.
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Okay. All right. That's going to be interesting and something to watch
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for as that rolls out. Tell me,
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let's go on the flip side of the equation. What organizations do you
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see that have either adopted,
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were early adopters, have their act together when it comes
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to AI or the ones that you can point people to, to say,
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here's a good example of what you should be doing.
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They don't really exist.
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And I was thinking indictment, maybe it's the people that we interact with.
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It's just so new. Right, Jackie? And many companies
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aren't big enough. And so we play mostly in SMB.
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Right. So that's context there. And we had a few big, big organizations
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as clients, but the most is SMB. And so why that matters
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is, in my view, the context of our interaction with
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clients is they don't have ctos. CIO's always like,
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they may have some head of technology, they don't have those roles or
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chief innovation officers and risk officers that large enterprise
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do. And so in our world, in the SMB
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world, under 100 million in revenue,
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they even 50 million in revenue, for that matter, they don't,
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they're shotgunning. This is new to them. And even if
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you are a large organization, Jackie, this law, the playbook,
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is just still being written on the fly. And so when you ask me,
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like, who's doing it right, I would say, broadly speaking, the ones
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that are doing it right are the ones that are using the playbook
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I described. Let's just pause for a second and let's just think about
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what kind, what is our purpose of using AI, what are our objectives?
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What kind of responsibility does that look like? Let's slowly
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adopt AI, socialize it really well with our organization,
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and continue to gain value through that. And the other
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big piece of what we train in our program, Jackie, is around metrics.
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So if you're going to adopt, actually, you know what, there are companies that do
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it well, now that I talk, because I don't know what you're going to ask
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me. So what I would describe as a company is doing it well,
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are ones that say, listen, let's go back to the meeting software,
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the AI, okay, you can adopt that, pilot it.
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The winning company is saying, let's pilot it for three months. What is
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the problem we're trying to solve? It is trying to get good summaries
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of meetings for those that weren't in attendance. It is. The problem
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to solve is I'm missing 20% of the meetings and I'm a
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busy executive. I like to get a summary. So we're really understanding why.
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Okay. And then bacon metrics, Jackie, over those three months of pilot,
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whatever that pilot period is. So getting feedback from the users,
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how accurate are the summaries and actually measurable outcomes that,
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say, at the end of the pilot, do we pivot,
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persevere or punt? These are the three P's that we
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always talk about. Persevere quickly means or pivot the story. Pivot.
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It's getting some value, but we need to make some changes, but we're going
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to stay the course. Persevere says it's working, it gets solving
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the problems, it's hitting our metric. Let's cascade this further or
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unlock more features, whatever it is. And punt says it's not
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doing what we thought it would do. Let's fail fast, punt it
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and try something different. So winning companies are following the
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framework again that we teach. Got it. Now,
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as I'm listening to you talk, and by the way, I should point out,
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you don't know the questions I'm going to ask.
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Standard format with us, the guests we have on, they know
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their stuff we don't deal with. They don't,
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you know, the ones that want questions in advance are the ones we don't want.
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Because if you can't answer the questions on what you
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do every day, then you're not the person who should be interviewed from my
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perspective. So you're game. I appreciate
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it. Our listeners and viewers should appreciate it as well.
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So thank you for doing that. But as I listen to you
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talk, what's coming to mind is another digital divide happening.
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Old school it was who had the Internet and who doesn't?
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And what are the ramifications of that? Is this new
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era going to be who adopts AI and just, you know,
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catapults into the future versus those who don't and are
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just slogging along? I don't think that exists anymore.
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And if we could play back our initial.
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Our first time we were on together, Amia talked about how the
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modern company is democracy. It's personalization,
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and democratization are keywords every organization has to understand.
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And so, you know, back in the day, we want to democratize access to
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water. Everyone should get water. We want to democratize access to
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education, you know, real media, like real storytelling.
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And so we're working on those things. That's continued.
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So when you think about that divide, I don't, again,
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don't quote me on this, but what we're starting to see out there, like,
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data is coming back, right? There is a belief,
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actually, Jackie, that more people in the world have
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access to a device and AI than
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that have clean, portable water and sanitation.
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Wow. So that's one thing.
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And so access, actually, if you have a smartphone, and so doesn't mean if
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you're in the Philippines or in Africa or in the United States, if you
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have a smartphone, you have access to AI. So that's one piece.
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The second piece is now we've also democratized leveraging or
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building on AI. So if you go to, for instance,
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like chats, you're, if you go to OpenAI, for example, we launched our first GPT
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in January of this year. So that was almost nine months ago.
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So built on that GPT,
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we do a lot of work in strategy and okrs.
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We built a GPT in which anyone in the world can use to
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help them craft okrs. We built it for free.
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It's take a lot of learning, but we built it. It's less than a
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day and anyone can do that. But anyone,
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Jackie, now with a little bit of dollars just to pay for your
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premium subscriptions, can build powerful GPTs,
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can start building solutions in AI. In fact, tech AI
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itself is allowing anyone to be able to code and build their own AI solution.
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So I'm not certain the way, if some people frame that
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the divide is actually big. It's whether or not you have the appetite,
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the courage and the discipline and the rigor to leverage
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this technology that's at your fingertips. Okay? So it's not like it's
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a young person's game. Anyone can learn this stuff, is what you're saying?
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100%. Okay. Because that brings to mind when
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we had Gary Vee on the show. He was talking about how he
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goes around to companies and, you know, he talks to the senior VP
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or who's ever in trouble. And they're saying they rely on staff
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to do the research and tell them what things mean because they're out
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of date with the technology and they don't understand it.
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And Gary's basic response is, anyone can learn this, sit down and do it,
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you know? So you're saying the same thing with AI. I am.
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Okay, now let's, let's. And can I give you a quick story,
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Jackie? And you know, I like to tell stories, so I use.
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I can use a lot, but let me just use one. Do you remember?
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It was probably about when I first started getting on stages. It was around 2017,
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and one of the things I talked about was saying, and this is when particularly
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sorry to pick on baby boomers, but baby boomers and older, we're poo pooing
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on the millennial lazy entitled,
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our world's like, we're done. These millennials are going to destroy
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the world. And here was the narrative. They're all stuck on this
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smartphone device thingy on this app called Facebook,
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soul sucking and wasting all their time. Within two
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years after that time, whenever it was 2017, whatever it was, I was getting on
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stages. Who became the biggest adopters of Facebook?
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The baby boomer. Why? Because they finally
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saw the value proposition of connecting with high school friends,
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old college sweethearts, getting pictures and videos of their
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grandkids selling stuff on marketplace. They were now
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getting value. The millennials went on to Instagram, Snapchat,
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TikTok, etcetera. So the story here is that as soon as
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you derive value, you're going to adopt. And AI
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is going to derive value in people faster than Facebook or the
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smartphone did. And most people are going to learn that AI is all around them
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anyway. They're using it. It's being machine learning.
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Everything they're using every app they use, the phone, they use, the gps,
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everything. And so when they figure that out and they start playing
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around with some AI tools, they're going to see it. They're going to say,
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I don't care if you're 40 years old or 80 years old,
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I want on this bandwagon. I think. All right,
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well, it's encouraging, and I like to think that that
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will happen. And it's interesting, as we're seeing from the
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pandemic, that older demographic, the baby boomers,
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are having a tough time disengaging from technology because
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they learned how to spend so much time on it during when we
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were all shut down pandemic. So that's kind of interesting and
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kind of funny, too, for the way they denounced it in the beginning.
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Exactly. And so AI, understandably,
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when your reference point is Terminator and irobot and
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matrix, your first inclination for older generation
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might be it's the end of the world and it's becoming a less human world
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where I have a stance, Jackie, that AI actually will
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help to create a more human world. And I'm happy to talk about that,
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too. Yeah, I was just going to say, can you.
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So let's. Let's just have a conversation between the two of us. Right.
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And, and hopefully resonates with the audience. If I asked you,
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Jackie, you were getting, having to
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take some kind of a scan, like a health scan, like you're seeing if there's
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any sinister disease within you. Yeah. And I told you that
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the human who is looking at that reading the report is
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85% accurate at detecting disease.
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And the robot was 95%. Who are you choosing?
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Yeah, you're going to go with the robot. Okay. So of course
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you would. The 10% delta. But what if I told you the next few years,
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as we're all coexisting with AI, that together,
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it would be 99%. Okay, so the first story
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is, AI is not about just killing all of our jobs. 100% is
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going to take away jobs. It's going to create more jobs. But if we can
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learn to embrace it and work together, we're going to get better outcomes.
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Let's keep the story going, Jackie. Okay. What if you
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were unfortunately diagnosed with that said sinister disease?
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Who do you want helping you through treatment and recovery. A human
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or a robot? Okay, well, here's a little bit gray area
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for me, because I'm thinking the robot may be
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more accurate, but the human would be able to employ,
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well, what ifs in a more gray area, or am I wrong?
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I think it's a human. I think most people want a human experience in
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times like that. And so AI, if most
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people said a human, right? This is probably one of our biggest complaints in the
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healthcare system, is that we're just numbers. We go and we get bad diagnosis,
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we don't get right treatment. We're just a number. Things are wrong. And then the
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nurses and doctors are always rushing, well, what if technologies,
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including AI, could be better at diagnosing and getting
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prognosis and treatment where you could actually have a relationship
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with your physicians and nurses to help create a human experience
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when you need it most? That's the future, in my opinion.
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And if you take almost any job out there, imagine if you could get AI
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and other technology to do the work. The day to day tasks no one
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likes to do, no one's good at, no one's perfectly accurate.
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Let them do that. What will it allow you to do? Create better relationships
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with your customers and better relationships with your team members and
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all your other stakeholders. Like, we're so bogged down on make work
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and other meaningless work that robots can do. We fell away from what
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we all need inherently, which is human connection, and I think
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that's what's going to happen. Okay. Any thoughts on why
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we're not hearing about this in the news media?
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Well, maybe there are. I don't know.
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I think that it's not. I think generally, media speaking, I'm not media
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savvy like you are, but my understanding is media generally
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is the doom and gloom and the scare things, and it's like that basic
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fight or flight stuff. And we want to hear about the car crashes and AI
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taking over the world and saying that, going out there
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and saying, no, actually, there are less people in poverty today,
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that the world is safer today, that AI is not misfor
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bad. I don't think that just generally gets pressed. That's just my observation
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as a consumer of content. But other than that,
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I have no. I don't know why. And maybe it's not even. You know what,
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Jack? Maybe it's not even a prevailing thought. That's just what I think and what
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I believe strongly and why we do what we do in
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my company. Yeah. Okay. Fair enough.
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Everyone's observations about what's in the news is
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always interesting to me because no one's wrong. You're bringing your
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own lens to it. So to hear someone else explain
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what they're seeing is always educational.
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That brings me to the next point I want to bring up, which is education.
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One thing we know for sure is technology moves
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fast, education moves slow.
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So there's a big gap there between
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what even the teachers know in terms of what they need to
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teach the kids in terms of advanced technologies.
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Any idea on how that's playing out now that we've
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really ramped things up with AI? So it's a concern of mine for
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sure. I think the statement is it's education is slow, at least in North
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America context for sure. I think if you look at some other places,
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like in Tel Aviv or Singapore, there's other jurisdictions around the world, countries around the
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world who are adopting it much faster and are less,
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have much, a little bit more risk tolerance, maybe, if you want to call it
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that. So I'm not, it's not global, but that is a risk generally, by the
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way, to North America. I think we're falling behind in a lot of, it's not
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just math and science. We're falling behind in other areas.
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So I think that there's a problem, and it's something that I have a 14
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year old daughter. She's now in high school, and people ask
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me all the time, like, what kind of career is she going to get into?
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Is she being set up for success there? And then I have
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nieces, nephews, etcetera, even younger. So anyway, to get back to the
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question, I think that theres absolutely a disconnect. We believe strongly
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in all contexts of innovation to work as an
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ecosystem. And this is part of the challenge, I believe what would
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happen if we actually forget about these four year terms
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and self serving agendas, et cetera. Let's actually bring
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together the stakeholders of an ecosystem, education, which are parents,
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which are the students, which of course our government, which is other
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bodies. Get them together and actually try to solve this problem together.
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We don't do enough of that. And I recognize, Jack, it's a
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big nut to crack. But what's the opposite or what's the alternative?
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The alternative is keep doing what we've always done.
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Yeah. Not being able to find any employees that are qualified. Jeff.
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No. And then you. And then, and so now we go down this rabbit hole.
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So, like, you can think about immigration and what happens if the talent
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that we organizations need don't exist in our own countries
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and we have to go overseas to bring them here. Well, that doesn't always go
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over well with everyone. And I'm not making it's a political conversation. But what
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are we doing to upskill reskill, and redeploy talent in
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our own country? It is a pretty big concern, I think, for me, because this
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world's moving fast, and we're not digitally savvy enough.
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Now you're getting me excited about this. Oh, my gosh.
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I hear people. I've got another goddaughter in university.
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They're not allowed to use AI in their course. Really? And I think,
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yeah. And I think, okay, so what are you preparing them for in the future?
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So you go do it. Doesn't matter what the course is. Agnostic to the course.
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Maybe there's some that. Maybe they're outliers. But you're
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gonna continue to go through four years or the next two years for her.
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No use of AI. And then when she graduates, the employer's gonna
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ask her, how might you use AI? Or what are you.
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Are you up to speed with how we're using AI in her company? You failed
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her. Yeah. You failed. Bringing her the experiences she
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needs for. The real world, it's kind of scary.
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It can be, but the alternative is scary, too,
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right? So there's. And I. And again, I love it. This is just my perspective.
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Right. I'm more of a technology guy. I'm a glass half full guy. I'm about
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full throttle, modern throttle, like, modernize your business
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guy. So I may be on an extreme,
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but, hey, look, if you worry, if you have anyone
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in the educational system, I would really challenge yourself
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to say, are we preparing our youth for the future
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that is here? The future is now. That's the name of my company.
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And we can't just wait for some future to arrive,
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particularly in government, in education, where historically,
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we're just slow to move. All right, pros and cons,
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large corporations versus, you know, scrappy startup,
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who would you give the edge? Oh, the edge goes to scrappy startup
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ten times out of ten. But it's not as. It's not as close as people
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think, as some people think. So there's lots of pros.
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What's the pros of the startup? Well, they're solving real problems.
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The startup exists to disrupt the incumbent, so they have
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to be innovative. They got to do something different. They've got to be agile.
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These are all the things that we. We believe and train on the. And they
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have to be laser focused on a customer. Right. Like, we have
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to solve a problem for a user, a customer,
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whoever, using the most innovative ways. And we got to be agile and we're
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going to do as quickly as we can. So there's benefits to that. They're going
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to deploy modern technology, they can adopt things quickly. Now, what's on the flip side?
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The flip side is they don't have customers, they don't have proof of concept,
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they don't have any like long term, even a bank account.
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You go to the enterprise, what are the pros and cons there?
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Let's start with the pros. They have customers,
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they have intelligent people who have built in systems
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and processes and all these things. They have cash flow and all that
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stuff. What's the negative? They can get complacent.
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It's hard to move the ship. They're not naturally innovative.
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They're most certainly not agile. And so what we're seeing, so there's
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pros and cons of both. I give the edge to startup just by
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a margin. But what's happening now in the enterprise world we're seeing
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is that if we can't keep up with them, and we used to try
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to create the accelerator, the incubator, the startup, the ventures in
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our company, and it's just not helping. They're just going to acquire these startups anyway.
460
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So they're kind of connected. Right? It's like, which one gets the edge?
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Well, like we, can we.
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Yeah. Anyway, so it's a very fascinating question.
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I just have to like the startup model. Okay. All right. So tell
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me though, when your name is now of work, how do
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you, ahead of the curve, what are you looking at?
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Well, technology is so there's three components that I believe every
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company, when a company's struggling to stay modern. Jackie, there's a couple
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of things here. One is the people and culture, for sure.
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And the culture is bottom up. The people
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to me is top down, meaning that without modern leaders with
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a growth mindset who are staying abreast of what's happening,
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your company is never going to stay afloat because they're the decision makers and you're
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going to lose talent because of them. So number one, the people, the leadership,
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have to change and reframe what it means to be a leader, operating at level,
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all these things. And let's create a culture that's really, truly bottom
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up and let's be aligned the second two pieces around innovation
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and agility. And so what we're seeing on the innovation side is you've got
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to constantly be scanning your environment. What are your contemporaries
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doing? What are the technologies that might disrupt your business?
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And are we constantly testing new things and challenging our assumptions and all
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that? That's part of being innovative and even having a strategy.
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And then the agile piece is really how we train about what's a modern strategy
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look like? What is it planning annually, quarterly,
484
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executing in two weeks, sprints and all that things. And so when
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we're looking at any company agnostic to sector,
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if you do those three things, you're going to find your path
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of where that future is going. Because I can't tell you what it is,
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but I can tell you the frameworks and provide the frameworks for you to figure
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that out, or at least guess with more certainty of where
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that future is going. And it's different for everybody.
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Okay, can you tell me what a healthy culture looks like?
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Oh, man. Like, okay. In my context, it's definitely
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inclusive. You know, I'm very big on. I think diversity wins
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in all contexts, and that doesn't mean how people look. I'm big
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more on diversity of thought and experience and backgrounds. And so
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if we can have companies that value diversity,
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regardless of what you look like, do we dissent?
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Do we bring varying degrees of insight? And do we challenge each other
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like that? That's diversity to me. I think that they have
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to democratize the business. We pay the leaders
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to make tough decisions, but we want the bottom
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up insights of those who are talking with customers who actually
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know the problem to solve, to be able to at least share and opine into
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the process. They're not the decision makers, but let them. Allow them be part of
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that business, I think is a big piece of that. And then that culture
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again, I keep going back to what I believe in, that culture of agility.
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We've got to create cultures where people are.
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The Fair Media Council is a 501 nonprofit organization
509
00:30:12,346 --> 00:30:16,314
advocating for quality news and working to create a media savvy
510
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