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I think AI now is starting to become a tool where where which I'm seeing now a lot is is the prompting piece.
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It's becoming more and more critical.
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For me, that's like where you as an individual around what you want to get out of AI, the prompting should be owned by you because that's your that's your critical thinking in terms of the output that you're looking for with AI.
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The trend that I'm picking up on, this is my view, is that everybody's looking at reducing workforce because they feel that AI and AI capabilities are going to increase productivity.
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Humans should own the goal.
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Like you should have, you should own the goal of what you're trying to achieve.
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And if you put all that together, then AI is your biggest companion, right?
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Work is changing.
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That's not a prediction anymore.
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It's just Tuesday.
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And the leaders doing it well aren't the ones with all the answers.
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They're the ones asking better questions.
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I'm Dave Kenyon, and this is Evolving Workforce.
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Today we're talking about what it really takes to manage a workforce across borders and why the psychological impact of AI on people is becoming just as important as the operational challenge.
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My guest today is Tim Marley, Senior Director at TMF Group, one of the world's leading providers of compliance and administrative services across more than 80 countries.
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Tim works with organizations expanding into Asia and is the front row seat to how workforce complexity and workforce anxiety is shifting in real time.
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Tim, great to have you on Evolving Workforce.
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Thanks, Dave.
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Appreciate the introduction.
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Yeah, look, it's it's a great opportunity to talk through this.
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And from my point of view, um it'd be good to sort of talk through my experience.
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Although I'm I'm here, uh work with TMF.
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This is definitely my personal experience that we're going to be talking about today.
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So I look forward to it.
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Yeah, no, I'm looking forward to having this chat with you.
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Yeah.
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You've got an incredible amount of experience and and the you've you've worked with organizations across Asia and globally, um, uh across you know organizations like ADP and TMF.
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What are you seeing now is the biggest shift uh in when you think about workforce?
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Yeah, so there's so many elements to that question uh um to sort of answer.
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But I'll start with the biggest shift obviously is is the transformation that's happening with AI.
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Um a lot of organizations now are sort of going through that process of understanding what what do those implications mean to how we engage with our employees and most importantly how our employees manage that capability in terms of productivity.
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And then the other pieces, the client engagement piece as well, right?
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Which is how do how do we give all the right tools for our employees to to manage those types of um you know outcomes that that benefit both uh the client, but then uh you know, put us in a in an area or put organizations in in an area that they can sort of leverage you know enhanced um capabilities and and understanding what those are, right?
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Really.
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Yeah, absolutely, Tim.
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And in terms of the complexity of managing workforce, you've seen this managing across Asia, multiple countries, the complexity and the compliance is is not getting easier, it's getting harder.
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Yes um even with better technology.
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Do you want to talk us through that?
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Yeah, and I think we start with the pace of change that goes with that.
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So for example, um, you know, different countries will have different requirements and it and it's it's always changing.
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So organizations have to be aware of how they plan for it.
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Yeah.
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Um like with it with Australia, there's a lot of change happening at the moment with regards to uh super.
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Um and we so we sit down as it uh as an organization in terms of the clients that we support to get them prepared for that that change process, what the what those requirements are, what their responsibilities are, um, and ultimately mitigating risk.
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So where can it go wrong, um, how can it go wrong.
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And I think that that's applicable to every country within the Asia Pac region.
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Um another point to think about is that where resourcing and cost of resourcing and skill set of person, um, that always plays a big part.
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So where organizations might think in different regions that we might, you know, we might have capabilities that we might have to manage internally and have resourcing for it, or we can outsource it.
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Um and then so certain countries where the cost structures are different in terms of resourcing,
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that might be a different outcome.
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So it's all those types of nuances and trying to manage that through.
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So when you're when you're when you're a multi when you're a multi-country organization, um you lend a lot towards your your leaders to have that level of uh capacity and understanding.
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Um and that's a lot of trust that you have to put into how they how they see what those requirements are.
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However, you need partners, right?
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So you so that plays a big part as well.
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With my experience, it's it's the technology part, which is what what what global technologies can we implement implement into these organizations that will give us that template.
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Um, and that template will be a proven template because the solutions are built around those requirements.
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And then working with service partners uh to say, well, we've invested in these types of technologies.
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Can you help us with managing the resourcing around those technologies?
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And can you have in-country support?
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Um and then that goes with its own challenges as well, where some organizations might look at hubbing uh you know services through their through their business in different regions because of costing and productivity.
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Um however, then you have to build out those skill sets within those teams and within those shared service functions, whilst other organizations will look at working with companies that can provide local resources to manage local outcomes.
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So and then it's an industry comes into play as well, where depending on the industries that you operate in as an organization, the the regulation and the requirements that go with it uh have different types of implications, right?
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So, you know, if you sit within, say, the pharmaceutical industry vertical that has its own um you know obligations per country, um per region, um, and then you whilst if you're in business business services, you know, those those requirements might be different, but they're they're more about just being compliant in terms of the local authorities in terms of what's required to operate a business in in those regions.
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Let's just dig into a little bit about um the beauty of TMF is that you're able to expand into multiple countries quite quickly using the entities that TMF have.
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Talk to me a little bit about what what TMF does.
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Yeah, so so TMF um you know it's an amazing company in one sense that it it's it's uh it's a services company, but we it's it's drives two types of uh outcomes, right?
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Which is it looks at providing global services with local resources, right?
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So I think that's very powerful, right?
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Why is it powerful?
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Um because when an organization, so an example would be an organization looks to grow and they see Australia as a target market, they'll reach out to us and they'll ask they'll ask the baseline questions, which is, you know, how do we set up?
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How do we set up our capabilities in Australia?
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What's the best business structures that we can put in place?
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Um and we'll provide guidance around that.
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Um They'll still work with you know other other organizations that might give them advisory around what those structures should look like.
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So our job is to help guide them around the blueprint that they've been given.
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Um and what do they consistently underestimate when they're expanding into Australia or into other countries in Asia?
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Yeah, I I think the when we think about Australia, I I'd say the the regulatory and the compliance requirements, um and the investment that has to go into that and understanding that, um, and the ongoing um requirements of of those responsibilities.
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Um I think that's always uh eye-opener for them.
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And then also the complexities in terms of uh the end-to-end business model, which is not just complying and setting up the entity, but the ongoing tax and accounting requirements, making sure you get partners that understand what needs to be done at the right times.
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And then also the people piece, right?
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So Australia, again, it's it's highly regulated in terms of what you need to do to support your people.
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So when they're coming into Australia, they start to realise that there's a lot of um there's a lot of uh baseline requirements uh to operate in Australia, which in other countries might be seen to be uh you know uh not as not as um what's right, not as detailed or or or the liability doesn't sit as high as what it is in Australia in terms of requirements.
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Would you say that Australia is the most complex in terms of Asia-Pacific region?
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Yeah, I look I I would say yes from my point of view.
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We we do like with with TMF, we do do a complexity uh, you know, benchmarking index survey every year, and Australia is definitely up there in terms of the complexity of doing business in um in Australia.
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But in terms of Asia, to answer that part of the question, um again, it goes back to the country that you you you you're you're targeting
to grow in.
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Um still still can be very complex.
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Um probably the cultural piece is is in different regions, understanding the the nuances of the culture around you know w what it takes in terms of time um setting up uh I think that's the the speed of setting up an entity or setting up an business operating um you know framework within that country in terms of your goals versus what's required in that country.
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I think that's that's that's that can be overwhelming for organizations as well.
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And that's why I think with us where we've got local people, we can have that we can have that discussion straight away, right?
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Which is a practical discussion, I call it, where you when you're getting advice, you're getting you're getting ultimate um advice around what is the best case business operating model around you being successful or your organization being successful in that country.
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But what we do is probably put a practical lens around that by saying all my experience in terms of how I operate and work with my c colleagues is that when we're working with someone that's locally like myself based in that country, we can pick up on those nuances straight away to say, hey, you need X amount in terms of what you require around investment to get this up and running.
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So that's a capital play.
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Um do you have that injection?
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Are you across it?
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Um preparing for it.
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Um also, here's here's other areas of complexity that are are unique to our country that you need to consider.
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So the the main point around that is that you you you need to have local knowledge and you need organizations or partners that are that are very geared around a certain outcome.
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Um we well, the freedom for us is that we don't focus on the advisory side, we focus on the operational and the guidance and the application and getting it up and running.
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Now we're gonna talk about AI.
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Um and we've talked about this off-air before.
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There's a there's a real anxiety emerging in teams around AI, um, not just about jobs, but personal value.
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Um talk to me about that.
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How widespread is that and what's what's your thoughts around that, Tim?
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Yeah, so look, it's it's absolutely a hot topic, right?
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Like um just just today, uh part of my son's school uh school was that we had a session this morning about career pathways through AI.
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Um the reason I bring that up is that it just it's it's everywhere, right?
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So it's it's you being a parent to you being a business owner or you being part of an organization, right?
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You're constantly asking this question around AI.
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Um so I think about AI, I start with the first piece, which is from my point of view, is is what's the purpose of AI in that organization or your organization?
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It's a very good point.
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Um you can be led quite a bit by the AI extensively, and sometimes you've got to step back and say, hang on, what am I trying to achieve here?
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What do I really want when I'm when I'm uh using AI?
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Yeah.
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What outcome am I looking for?
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But also, yeah, keep that critical thinking hat on yourself.
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That's a very good point, Tim.
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Um now does this is a question that we've sort of talked about too, is does AI replace jobs or just tasks?
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What are you seeing on the ground right now?
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Um Yeah, so look at the moment I think uh everybody's looking for AI to uh I wouldn't say replace, to to r increase outcome based on improved productivity.
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Yeah.
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Okay.
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So what does that mean?
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Fundamentally, they're saying we're saying most organizations are saying how credible are we going to be in terms of our client base if we don't get the right AI capabilities put into our business for being competitive in terms of uh our output.
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So then the layers come into it, which is how can AI help us with how we operate as a business from a function standpoint?
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Um that that could go back to your operational functions around requirements.
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It could be if you're a production company or uh you sit within industry, then what does that mean in terms of what can AI do to drive efficiencies in the process?
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And then the other piece is the people the people, right?
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Is how do we get the most out of our people?
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Um, how do we engage with our people proactively, but fundamentally how to give them the tools so they they're more productive?
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Tim, do you find um in in businesses that uh the ones that you're talking to, also TMF, that most people now are like actively engaging, or is there still some people who are not using AI?
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Again, my opinion is I think every most most organizations are.
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And I remember those same synergies of the world's gonna end and you know So I feel it's it's
there's some tipping points that are very similar to that.
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And um so I think all organizations have gone in um and said, look, we need to be across this because we don't want to miss out.
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And they shouldn't, like, because I think it's such a great tool and it's a great capability for all of us.
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Um however, I think where where the challenge is now, it's what based on some of the some of the productivity that's being like, you know, efficiencies that have been gained through areas of business, um uh can what else can we do and what else can we do with it?
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Um and then the cost of that.
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I think that's starting to un that that uh it's being uh it was underestimated.
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It was uh it was, well, hey, we can do all this, um, but now it's it's what what's the cost of it?
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Um I'm sure these org all these organizations that have this capability and provide these capabilities to to other companies.
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The they've they've got a commercial model, a pricing model that goes with it as well.
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And then where's that going, right?
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And is and then and then the the other piece is maintaining these databases and the infrastructure.
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Again, I'm not an expert around it, but what I hear and what I read about it is that that's that's starting to become a concern, which is a concern of how do we manage that um, you know, in country, which countries can manage it, who's got the capacity to manage it, um, you know, what does that mean in terms of driving that investment into our countries?
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Uh what's the obligations that we have?
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So all those deep questions are being asked right now.
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And I think that it has a a downstream effect on all of us, with with some organizations will start to weigh up when that's that tipping point of cost start to hit.
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Yes.
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Do we need people versus what level of AI do we need?
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I think that's what type of efficiencies do we need and what level are we willing to stop at based on just having an open door to saying we'll just keep doing it and see where it lands.
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Again, that's my opinion, but I think that's what I'm seeing.
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You you brought up before at each level a major revolution of technology, you know, people have said, you know, the the sky's falling in and the world's gonna end.
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Um, you know, obviously this this happened in the industrial revolution, um, the advent of cars, the the uh the advent of the personal computer, yeah, yeah, the uh the internet, uh, and now is our next big one.
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And at each point people say, oh well, we're gonna all lose our jobs, you know.
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Sure.
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They thought the same thing with the advent of the personal computer in the early late 70s, early 80s.
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Um I think you know that's a great point that you brought up because it's just about how we work it out.
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There's there's anxiety, but I think we we're moving beyond that now to work out how it can augment um how we work.
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Yeah, and I I mean and that's such a such a critical point too, because I think it's uh it's such a positive right.
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It's not it's not a and I'm a glass half full type of person, but I still think I sit there and I think this is us evolving.
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Like this is this is a good thing.
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Um however, like with any tool or any type of movement forward, like you know, like you said, like if you go back 150 years, 100 years, it was the development of a a car, right?
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So and what impacts that it had on the horse and carriage, right?
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And and so it's a bit like that.
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Um where it's a little bit different, it's in my mind, it's it's it's not as physical.
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So typically when you see like the you see the you know, industrial revolution or all those types of things that are sort of occurred in history, you you seem it to be it seems to be more physical, right?
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And I think with this it's it's sitting through the same ways that we t typically have been operating through, like you said, computers and and the internet, but it's giving this new capability around um around thinking.
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And and you know, we talked about at the start, which is that whole piece around the critical thinking component.
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And I think where the edge is at the moment in terms of generations, right?
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Because I I was literally thinking about this as well, where where I'm sort of in my where am I in my career, probably I'd say I'm bit I'm halfway through it, a bit not more, if not more, right?
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However, I've I've lived a lot in in my little lifespan in terms of my career where I started, you know, where internet was becoming a thing, e-commerce was becoming a thing, um, and then how we engaged changed in terms of the internet, and then and then the evolution of terms of the iPhone, all that type of stuff, in terms of how we engage for apps.
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And so I've seen, I've seen personally, I've I've seen all the manual to all the automation that's happening at the moment, and I can sit there and I can still reflect and say, well, if this
situation is this, maybe we can think about this and then get this type of outcome.
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Because we're still in the workforce, but with the new generation coming in and you know, the generation changing in terms of the the, if you look at the demographics in terms of maturity and age, there's a lot of lot of skills are gonna be moving out of the workforce.
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So going back to the workforce piece, I think AI will will do two things, right?
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It will help with the movement of that age population out of the workforce.
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And how it will do that is giving more pro more capacity, more capability per person in terms of AI and the capability of AI.
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However, it's it's where I'm sort of got a question mark around it personally, and uh is like what does that mean from a critical thinking piece, right?
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Because we've got natural experience, because we're in the workforce what what's post and pre.
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So where is it going to be in the next 10 to 15 years?
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Like that would be interesting.
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Like I don't and we'll probably get to that, but that's something that I I'm interested in the most just for myself, just seeing that change process.
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I'm interested in that too, because yes, if I had grown up um, you know, even in school, um using using AI to write my essays and I just sort of correct it, um, even forming sentences, all that sort of stuff, you know, how's that going to be incorporated if I'm a s uh a ch a child right now?
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Um and who knows, maybe maybe your kids won't be won't be working.
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Who knows?
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Um but I suspect they will.
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Yeah, look, I I think w what w working I think working in the way we work, yes, it'll be different.
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But working's still gonna be i it's it's it's who we are.
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It's like it's what you choose to do in your life, right?
00:22:14.319 --> 00:22:16.240
So that's not g I think that's only gonna evolve.
00:22:16.400 --> 00:22:23.279
You're gonna so whatever your career is and whatever you have passion for, and it goes back to what I was saying before, which is I think the purpose piece.
00:22:23.440 --> 00:22:28.319
I think AI is if you if you know your purpose, AI will help you with your purpose.
00:22:28.559 --> 00:22:31.200
But I think career and purpose are still gonna be interlocked.
00:22:31.279 --> 00:22:31.359
Yeah.
00:22:31.599 --> 00:22:34.799
But the way that we work, and if you think about it, I don't think it's new.
00:22:34.880 --> 00:22:36.079
Like again, this is my opinion.
00:22:36.160 --> 00:22:43.680
Like if you think about work, work was completely the synergy you say certain roles would have the same type of outputs 100 years ago.
00:22:43.920 --> 00:22:49.519
Um however, there's a lot of roles that don't exist that will that were mainstream roles and career paths.
00:22:50.000 --> 00:22:51.599
So that's what AI is going to do.
00:22:51.759 --> 00:23:01.279
I I think, again, I'm my opinion is that it's only going to help us be more strategic around outcome.
00:23:01.759 --> 00:23:03.200
That that's how I see it too, right?
00:23:03.359 --> 00:23:12.799
It's not we're still like the organics of of you know consciousness and all that, if you go deep into that, at the end of the day, it's not that.
00:23:12.960 --> 00:23:17.519
It's it's it's a it's a tool that that understands the data.
00:23:17.759 --> 00:23:34.000
So it's got a database that it works off and it and it subsequently has the capability of of giving s some great outputs for you as a as a user to utilize to get a best out that to get a better outcome, right?
00:23:34.240 --> 00:23:38.880
So I still think work will still be work, but it won't be how we see it.
00:23:38.960 --> 00:23:44.240
But I think the careers and the res responsibility of what you want to do might might deviate.
00:23:44.400 --> 00:23:58.240
And and again, going back to the conversation I had with my I was listening to this morning and having a conversation with my son about it, like he he loves, he's he's he's always loved uh programming since he was a kid, and he's he's a teenager now.
00:23:58.400 --> 00:24:01.920
And so our if you go back five, six years ago, I just thought that's what he's gonna do.
00:24:02.000 --> 00:24:05.359
He's gonna be a software engineer, he's gonna definitely go into that career path.
00:24:05.680 --> 00:24:12.319
However, he's now, he still wants to do that, but he wants to be, he's a great problem solver.
00:24:12.799 --> 00:24:18.400
So my thinking is with him, and we spoke about it, which is that's the evolution of work.
00:24:18.559 --> 00:24:34.079
The work's gonna be, you have to be a great problem solver, have critical thinking across a whole range of technical skills and requirements to to be functional in the work environment in the future, right?
00:24:34.400 --> 00:24:35.279
That makes so much sense.
00:24:36.000 --> 00:24:53.759
You know, I um I talked to my my my niece and my nephews about, you know, your generation is gonna be ones that actually the ones that do really well, the ones that have the human elements that are great communicators, that's highest high empathy, and yes, great problem solvers.
00:24:54.240 --> 00:24:59.920
Because those elements are gonna be absolutely even more important in the future, I believe.
00:25:00.240 --> 00:25:12.880
Yeah, and where I got passion around that is that when we think about, like if you think about your day job, most people, the administration part, it it's you har it's hard to get motivation around it.
00:25:13.039 --> 00:25:17.440
So you you're constantly saying, well, this is a this
is the baseline administration that I have to do in this role.
00:25:17.519 --> 00:25:17.759
Yeah.
00:25:18.079 --> 00:25:19.920
I have to achieve it and I have to do it.
00:25:20.160 --> 00:25:22.240
So AI is going to definitely help with that.
00:25:22.400 --> 00:25:27.519
So it puts you in a position where you can be strategic around what you want out of your role, right?
00:25:27.839 --> 00:25:44.720
So, and that's where I think no one, we're not we're not moving our lens to we've still got this, we've still got our mind, we've still got our thinking process, we've still got our imagination, we've still got our uh our critical um, you know, capacity to sort of say, what else can I do?
00:25:44.880 --> 00:25:46.240
And how else can we do it?
00:25:46.400 --> 00:25:47.759
Because that's where we all want to be, right?
00:25:47.839 --> 00:25:55.920
Like if you like I said, if you go to the average person, they'll say, uh, admin keeps me bogged down, or this keeps and and I've been there and I do it today, I still say it.
00:25:56.079 --> 00:26:08.160
But then I think to myself, how do I I can't wait till this is automated so then I can start thinking about what I want to do again with my career and the passion of what what I'm meant to deliver in that job.
00:26:08.480 --> 00:26:09.359
So yeah, yeah.
00:26:09.519 --> 00:26:10.400
So I think that's key.
00:26:10.480 --> 00:26:10.799
That's key.
00:26:10.880 --> 00:26:12.640
That's why I think AI is amazing in that sense.
00:26:12.720 --> 00:26:12.880
Yeah.
00:26:13.119 --> 00:26:16.240
Tim, we uh on Evolving Workforce, we like to play a few games.
00:26:16.319 --> 00:26:16.559
Yep.
00:26:16.720 --> 00:26:20.960
And the first one's called Three Quick Games Before We Finish, Humans versus AI.
00:26:21.200 --> 00:26:34.640
And so, in your view, what what should humans own outright in a workforce can context, workforce control, if you like, and what should we be comfortable in AI handling, like the administration tasks that you were talking about?
00:26:34.960 --> 00:26:37.440
Yeah, look, I think humans should own purpose.
00:26:38.160 --> 00:26:38.480
Right?
00:26:38.640 --> 00:26:40.880
I think that's we shouldn't let go of that, right?
00:26:41.279 --> 00:26:48.480
And that's intertwined with what I'm saying with regards to what I'm seeing, which is you know, what are you gonna ask the AI?
00:26:48.559 --> 00:26:49.359
That that's you.
00:26:49.599 --> 00:26:57.440
You should know what you want to ask the AI and and have a have a purpose of what that what the outcome you're looking for.
00:26:57.599 --> 00:26:59.119
So I think purpose is key.
00:26:59.279 --> 00:27:01.119
And then what goes with that is intent.
00:27:01.599 --> 00:27:08.400
You have to own the intent as humans compared to the AI owning your intent, right?
00:27:08.559 --> 00:27:13.119
Which is you don't need to outsource your intent to AI to say, what should I do?
00:27:13.279 --> 00:27:22.240
It it should be here's what I'm thinking, purpose, this is what I want to, how I want to do it, what are your suggestions in terms of how I can achieve that?
00:27:22.480 --> 00:27:23.839
And that goes to the last point.
00:27:24.079 --> 00:27:25.039
Humans should own the goal.
00:27:25.119 --> 00:27:29.599
Like you should have, you should own the goal of what you're trying to achieve.
00:27:29.759 --> 00:27:34.319
And if you put all that together, then AI is your biggest companion, right?
00:27:34.559 --> 00:27:50.880
Uh in terms of AI, I would say where AI's got uh great capity or potential is that it can do things at a rapid speed that you can dream of doing as a human, right?
00:27:51.039 --> 00:28:03.920
So what I mean by that is it could be the calculations, it could be uh analysis, it could be review of the data that it's got access to.
00:28:04.240 --> 00:28:11.839
And those that piece there, I think, should be even, you know, I can't wait to see what it does, right?
00:28:11.920 --> 00:28:14.880
Because because then that's gonna you're gonna achieve so many goals with that, right?
00:28:14.960 --> 00:28:34.720
So you're starting to hear those stories now, right, which is we've got, you know, from from the sort of the again, I'm just this is my reading and my opinion around it, like if you look at the healthcare side, which like you you have all these we have all these diseases and and you know, there's a lot of there's a lot of smart humans that are involved in that.
00:28:34.880 --> 00:28:53.519
But how about if if you like I said, augment AI into those types of roles, where we're gonna go as a society, where we're gonna take it, which I think for this generation and the new generation is my son and my daughter and and the new generation's gonna come, it's gonna be amazing outputs over the next, who knows, over the next 10 to 15 or 20 years.
00:28:53.920 --> 00:28:54.799
So exciting to see where it is.
00:28:54.960 --> 00:28:59.119
So I think that's where AI I think it's yeah is an amazing tool in that sense.
00:28:59.200 --> 00:29:00.480
That's the AI's role.
00:29:00.640 --> 00:29:16.880
But I I still think at the end of the day, AI can't be it can give guidance, like but going back to TMF, w advisory, that's it's it's it's you need to build it out with the right people that you can get access to, or humans.
00:29:17.119 --> 00:29:20.240
And then I think AI is is a guidance tool.
00:29:20.400 --> 00:29:24.799
AI can be something that can help facilitate those outcomes.
00:29:25.119 --> 00:29:25.519
Perfect.
00:29:25.680 --> 00:29:26.079
Love it.
00:29:26.240 --> 00:29:27.839
Um I totally agree with you.
00:29:27.920 --> 00:29:33.119
That's makes makes a lot of sense, Tim, and it brings me to the next game, which is change your mind.
00:29:33.200 --> 00:29:41.279
What's something that you would have believed about AI's impact on workforce maybe two, three years ago, that you completely changed your mind on?
00:29:41.839 --> 00:29:59.119
Yeah, look, I I just my
thinking about AI was um it it it was evolving to be a substitute for um certain outcomes, right?
00:29:59.200 --> 00:30:16.640
Now, for example, um say if you've got an organization that wants to run a balance sheet or an accounting or whatever it may be, and AI can do a lot of that work in terms of getting those outcomes, I'm sure.
00:30:16.880 --> 00:30:25.680
However, there's still gonna be components that have to be led by human engagement and and expertise in that field, right?
00:30:25.839 --> 00:30:28.720
So what I thought was it was just gonna c and maybe it will, right?
00:30:28.799 --> 00:30:47.200
But I'm just my view at the moment is there's definitely areas of tipping points that the capacity questions getting answered that, you know, like I said to you, costs, resources, environmental impacts, capacity of of having this this infrastructure in place, which countries we'll we'll probably get through that.
00:30:47.359 --> 00:30:50.880
But I think at the moment, I think I just thought it was endless.
00:30:51.039 --> 00:30:59.039
But now I'm just thinking it's everybody's starting to understand just now they're starting to understand like what what does that really mean?
00:30:59.200 --> 00:31:11.680
Um and what are the impacts around my organization, my client base, my employees, you know, and and the comp and the countries that I'm operating in.
00:31:12.240 --> 00:31:15.440
Now, the next one is uh predict one prediction and one warning.
00:31:15.519 --> 00:31:24.640
What's one prediction you make about AI um and in the workforce across Asia and APAC region over the next two two years or so?
00:31:25.759 --> 00:31:47.839
Yeah, so look, I again is just my prediction is um it's gonna it's gonna become more of a a companion capacity compared to a uh sort of a substitute.
00:31:48.000 --> 00:32:02.720
And then also um at the moment you'd think it's sort of a subservient type of disc it's it's put the put in what I want and give me what you I think it's the relationship's only gonna better, uh it blend better in terms of usage.
00:32:02.960 --> 00:32:08.880
Um so I think everybody's starting every day you're getting better and better and saying what do I want out of my AI tool?
00:32:09.039 --> 00:32:11.519
Or whatever from a workforce management standpoint.
00:32:11.680 --> 00:32:19.039
So for example, uh from a workforce management perspective, I think it's gonna help with I'll give you a couple of examples actually.
00:32:20.240 --> 00:32:34.960
Thinking about how you engage with employees, what we're noticing, what I what I've noticed is that employees are are really trying uh understanding who and what their policies are around the internal organization, right?
00:32:35.119 --> 00:32:42.000
So an organization will have set policies that they put in place, and those documents are at times are quite heavy.
00:32:42.240 --> 00:32:48.960
So an individual would have to go through a lot of personal review, right?
00:32:49.599 --> 00:32:56.480
So I think that AI is gonna help a lot of employees to say, what does this document really mean for you?
00:32:56.720 --> 00:33:12.559
All right, and then and that that's a new place for everyone because it's gonna give capacity very quickly to employees to understand what are the responsibilities of my organization and and my role in the organization.
00:33:12.880 --> 00:33:23.599
And that's it's that's in country, that's my leadership, what's what's the obligations of my leadership to my role and and what it may be.
00:33:23.839 --> 00:33:26.480
And it's gonna be it's gonna be a lot of change.
00:33:26.559 --> 00:33:37.920
Like I think there's gonna be uh so my my passion around this is uh is that I think peep payroll teams, HR, uh are gonna become even more critical.
00:33:38.000 --> 00:33:56.960
And workforce management, all these tools and all these software, and all the people that manage these systems, it's gonna be massively critical because everyone was gonna start to use AI and have a different type of working engagement relationship with employer-employee type of uh situations, right?
00:33:57.119 --> 00:34:27.760
And they could be from right from career development, um, career progression, skills, skill development to performance management, you know, grievance, all those areas are gonna definitely have a high emphasis, and AI is gonna give the capacity to to the employee to ask those types of questions, where in the past it's an investment for that employee to get that access to that to that information that makes sense to their situation, right?
00:34:27.920 --> 00:34:46.320
So meaning they'd have to go and speak to someone of that skill set for them to review it to get that outcome like you know, w whatever if they have access to associations or to lawyers or to um, you know, whatever it may be in terms of that support, I think now they're getting there still.
00:34:46.480 --> 00:34:47.840
So I think there's gonna be a huge change.
00:34:48.000 --> 00:34:53.599
I think that employee relationship is not an employer relationship, it's gonna evolve.
00:34:53.840 --> 00:35:01.920
And those policies, workforce management policies, HR, all those types of policies are gonna be critical.
00:35:02.079 --> 00:35:05.760
They're not gonna be just, you know, black and white.
00:35:06.559 --> 00:35:10.159
They're gonna have to evolve and they're gonna have yeah, and they're gonna have to really be powerful.
00:35:10.400 --> 00:35:12.559
But I think there's a huge opportunity both ways.
00:35:12.639 --> 00:35:34.079
I I I don't think it's it's gonna have its challenges and it's gonna cause disruption and there's gonna it's gonna cause you know friction if at times, but I think the positive is it's gonna it's gonna cut cut out a lot of ambig ambiguity in terms of what do we need to do to help our employee and employee, employee, what are my responsibilities to help the organization?
00:35:34.320 --> 00:35:36.079
So that that's my
that's my big thing.
00:35:36.159 --> 00:35:38.719
I think that's where it's gonna be exciting in terms of where it's gonna go.
00:35:39.039 --> 00:35:40.719
And Tim, one warning.
00:35:40.880 --> 00:35:53.360
So, in terms of thinking about organizations and workforce expanding into APAC, what what are we um likely to get wrong or if we don't watch out for compliance or whatever it might be?
00:35:53.679 --> 00:35:56.400
Yeah, uh I think AI is not governance.
00:35:56.880 --> 00:36:00.159
So, and that's something that everybody needs to consider.
00:36:00.800 --> 00:36:03.039
And what does that mean again?
00:36:03.280 --> 00:36:06.719
It means AI will give guidance.
00:36:07.440 --> 00:36:16.400
Um at to be fair, at times you have to still challenge the guidance because you have to make sure that the sources are right in terms of the output.
00:36:16.639 --> 00:36:23.599
It's it's not it can give you really good guidance and it can give you a high percentage range of what that looks like.
00:36:23.840 --> 00:36:26.079
However, it's not governance.
00:36:26.480 --> 00:36:32.559
So I think that's you can't outsource governance and policy.
00:36:32.800 --> 00:36:36.880
That's that has with with the employees and workforce management, like what I said before.
00:36:37.039 --> 00:36:42.320
So I think that's something that it's gonna become very critical.
00:36:42.880 --> 00:36:59.280
And as leaders or uh you you have to understand you can get all the tools in the world, but if you haven't got the right governance and you haven't got the right inf right structures in terms of what's required, um the liability is not gonna disappear with AI.
00:36:59.679 --> 00:37:03.599
Tim, thank you so much for joining us on Evolving Workforce.
00:37:03.760 --> 00:37:06.400
Um, I think this has been an amazing chat.
00:37:06.559 --> 00:37:10.159
Um you're absolutely right.
00:37:10.320 --> 00:37:17.679
In terms of uh keeping that human in a loop, that's something we talk about uh quite a bit here on Evolving Workforce.
00:37:17.840 --> 00:37:20.239
Um yeah, we really appreciate your time.
00:37:20.400 --> 00:37:28.639
Is there anything that you wanted to cover that we didn't cover that leaders should should be thinking about in terms of AI, workforce, Asia expansion?
00:37:29.760 --> 00:37:34.480
Yeah, look, I just think it's it's a huge opportunity.
00:37:34.719 --> 00:37:51.679
Um and it's the best opportunity you you've you've got to engage with the employees and have mutual outcomes that benefit both your clients and the performance of your company.
00:37:51.840 --> 00:37:54.159
I don't think there's ever been a bigger opportunity than this.
00:37:54.400 --> 00:38:06.960
So I think all the all the you know the the end of the world type of vision around AI, I I don't I just don't I personally don't think that's what it is.
00:38:07.199 --> 00:38:10.559
I think it's a huge opportunity and and you've got to treat it that way.
00:38:10.960 --> 00:38:11.199
Yep.
00:38:11.599 --> 00:38:13.760
Thanks so much for coming on Evolve in Workforce, Tim.
00:38:13.920 --> 00:38:14.159
Thank you.
00:38:14.239 --> 00:38:15.199
Cheers, appreciate it.
00:38:15.519 --> 00:38:15.840
Bye.
00:38:38.719 --> 00:38:40.480
Delivering new certainty.
00:38:40.719 --> 00:38:43.679
This podcast was recorded on the land of the Gadigal people.
00:38:43.920 --> 00:38:47.760
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00:38:55.920 --> 00:38:56.800
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00:38:56.880 --> 00:39:00.480
I've been Dave Kenyon, and this is Evolving Workforce.