Jason Schultz (00:00):
There is innovation fatigue, there's AI fatigue, there's transformation fatigue, creates anxiety, quite frankly. And again, that's why you have to remain focused. I always like to say deep breaths and baby steps. And the idea is that sometimes slow is smooth and smooth is fast because you can get bogged down with taking on too much.
Will Ayers (00:19):
Behind every great law firm are bold leaders and powerful solutions that help them run a better business. Welcome to Studio A, the home of legal tech innovation. Welcome to Studio A, powered by Aderant, your podcast for the latest conversations shaping legal tech. I'm Will Ayers. The legal industry has moved beyond incremental change. AI is definitely accelerating and also increasing expectations as well. Clients are demanding precision and return on their ROI and operational discipline is now a competitive advantage. Today, I'm joined by the talented innovator himself, Jason Schultz. He's the CIO at Michael Best and Friedrich. The AmLaw 200 firm has more than 400 legal professionals and serves clients around the globe. In addition to that, they are known as one of the most innovative firms in the legal industry. So on this episode, we will explore what leadership looks like when transformation is expected and it's not optional.
(01:28):
And what separates law firms that are experimenting with technology from those that institutionalize it? Jason, thanks for finally, finally joining us on Studio A. How are you doing today?
Jason Schultz (01:42):
I'm doing well. Appreciate you having me and glad we were able to finally get these dots to connect. I know there's some scheduling hurdles, but big fan of the show, big fan of everything the A team's up to and happy to be here and be a part of this discussion, so appreciate it.
Will Ayers (01:56):
Thank you. Thank you. And we are a big fan of you as well. That's why you are on studio. A, so before we get started, tell us a little bit more about your role at Michael Best and some of the key things that you are responsible for at your law firm.
Jason Schultz (02:11):
Yeah, appreciate that. So per your intro, I'm leading innovation and technology at Michael Best. Kind of a cool story with the firm. We're 177 years old now and really have grown the firm, both from a talent perspective, from a capability perspective, but also just geographically. We now are spread across 20 offices in nine states and we're doing some pretty innovative things. In addition to our primary business, which is our law firm, we also have another non-legal consulting entity called Michael Best Strategies, where we do some consulting, government relations. We also do some public affairs work, kind of that intersection between business and government. And so in my role, I get to oversee various areas of technology, security and innovation across those entities. I would say in my role day-to-day, it's kind of three areas of focus. The first being everything we're doing from a cybersecurity and data privacy perspective.
(03:02):
So how do we enhance our security programs? How do we harden the environment? And how do we make sure that we can instill continued trust and confidence in the programs we put together? The second area would be IT operations and infrastructure. So everything from our network to our enterprise application stack, to custom app dev, to how we support all those capabilities with inside the organization. And then the third area, I think, which is where this conversation will be more focused is around innovation, process improvement, change management. How do we do things better, faster? How do we improve efficiencies? How do we reduce administrative burden? How do we drive our practitioners up the value chain, drive the cost down and all the while providing an amazing client experience for those that we serve?
Will Ayers (03:46):
Now you mentioned doing better things faster, and I think that's a great segue to our questions. Let's dive into leadership during this moment of rapid acceleration across the legal industry. The legal industry is moving from incremental change to structural change. What does leadership look like when transformation is no longer optional, but expected by clients, attorneys, and the market in general?
Jason Schultz (04:13):
Yeah, great question. Well, as you stated, the industry's certainly going through a seismic shift, if you will. And I do believe that's being driven by a variety of factors. One, technological advancements. There's a lot of cool emerging tech, AI, obviously being at the forefront of that conversation. Client demands are changing and shifting. The competitive landscape is shifting. There's more alternative legal service providers out there, more folks that are doing pieces of the overall puzzle. The talent dynamics are more competitive than ever, and then just the overall market pressures that we're facing in and outside the industry. And so it's not really optional. To your point, I think the question is structured very well. It's a must. Leadership must evolve beyond the status quo. And so how do you go about doing that? Well, I find the conversation around AI to be a fascinating one. As you know, it's not a new concept.
(05:03):
This technology's been around in various forms and we've been using it in narrow ways for many years. Although I do think the stage has been set as it relates to what GenAI is doing and some of the new capabilities that have been developed as a result of that. And that's just a matter of timing. The computing power, having sufficient training data, all of that to be able to demonstrate these capabilities at scale is now readily available. And I feel that data proliferation is kind of fueling the boom. And so here we are. It's disrupt or be disrupted. A few years back, I was trying to pull some folks along and now they're kind of pulling me along a little bit. It's hard to keep up with everything that's going on. I do think though that AI will expose leaders who are thinking like machines. And if you think about certain areas of the work that we do as knowledge workers, there's some of it that is formulaic or you could program it.
(05:55):
It's database, rules-based, task-based. So there's an element of that that the machines can do very well. And so again, I think AI is going to expose the leaders that are tethered to that old way of thinking. I think the future is going to belong to leaders that are architecting what is possible, the art of what is possible. I also think that because AI is moving so quickly, it's exciting. It can augment or amplify a lot of what we do, but that means it can amplify both your capabilities and also your dysfunction. So if your processes are broken, AI will help you fail faster. If your strategy's unclear, AI will optimize toward the wrong goals more efficiently. So I think we're kind of at this threshold of a new leadership era, one where AI is going to expose the limits of that legacy thinking. Folks that are, again, are looking in the rear view mirror and set out the windshield.
(06:45):
And it's going to be a first stop for any leader that is able to say, "Hey, I need to be more self-aware." And there's opportunities here, like asking the right questions. Are we using AI to improve the past or to invent the future? Do we deploy AI to shrink the workforce and automate yesterday's work? Are we trying to go up out in a different way? Are we trying to augment human potential? Are we trying to pursue different outcomes? Are we trying to invent an entirely new business model? That to me, those are the exciting conversations that I could be a part of. And again, I think it requires people to really have to reimagine. There's a quote I like by, don't hold me to this, but I believe the author is H. Nelson Jackson. And the quote is, "You can't do today's job with yesterday's methods and be in business tomorrow." And that's kind of where we're at.
(07:33):
That's where the conversation's at. So again, it's easy to stay in the past, but I don't think we have a choice. I think it's here and that's going to require a new form of leadership and a lot of things have to happen to get there. Unlearning, embracing the disruption, being in the game, and just accepting the fact that we're all experts in the making. I think there's a lot of folks on the sideline right now because they don't know what they don't know as opposed to being curious, creative, leaning into the learning, failing forward, which is where I like to play.
Will Ayers (08:02):
Now, there's a difference between adopting tools and building capacity or capability. At Michael Best, how do you ensure innovation? Because things are moving very fast at the moment in the era that we're in.
Jason Schultz (08:17):
Yeah, I think that's a good question. So adopting tools, typically when I think about adopting tools, that approach is focusing on acquiring and using ready-made off-the-shelf solutions. There's a lot of SaaS products out there subscribe to them, or you're implementing vendor-provided technology has minimal configuration or customization. So when I'm adopting a tool, it's like speed. They're quick to deploy. There's typically lower upfront risk or cost. There might be less internal effort to actually get it out there into the ecosystem. The integration complexity might not be there. Even the adoption challenges themselves might be fewer and far between. And so I think about that when I think about adoptive tools, and certainly have a lot of tools in our toolkit. So we are adopting tools. But when I think about building capability, that to me is more part of a longer term strategy. Maybe there's a roadmap involved where you're really looking at maybe more disruptive innovation versus more incremental innovation.
(09:13):
Slower to start, there's going to be an investment in people. You might have to hire people, you might not have the skills on the current bench. You might have to re-engineer or develop a process. There might be infrastructure pieces that you need in place. So it's like a slower start that maybe has more experimentation iteration. Oftentimes when I think about building capability, there's also controls that need to be in place. If you think about it from a compliance perspective, having the right governance models in place. Integrations. When you're doing these big investing in big platforms or making big shifts in how you're approaching your technology stack, you have to think about larger integrations, you have to think about long-term ownership. So it's not just the initial release, but how do you continue to enhance it, make it better, optimize it? And then ultimately, I think the outcomes are different.
(10:01):
How you measure those outcomes is different than ... We turn on tools all the time because it's a cost of doing business. Whereas if we're trying to do something more disruptive, we very much are looking at the outcome and how we're managing and measuring the return on those larger investments. I think the second part of your question though is how do you ensure innovation? And it's easy to chase shiny objects. I certainly think there's a lot of hype right now within AI, but for me, innovation requires a strategy regardless of what the innovation is. And I always have defined innovation as applying novel solutions to meaningful problems in order to create value. So if you just look at it, people think when they deploy technology, they're innovating. Or I love when people say innovation's the light bulb. It's the idea. It's not the idea. And it's often not just the technology.
(10:49):
Technology itself solves nothing. It requires people and process of change. It requires the behavior surrounding the technology to determine if adoption is successful or not. And I think that's what's going on right now, certainly in the legal industry, is that we're at this innovation theorist call it the chasm. It's a point where the initial enthusiasm from a small group of early adopters, which all organizations have, they put their hands up, they're the innovators. But that enthusiasm from the small group of early adopters, it fails to translate to the organization, to the early majority. And the reason often is because of behavioral change. How do you get people to change the way they work? How do you make sure that they're not reverting back to the old methods? And that is a different approach. And again, we've gone at it since I've arrived five years ago, it's been a very consistent approach as it relates to how we innovate.
(11:39):
And so when AI became the hot topic of conversation, it wasn't like, well, how are we going to use our adopt AI? It was, while we have an innovation program, we have a strategy. Let's follow that. Let's make sure that the right ideas are the ones that are moving forward and we're not just chasing our tail, which again, you can certainly do in this environment. It's moving very, very quickly. So I think we have a different approach. It's a strategy that has a multi-year roadmap. It's tethered to our firm's strategic plan. We intake ideas from across the organization through an innovation pipeline. We use design thinking and brainstorming sessions to make sure, hey, we got a cool idea or maybe two that we want to stitch together, but are they the right idea? Is that the right problem? What's the business value? What's the cost?
(12:23):
What's the feasibility of even doing it? And once you get through those conversations, then we can start to develop a business case. And the business case has to be sound because you're going to come back to it as you get further along on your journey. We get those business cases. We have a lot of conversation within our innovation council, which again is a cross-section of the firm. And then ultimately we fund our strategic program portfolio very much like an entrepreneur would seek funding from a venture capitalist. It's a portfolio that stands on its own separate from just the core IT operating budget. And once we fund it and activate it, it's all about monitoring progress, reporting on success and failures and tracking the outcome. And then just again, iterations. The whole idea, I'm a big believer that done is better than perfect. And so sometimes you just got to get things going.
(13:11):
You got to get the feedback loop going and then you can make changes from there.
Will Ayers (13:14):
Now you talked about strategy. Let's lean into that a little bit more. As AI accelerates, how do you balance urgency with operational discipline, especially in areas like financial systems and client data where precision really, really matters?
Jason Schultz (13:30):
Well, it's very hard to do. So like I mentioned earlier, Will, I think we are still dealing with the hype cycle. I think there's a lot of noise in legal tech right now, and it's very, very challenging, I think, to find the winners. The other challenge is I don't think the hype necessarily matches the reality with regards to the effort it takes to be successful. So if I look at just how the legal tech ecosystem has grown, the amount of outside software companies that we have to try to evaluate and ultimately manage, it's skyrocketed. And so the complexity of the technology procurement process, trying to support all these various technologies and applications, trying to architect data integrations, and then all the while providing a seamless user experience, it's more challenging than ever. So one of the things that we do to make sure that we're making the right decisions is you got to start with the three whys, which is again, going back to our innovation strategy and how we approach identifying problems.
(14:27):
The three whys are, why should we do anything? Why should we do it now? And why should we do what's being proposed or recommended? And once we get through that, like I said, you got a business case, but even once you get there, you still have to look at the overall structure of the organization, like people. Is your team prepared? Do they have the capabilities necessary to make the transformation successful? Because again, a lot of things we're talking about with AI, it's not about the technological capability, it's about human adaptability. And so you need to make sure that the people piece is in a good place. The power of these tools is only good as the people that wield it or don't wield it. So the cultural aspects, cultural adoption, the change management, which you mentioned earlier, that's a big piece that ensures that you get trust upfront, you get buy-in and then you can sustain that momentum.
(15:12):
Also, the process. Are you identifying the right problems? You can't throw AI at everything, which I've heard suggested in a lot of peer groups that I'm in and some events that I've attended. You cannot automate an ad process. You got to redesign it. So sometimes you have to start there. What is the process? Do we have a process? Do we have a process that's documented and understood? Is it being applied the same, whether it's the right process or not? Let's start with the fact that we have a consistent process that everyone understands. From there, you can look for opportunities to augment or amplify. And then the technology piece is very important too because you don't always need to go and buy something new. Sometimes you already may have that capability in your portfolio. And if you do, you should really look at the incumbent technology.
(15:52):
Is that provider releasing new functionality? Are you tied to their roadmap? Do you know where they're going? Because sometimes it might just be waiting a little bit, as opposed to going and buying something new and adding it on. And the other piece to everything that we're doing too, which I think Adderall is a way out in front on, which I'm a big supporter of is the fundamentals. One of the biggest challenges a lot of firms are facing today, it's not a lack of data. It's a lack of usable, weld-structured information that can truly drive these outcomes. And so you can spend a lot of time, like I said, putting these very powerful tools on top of a bad foundation only to have to rebuild the foundation.
Will Ayers (16:28):
Now you mentioned people as a key part of that innovation strategy and Michael Best and Aderant are partners. I won't say you guys are our client. I will say you are a partner. And I've spoken to legal professionals and leaders at Michael Best before. And before modernizing your work to cast cycle, your team described black holes and visibility. Beyond lost time, what does that kind of opacity cost a firm strategically?
Jason Schultz (16:59):
Well, we've had a lot of discussions with other members of the Aderant team, and I've always walked away kind of feeling energized and inspired in some way. At the end of the day, we're in the practice of delivering value legal services to our clients. And so the people, the processes, the technology that we use to manage our revenue cycle, it's the backbone of the firm's business. So any improvements that we can make in this area, again, whether it's reducing administrative burden, improving efficiencies, removing areas of friction, all of that allows us to not only capture the work, but bill our clients and ultimately collect on those dollars, which again is the whole idea of work to cash, which I think your slogan's way better than what I said. So it's the whole idea of how do you optimize the work to cash? And we're looking at this because there's always opportunities for improvement.
(17:50):
You're never done. Now, sometimes the juice isn't worth the squeeze, but again, you can always identify opportunities for improvement because everything around us is changing. So we recognize a lot of inefficiencies, whether it was in timekeeping, billing, compliance with OCGs, all of it slowed down that work to cash cycle. And so some of the, I guess, pain points, if you will, we're like, we're recording time, but the bills weren't generated the right way, or there's manual handoffs in the workflow, or you'd get something pushed through only to find out that it was flagged because there was compliance issues. The lack of that centralized visibility adds time. And we are in an industry where time matters. It matters everywhere, but it certainly matters in the legal industry. I mean, our practitioners, we refer to them as timekeepers. And so when you have limited visibility or if you have multiple systems or processes that have to be run a certain way, there's a lot of room, a lot of variables, a lot of room for error.
(18:47):
And so when you have limited visibility, I think you have essentially an environment where you have impact blindness. You lose time, increase administrative burden, the client experience is at optimal, if things aren't happening smoothly, could be a revenue linkage. All the costs add up. If you have to touch something more than once, all that adds up in the end. So that was kind of the lens that we were looking at it through as it relates to how we think about modernizing some of those areas. By
Will Ayers (19:13):
Centralizing billing workflows, embedding compliance upfront and leveraging Aderant's integrated solutions, Michael Best reduced its collection cycle from 55 days to 47 days. What changed internally once you had that level of real-time visibility and control?
Jason Schultz (19:31):
Well, hopefully it's gone down even more since that case study was published. But again, I think there's value in running operations on an integrated platform. I'm a big believer in the right tool for the right job, but there's complexity when you're trying to make all these systems work seamlessly. And so I do think there's value in the integrated kind of work to cash platform suite of capabilities that Adderall offers the market. So when I think about some of the things that have changed, well, we are a subscriber to I Timekeep, which again is simplified and streamlined time entry for practitioners. And there's a ton of administrative burden in capturing time. And I'm excited about some of the opportunities to even grow further into the capabilities of that solution as it relates to passive time entry and some of the things that, again, will bring that administrative burden down even further.
(20:21):
OCG compliance, we subscribe to OCG live, which again has ensured that Bill's met our outside council guideline requirements upfront. Before past this stuff downstream, have to deal with a rejection and start the process over. It's like if you don't have time to do it right the first time, do you have double the amount of time to correct it when it comes back? It's like that whole conversation, right? And then Buildblast has become a real acre, I would say, in transforming Billing into a more centralized, automated, transparent process. We used to have to go to all of these different portals. It was a little bit of a mess. And I think with BuildBlast, our billing team has been able to reduce or in some cases eliminate a lot of the manual tasks. So there were communication gaps that have been closed. We now have real-time access and visibility into the entire billing workflow, which again, that insight allows us to see billing volumes, allows us to see email receipts, all the reporting, basically smarter financial management.
(21:14):
And so that was the whole idea of the black holes that you had referenced in your previous question. You don't know what you don't know sometimes, so it's hard to quantify the issues when you don't know what all the issues are until you start to go through this process of uncovering them. And so again, I think now with that visibility, we have more control and essentially it's our ability to audit and report on it and ultimately get paid faster, which is very, very important in our business.
Will Ayers (21:37):
Getting paid faster is very important. How did improved financial visibility impact leadership decision-making, particularly around the investments that you make at the firm, bringing in new talent and innovation priorities?
Jason Schultz (21:51):
Well, again, I think the visibility, it allows us to be, I would say, more informed, to be more proactive, to make strategic decisions. It's really the shift between decision-making that was reactive that had a lot of guesswork to proactive data-driven decisions. And I really am a big believer in that. Without data, everyone has an opinion. Data can cut through some of those conversations and some of ... And again, it enhances the decision. So if you have that visibility, you're able to evaluate investment opportunities more rigorously, you're able to assess the returns, you look at cashflow implications, basically making sure that you're making decisions that are aligned with the overall financial health of the organization. That is ultimately the outcome of
Will Ayers (22:32):
That. AI only works when ownership is shared. So let's talk a little bit more about AI and some of the things that you guys are doing at Michael Best as it pertains specifically to AI. What does true co-ownership look like at Michael Best when it comes to AI? Because I'm pretty sure your teams are working together across departments. So can you talk about that a little more?
Jason Schultz (22:56):
So at the end of the day, we are focused on driving our practitioners up the value chain and ultimately reducing the cost of fulfilling those legal services. We're really shifting from selling legal services to selling legal solutions as a result of what we're going up against here. You can't go at it alone. This can't be some siloed approach. It can't just be coming from the technology team or one practice group. It really requires a cross section of the organization, requires us all to level up together. And so I would say several years ago, we were having discussions around the approach, the strategy. How do you make sure that you are working together? You mentioned co-ownership. What does that look like? It's not any one person or one team. It's everyone rowing together. So our approach to that was creating an AI center of excellence where we could essentially identify team members to participate in a cross-functional team that would ultimately influence the direction.
(23:56):
And the idea there was get diverse perspectives, views, experiences. How do you position the organization to make sure that we're harnessing the collective knowledge, creativity, curiosity? Well, you can only do that when you're tapping people from around the organization as opposed to any one group. And so that center of excellence is kind of how we took our strategy forward. And again, it's a dedicated center, coordinates our efforts across the organization, helped us unify around our vision and made sure that we had consistent and efficient communication across all the stakeholder groups. We used the Center of Excellence to set standards and develop processes and our acceptable use policy. We also used that group as it relates to managing existing relationships with whether they're vendors or partners or potentially bringing on new ones. Also, it's a group that helps us continue to identify opportunities within our own team where we need to augment or amplify the folks that are helping us drive this strategy forward.
(24:58):
So you got to bring everyone together innovation typically as a result of collaboration, and that's something that we believe in very strongly at the firm, and it's something that we've used to move forward on the AI front.
Will Ayers (25:10):
There was a AI conference that I actually attended a couple of weeks ago, and the main theme was AI being more integrated into workflows. And I think that over the past two years, AI's transitioned from surface level automation to being deeply integrated into core systems at businesses. How do you distinguish between surface level automation and embedded intelligence that's deeply integrated into the workflows or the ecosystem at your firm?
Jason Schultz (25:46):
Great question. So I guess how I would think about it is surface level automation, again, that's been around for a while. Typically, you can use tools like basic robotic process automation, RPA, where you have a scripted workflow that can handle repetitive predefined tasks that are based on fixed rules. A lot of the processes documented or not are right for surface level automation. If X happens, do Y. Those surface level automations too are often bolted on. They're like an external layer to something that maybe a larger, a core system. When I think about embedded intelligence, I think about even AI, deeply integrated into core applications and workflows where it's operating natively where the work occurs. And there's technologies that we're using. I know that Aderant is using the deployer solutions, machine learning, natural language processing, predictive analytics, all that allows you to adapt in real time, make decisions, sometimes predict what's going to happen next and improve over time.
(26:48):
So that's kind of how I think about those two approaches. And there are distinctions. So the depth of integration would be one. Surface level is typically, like I said, it's an add-on, it's external, whereas embedded intelligence typically is built directly into the system. Think about all the AI that Adern's deploying with MADI in your practice management platform where it's starting to anticipate outcomes. That to me would be a distinction. Another distinction would be adaptability and learning. A lot of the surface automation follows static rules, and a lot of it doesn't even involve without some form of human intervention or manual reconfiguration, whereas some of the embedded intelligence learns from interactions, patterns, exceptions. It gets smarter over time, which is exciting. And another distinction I would call out would be the scalability and efficiency. So sometimes surface automation can give you a temporary lift or create a little bit of bump, whereas embedded intelligence is something that you can scale over time.
(27:46):
You can optimize resources and ultimately drive long-term productivity. So there's room to do both. I think it just comes down to what problem are you trying to solve and what tool do you need to solve it? And that's why sometimes I laugh when everyone's like, "Can't you just use AI?" And that scenario might be the very scenario where we'd be doing what you're suggesting, which is no, it's actually just surface level automation, like document automation, something like that. You don't necessarily need embedded intelligence to solve every problem, nor you might not even be in position to use it anyways. So I do think there is a distinction between those two.
Will Ayers (28:21):
Now, a common theme that always comes up when I talk to leaders in the industry like yourself is trust, governance, and responsible innovation. So law firms like Michael Best, all law firms actually always operate on trust. What does trustworthy AI mean to you and Michael Best?
Jason Schultz (28:40):
The practice of law, trust is, it's the foundational currency. It's what the client relationship is built on, confidentiality, accuracy, ethical judgment, accountability. Without it, there is no practice of law. So to me, trustworthy AI means systems and how those systems are used, it needs to preserve and demonstrate and reinforce that core professional obligation rather than undermine it. And it goes way beyond the technical performance or speed. It requires AI to be deployed in ways that align with the non-negotiable pillars of the practice of law. So we talk about rigorous governance. We talk about and make sure that you can audit it, permissions, controls, all of it. How do you govern the human elements of it? That is a big piece of it. So the components of trustworthy or responsible AI, there's many, but a few that stand out. The first would be your governance and policy framework.
(29:39):
Do you have clear firm-wide policies that define acceptable use, that communicate what is acceptable and what applications are prohibited? Is there an approval process? And then how do you manage the ongoing oversight of what's happening in the environment? Another would be, I mentioned audibility, the transparency of what it is ... You're using. You have to be able to audit that. You have to be able to understand how the technology came to that outcome. What was the data that was used? What was the reason? What was the logic? The explainability of the output. And I would say a lot of the discussions early on with a lot of the niche legal tech providers, we couldn't get past that. We couldn't get past explainability. Explain to me how this ... Give me a model card. Help me understand this. So that's a big piece of it because you have to understand this technology's a mirror of humanity right now, so there's going to be issues, there's going to be errors, there's going to be bias, there's going to be hallucinations, all that.
(30:36):
But as long as you understand it, you can manage to it. But you have to have that level of transparency and explainability. Another big area, everything we're doing today, I don't care what area of the business it is, I don't care what the solution does, you have to start with security, information security, data security. It has to be security by design. The state of the cyber crime landscape is so volatile and it's growing at such a fast rate that if you can't innovate safely and security securely, you just shouldn't do it. The stakes are too high. We have a pretty thorough vendor assessment and audit that we do to even let some of the providers into our environment, looking at access controls, looking at identity management, looking at all their documentation, looking at data encryption. There's a whole long list of things that we have to get through just before we even pilot something.
(31:26):
That's a big piece of it. And then ultimately I would say the accountability and the requirements around ethical alignment. Ultimately, the attorney is responsible. You can't shift the blame to AI did it. So you have to understand it and you have to audit it and you have to be able to explain it. And we need to make sure that we are putting our practitioners in a good place to do that.
Will Ayers (31:44):
Now, AI is augmenting a lot of daily tasks for legal professionals around the world. Where do you see AI augmenting professional judgment and where must humans remain in the loop? Because that's a huge topic every time I talk to someone.
Jason Schultz (32:02):
I think you're absolutely right. I think we are right now moving down a path where we are simultaneously enhancing productivity, efficiency, accuracy, scale, but we're also kind of destabilizing the industry as we know it. And there is a difference between what AI can do, whether you're augmenting something or automating something outright and what humans should do and where they play. And you could break down any body of work probably into three buckets. The first being, what are we doing today that is, like I said, rules-based, task-based, repetitive? We can automate that. There's a real opportunity for automation there. The second bucket is what are we doing where if we collaborated with AI with machines, we could amplify or augment what we're doing. We could get to different outcomes faster, better, for less cost. And then the third bucket is, what are we doing that's truly human?
(32:58):
And those human skills, those human capabilities, I think are valued at a premium and that premium will probably continue to increase. So some examples would be, I think AI can augment legal research, discovery, document drafting, review. There's capabilities around predictive analytics and risk management, forecasting. There's a lot of opportunity within the administrative back office functions. Think about tasks like transcribing, deposition, summarizing meetings, automating billing reviews. There's tons of stuff there where AI can run with it. I think there are certain aspects of the legal practice though that do demand human oversight. And again, there are ethical obligations. This is all governed in the ADA model rules, but there needs to be accountability and there needs to be inherent limitations of AI in handling some of the areas where there is ambiguity or where there needs to be human empathy. So the ethical and moral judgments, the complex reasoning and strategy decisions, the supervision and accountability of the outcomes.
(34:03):
And then ultimately where I think there's a huge opportunity for us to spend more time is around the client relationships, like building trust, counseling clients through crisis or helping them seize opportunities. And being able to interpret all the nonverbal cues in a mediation, for example, that is going to always require a human element. I don't think AI is going to be able to do that.
Will Ayers (34:25):
Now, I think in your role, you sit in a very interesting spot because you are the CIO at Michael Best. Technology is moving fast, but I would say maybe the legal industry overall as an institution doesn't necessarily move at the same speed, I would say. But I think that firms don't have the luxury of a five-year transformation cycle anymore either. How has that changed your change management approach as a leader?
Jason Schultz (34:57):
I think I spend most of my day selling change, telling stories, negotiating, debating, helping expand the imagination of folks that have the curse of knowledge because they've been very successful doing what they do a certain way for a very long time. It's hard to disrupt something that's still working today. Comfort is ultimately the enemy of change. If you want to grow, you got to get uncomfortable. How do you do that? A couple things that stand out. One is just the technology itself. A lot of organizations, certainly a lot of firms, all their technologies rolled into one operating budget. So the innovative strategic initiatives don't necessarily stand out. They're bucketed in. Now you can drill down and peel back the layers, but we found that separating where the dollars are going has allowed us to have a different conversation with leadership and with other stakeholders across the firm.
(35:47):
So through our budget cycle leads here, we have our standard IT operating budget, the blocking, the tackling, the keeping the lights on, keeping the systems and environment secure. And then we have programs portfolio where we're saying, "Hey, these are the initiatives that align with our strategic plan, our strategic priorities, and where we're trying to go. " And we really try to focus the conversation in that portfolio. Now, not everything in that portfolio gets funded approved, but the idea is we're having a very focused conversation on the initiatives, programs, and technologies that are moving the needle versus the ones that are keeping us operational. Those are two to meet very different conversations. You also have to make sure that you're managing the outcomes and you're telling that story over and over and over again. It all starts with a sense of urgency. We talked about the three whys early.
(36:34):
You get through that, then you got to get a guiding coalition. Most of the great ideas that we've been able to execute on were because somebody else raised their hand and we championed it. There's a quote I like that says, "It's amazing what you can accomplish when you don't care who gets the credit." So let other people get the credit, build that guiding coalition. And then again, you got to communicate over and over. We do a lot of things along the way. We're blazing trails, so you're going to take a branch to the face when you're out in the woods, but you have to be able to enable action, remove barriers. And some of that comes down to incentivizing the right behavior, showcasing work, funding pilots, rewarding early adopters, all of that. And then again, just start stacking those short-term wins. And I think that's really what helps sustain the acceleration and the world we're in today.
Will Ayers (37:18):
Now, as a part of that acceleration, that means that things are moving fast. There's a new AI startup or company that is trending, popping up pretty much every week. But at the same time, you guys are juggling AI pilots, system upgrades, still running the business. So you have client expectations that are still there as well. How do you prevent your firm from going through innovation fatigue?
Jason Schultz (37:45):
Well, I don't know if we're able to prevent it, but we try to minimize it. And I think you're spot on. There is innovation fatigue, there's AI fatigue, there's transformation fatigue, creates anxiety, quite frankly. And again, that's why you have to remain focused. I always like to say deep breaths and baby steps. And the idea is that sometimes slow is smooth and smooth is fast because you can get bogged down with taking on too much. And it's not just like, can the technology do it? Can we add it into the environment? Can we integrate all that? It's the human component. Can humans adapt? Are we throwing too much change at the organization at one time? And we manage to that. We have change management monthly meetings. We are looking at a change management schedule that extends throughout the year. We're constantly moving stuff around reprioritizing, sequencing when things are triggered, when we're communicating, how much in advance we're communicating, what are we communicating?
(38:37):
Who do we need to pull in? It's somewhat of a fluid state. It's not a set and forget strategy. It's dynamic. And I think that is the approach. You have to have a dynamic approach to going about this. I think you also have to set the proper expectations like, "Hey, we are piloting this. We are testing this. We are experimenting. This might make it through. This might be the tool, the opportunity, but it might not. " And I think when you tell folks that upfront, that's very helpful because you're setting the expectation that you might invest some time in something that doesn't make it to the next phase. We try not to overpromise, if you will. We try to be very transparent and again, reward people for their contributions. And that's very important because we need multiple people, multiple stakeholders, multiple groups participating to that strategy.
(39:21):
So I think just being clear, having a clear visible strategy tied to firm objectives and goals, I think making sure leadership's behind it, make sure we have the right mindset, growth mindset, and then start small and build and just keep communicating over and over.
Will Ayers (39:36):
As you continue to build and in times of acceleration, what signals tell you that a transformation or a transformative initiative like the things that you guys are doing to modernize work to cash, what tells you that those things are working and culturally taking hold? Because I think an interesting thing about change management is you are adopting new technology, but you kind of mentioned it earlier. You are changing the culture with inside the organization as well. So in terms of acceleration, what signals tell you that things are working and that culturally inside the firm, it's moving in the right direction? I
Jason Schultz (40:17):
Think there's a variety of signals. I think some of them are qualitative, some are quantitative. As an example, you can track surveys, there could be baseline success metrics where we say, "Here's how we used to do it. These were the outcomes. Here's how we're doing it. Now look what we've changed." And then there's a lot of behavioral observations. So an example would be employee or team member engagement and satisfaction. Early on, there's always resistance. You're moving people's cheese. And again, some people, they jump into those opportunities. They can't wait for you to change something, but others, it takes a little while. So I think when you see team members embrace the new process, typically they're going to report higher job satisfaction. That's a pretty strong sign. When you're showing, "Hey, this initiative is helping you do things better, helping you grow, helping you expand." That really helps foster a sense of ownership.
(41:11):
It allows them to fingerprint it and be a part of it versus just you must do this. That's why I'm saying there's a lot of storytelling that needs to occur even once you get something new into the organization. So the big piece I would say is employee engagement satisfaction. Another would be you see a lot of collaboration innovation. So I know culturally things are working when I'm starting to hear feedback, inputs, ideas from across the organization. It's almost like an informal collaboration that's happening, a focus effort to modernize our processes. And it's cool because we're trying to promote it, but some of it's happening organically. And there again, there's things that we look at to track this, everything from idea submissions coming into our pipeline to the successful outcomes of projects to how that impacts profitable, revenue growth, all of it. And then another big signal or thing we like to look at is overall performance and client feedback.
(42:05):
Ultimately, that's what matters is what we're doing is a transformation that we're deploying yielding tangible results. So are we shortening the work to cash cycle? Do we have higher realization rates? Are we getting more client feedback when we do our listening sessions? All of that, I think, really helps support the conversation.
Will Ayers (42:27):
Now, before we wrap, let's zoom out a little bit because we zoomed in on Michael Beth, but we're going to zoom out just a little bit. Michael Best is one firm, but the pressures you're navigating are industry-wide. If you zoom out beyond Michael Best and look at the legal industry as a whole, five years from now, what will separate the firms that truly transform from the ones that did not?
Jason Schultz (42:51):
So I think we're going through a very interested period in human history, and we've experienced this before, but I think the pace of change that we're experiencing now is a multiple of whatever we've been up against in human history. So when I think about the practice of law, it's hard to ignore how similar AI technology is to what ... Not everything that legal practitioners do, but a good portion of it. It is and will directly impact the business model and all the economics around the industry. And so we're already seeing it. When you look at some of these tools and what they can do and what they did yesterday and what they can do today, the marginal cost of a lot of foundational legal services, whether that's diligence, drafting, legal research, document summarization, when the marginal cost of those services approaches zero, I don't know how you continue to defend a pricing model that's based on units of time.
(43:45):
That's not to suggest that the billable hour will go away. I think the billable hour will be a part of the overall fee structure, but there needs to be other fee arrangements that need to be offered. And it's really going to come down to a conversation collaboration with the client. Right now, we are very much tethered to the billable hour. All of the success metrics, the productivity metrics, everything that's incentivizing the behavior of a practitioner is tied to that. So I feel like today leaders are faced with these impossible choices. Do you adopt AI and then hours fall, which your revenue falls if you do go make it up or do you resist it? Which again, there are firms that are resisting it. I think clients are going to defect at a faster rate because there's going to be cheaper competition that can do the same thing.
(44:26):
So the entire business model has to be transformed. The economics have to shift to outputs like valued outputs, not billable hours. The revenue increases need to be based on more outputs, not more hours. I think attorneys that are using AI will replace attorneys that are not. Attorneys that are using AI are going to scale their practices because they're going to be improving models, workflow, not adding more people. And when you start to look at that level of disruption, Will, we should experience higher margins. We should be able to get more predictable outcomes. We should have a more efficient service delivery model. And ultimately that has to be a better customer client experience. So the industry, I think in five, probably before this, but to answer your question, I think it's going to evolve from a traditionally human-centric, billable hour dominated field to a more efficient, data-driven, value-oriented ecosystem.
(45:21):
And I think good lawyers in the future are going to be delegators and leaders, not just document producers and experts. I think that is ultimately the big shift. And I think the firms and leaders that understand that and understand that this is a mindset shift, that they understand that we now have intelligence on tap and that's disruptive, but that's also very exciting. Abundance creates new work. We're so busy right now chasing urgent tasks that we never get to the important work sometimes. It's like we're working in and not on it. So think about, I think leaders that are asking the question today of, what problems could you solve with 4X, 10X, 100X growth of intelligence? What could we do with that? To me, that's the questions that we should be asking today. We should be looking at the fact that a lot of the routine hourly tasks can be automated, and what does that mean to firm economics?
(46:14):
How do we shift attorneys from being the firefighters to being strategic partners? And then all the while, I think the very clients that we serve, the in- house legal departments, they're having the same conversations and they're going to absorb more. They're going to absorb more work. And so we need to be, as outside counsel, we need to be prepared for that. We need to help our clients get there before they realize they need to. We need to change the value proposition. We need to work collaboratively with them in scoping work, scoping matters, coming to reasonable pricing agreements. We need to do this with them and not to them. I think those are some of the things I think about or how it's going to shake out. And I think the firms that figured that out give me a ton of growth potential because think about this too.
(46:58):
If AI does what everyone's suggesting, there's going to be a lot of economic growth. Well, if the economy continues to grow, there's going to be a lot more opportunity to provide legal solutions. Now, the number of organizations, number of firms providing those legal solutions might go down, but I think the overall portfolio of work or the overall size of the pie, I think is going to continue to grow. So the firms that are failing fast, learning fast, that are changing the culture that are leading and prescribing the change as opposed to waiting for people to opt in and volunteer, I think those are the ones that are going to make it. The ones that are disrupting versus waiting to be disrupted.
Will Ayers (47:35):
Well, Jason, thanks for an incredible conversation. As you know, I'm a huge fan and I was waiting for this conversation and it definitely delivered. I'm a fan of all of the amazing things that you all are doing at Michael Best and no doubt about it. You are one of the top innovators and voices in our industry. So I appreciate you taking the time out of your busy day schedule to stop by Studio A, and I definitely look forward to having you back on again. Hopefully, I can get an interview with you at Momentum 2026.
Jason Schultz (48:08):
Yeah, I would love to do that. Love to continue the conversation and appreciate the time, appreciate the feedback. And like I said, I'm a big fan of you, the Aderant team, everything you're all doing. I think there is something to be said about strategic partnerships and not just vendors selling solutions. And I've always viewed Aderant as a strategic partner. I think you're making the right moves. I think the market position, the growth trajectory, how you're innovating, where you're innovating makes a ton of sense. And we're just happy to be a part of that journey and to be a part of that collaboration. So appreciate the time.
Will Ayers (48:37):
And we feel the same way, Jason.
Jason Schultz (48:39):
Awesome. Have a great day.
Will Ayers (48:41):
That's Jason Schultz, CIO at Michael Best. In the AI era, experimentation is easy, but institutionalizing change is hard. But one thing is certain, the law firms that win will build integrated ecosystems. If you enjoyed this conversation, you can check us out on all major streaming platforms, Apple Podcasts, Amazon Music, Spotify, and YouTube. Thanks for tuning in to Studio A. Thanks for listening to Studio A. For more from this episode, visit adorant.com. Be sure to subscribe so you never miss a beat, and we'll see you next time in Studio A.
There is innovation fatigue, there's AI fatigue, there's transformation fatigue, creates anxiety, quite frankly. And again, that's why you have to remain focused. I always like to say deep breaths and baby steps. And the idea is that sometimes slow is smooth and smooth is fast because you can get bogged down with taking on too much.
Will Ayers (00:19):
Behind every great law firm are bold leaders and powerful solutions that help them run a better business. Welcome to Studio A, the home of legal tech innovation. Welcome to Studio A, powered by Aderant, your podcast for the latest conversations shaping legal tech. I'm Will Ayers. The legal industry has moved beyond incremental change. AI is definitely accelerating and also increasing expectations as well. Clients are demanding precision and return on their ROI and operational discipline is now a competitive advantage. Today, I'm joined by the talented innovator himself, Jason Schultz. He's the CIO at Michael Best and Friedrich. The AmLaw 200 firm has more than 400 legal professionals and serves clients around the globe. In addition to that, they are known as one of the most innovative firms in the legal industry. So on this episode, we will explore what leadership looks like when transformation is expected and it's not optional.
(01:28):
And what separates law firms that are experimenting with technology from those that institutionalize it? Jason, thanks for finally, finally joining us on Studio A. How are you doing today?
Jason Schultz (01:42):
I'm doing well. Appreciate you having me and glad we were able to finally get these dots to connect. I know there's some scheduling hurdles, but big fan of the show, big fan of everything the A team's up to and happy to be here and be a part of this discussion, so appreciate it.
Will Ayers (01:56):
Thank you. Thank you. And we are a big fan of you as well. That's why you are on studio. A, so before we get started, tell us a little bit more about your role at Michael Best and some of the key things that you are responsible for at your law firm.
Jason Schultz (02:11):
Yeah, appreciate that. So per your intro, I'm leading innovation and technology at Michael Best. Kind of a cool story with the firm. We're 177 years old now and really have grown the firm, both from a talent perspective, from a capability perspective, but also just geographically. We now are spread across 20 offices in nine states and we're doing some pretty innovative things. In addition to our primary business, which is our law firm, we also have another non-legal consulting entity called Michael Best Strategies, where we do some consulting, government relations. We also do some public affairs work, kind of that intersection between business and government. And so in my role, I get to oversee various areas of technology, security and innovation across those entities. I would say in my role day-to-day, it's kind of three areas of focus. The first being everything we're doing from a cybersecurity and data privacy perspective.
(03:02):
So how do we enhance our security programs? How do we harden the environment? And how do we make sure that we can instill continued trust and confidence in the programs we put together? The second area would be IT operations and infrastructure. So everything from our network to our enterprise application stack, to custom app dev, to how we support all those capabilities with inside the organization. And then the third area, I think, which is where this conversation will be more focused is around innovation, process improvement, change management. How do we do things better, faster? How do we improve efficiencies? How do we reduce administrative burden? How do we drive our practitioners up the value chain, drive the cost down and all the while providing an amazing client experience for those that we serve?
Will Ayers (03:46):
Now you mentioned doing better things faster, and I think that's a great segue to our questions. Let's dive into leadership during this moment of rapid acceleration across the legal industry. The legal industry is moving from incremental change to structural change. What does leadership look like when transformation is no longer optional, but expected by clients, attorneys, and the market in general?
Jason Schultz (04:13):
Yeah, great question. Well, as you stated, the industry's certainly going through a seismic shift, if you will. And I do believe that's being driven by a variety of factors. One, technological advancements. There's a lot of cool emerging tech, AI, obviously being at the forefront of that conversation. Client demands are changing and shifting. The competitive landscape is shifting. There's more alternative legal service providers out there, more folks that are doing pieces of the overall puzzle. The talent dynamics are more competitive than ever, and then just the overall market pressures that we're facing in and outside the industry. And so it's not really optional. To your point, I think the question is structured very well. It's a must. Leadership must evolve beyond the status quo. And so how do you go about doing that? Well, I find the conversation around AI to be a fascinating one. As you know, it's not a new concept.
(05:03):
This technology's been around in various forms and we've been using it in narrow ways for many years. Although I do think the stage has been set as it relates to what GenAI is doing and some of the new capabilities that have been developed as a result of that. And that's just a matter of timing. The computing power, having sufficient training data, all of that to be able to demonstrate these capabilities at scale is now readily available. And I feel that data proliferation is kind of fueling the boom. And so here we are. It's disrupt or be disrupted. A few years back, I was trying to pull some folks along and now they're kind of pulling me along a little bit. It's hard to keep up with everything that's going on. I do think though that AI will expose leaders who are thinking like machines. And if you think about certain areas of the work that we do as knowledge workers, there's some of it that is formulaic or you could program it.
(05:55):
It's database, rules-based, task-based. So there's an element of that that the machines can do very well. And so again, I think AI is going to expose the leaders that are tethered to that old way of thinking. I think the future is going to belong to leaders that are architecting what is possible, the art of what is possible. I also think that because AI is moving so quickly, it's exciting. It can augment or amplify a lot of what we do, but that means it can amplify both your capabilities and also your dysfunction. So if your processes are broken, AI will help you fail faster. If your strategy's unclear, AI will optimize toward the wrong goals more efficiently. So I think we're kind of at this threshold of a new leadership era, one where AI is going to expose the limits of that legacy thinking. Folks that are, again, are looking in the rear view mirror and set out the windshield.
(06:45):
And it's going to be a first stop for any leader that is able to say, "Hey, I need to be more self-aware." And there's opportunities here, like asking the right questions. Are we using AI to improve the past or to invent the future? Do we deploy AI to shrink the workforce and automate yesterday's work? Are we trying to go up out in a different way? Are we trying to augment human potential? Are we trying to pursue different outcomes? Are we trying to invent an entirely new business model? That to me, those are the exciting conversations that I could be a part of. And again, I think it requires people to really have to reimagine. There's a quote I like by, don't hold me to this, but I believe the author is H. Nelson Jackson. And the quote is, "You can't do today's job with yesterday's methods and be in business tomorrow." And that's kind of where we're at.
(07:33):
That's where the conversation's at. So again, it's easy to stay in the past, but I don't think we have a choice. I think it's here and that's going to require a new form of leadership and a lot of things have to happen to get there. Unlearning, embracing the disruption, being in the game, and just accepting the fact that we're all experts in the making. I think there's a lot of folks on the sideline right now because they don't know what they don't know as opposed to being curious, creative, leaning into the learning, failing forward, which is where I like to play.
Will Ayers (08:02):
Now, there's a difference between adopting tools and building capacity or capability. At Michael Best, how do you ensure innovation? Because things are moving very fast at the moment in the era that we're in.
Jason Schultz (08:17):
Yeah, I think that's a good question. So adopting tools, typically when I think about adopting tools, that approach is focusing on acquiring and using ready-made off-the-shelf solutions. There's a lot of SaaS products out there subscribe to them, or you're implementing vendor-provided technology has minimal configuration or customization. So when I'm adopting a tool, it's like speed. They're quick to deploy. There's typically lower upfront risk or cost. There might be less internal effort to actually get it out there into the ecosystem. The integration complexity might not be there. Even the adoption challenges themselves might be fewer and far between. And so I think about that when I think about adoptive tools, and certainly have a lot of tools in our toolkit. So we are adopting tools. But when I think about building capability, that to me is more part of a longer term strategy. Maybe there's a roadmap involved where you're really looking at maybe more disruptive innovation versus more incremental innovation.
(09:13):
Slower to start, there's going to be an investment in people. You might have to hire people, you might not have the skills on the current bench. You might have to re-engineer or develop a process. There might be infrastructure pieces that you need in place. So it's like a slower start that maybe has more experimentation iteration. Oftentimes when I think about building capability, there's also controls that need to be in place. If you think about it from a compliance perspective, having the right governance models in place. Integrations. When you're doing these big investing in big platforms or making big shifts in how you're approaching your technology stack, you have to think about larger integrations, you have to think about long-term ownership. So it's not just the initial release, but how do you continue to enhance it, make it better, optimize it? And then ultimately, I think the outcomes are different.
(10:01):
How you measure those outcomes is different than ... We turn on tools all the time because it's a cost of doing business. Whereas if we're trying to do something more disruptive, we very much are looking at the outcome and how we're managing and measuring the return on those larger investments. I think the second part of your question though is how do you ensure innovation? And it's easy to chase shiny objects. I certainly think there's a lot of hype right now within AI, but for me, innovation requires a strategy regardless of what the innovation is. And I always have defined innovation as applying novel solutions to meaningful problems in order to create value. So if you just look at it, people think when they deploy technology, they're innovating. Or I love when people say innovation's the light bulb. It's the idea. It's not the idea. And it's often not just the technology.
(10:49):
Technology itself solves nothing. It requires people and process of change. It requires the behavior surrounding the technology to determine if adoption is successful or not. And I think that's what's going on right now, certainly in the legal industry, is that we're at this innovation theorist call it the chasm. It's a point where the initial enthusiasm from a small group of early adopters, which all organizations have, they put their hands up, they're the innovators. But that enthusiasm from the small group of early adopters, it fails to translate to the organization, to the early majority. And the reason often is because of behavioral change. How do you get people to change the way they work? How do you make sure that they're not reverting back to the old methods? And that is a different approach. And again, we've gone at it since I've arrived five years ago, it's been a very consistent approach as it relates to how we innovate.
(11:39):
And so when AI became the hot topic of conversation, it wasn't like, well, how are we going to use our adopt AI? It was, while we have an innovation program, we have a strategy. Let's follow that. Let's make sure that the right ideas are the ones that are moving forward and we're not just chasing our tail, which again, you can certainly do in this environment. It's moving very, very quickly. So I think we have a different approach. It's a strategy that has a multi-year roadmap. It's tethered to our firm's strategic plan. We intake ideas from across the organization through an innovation pipeline. We use design thinking and brainstorming sessions to make sure, hey, we got a cool idea or maybe two that we want to stitch together, but are they the right idea? Is that the right problem? What's the business value? What's the cost?
(12:23):
What's the feasibility of even doing it? And once you get through those conversations, then we can start to develop a business case. And the business case has to be sound because you're going to come back to it as you get further along on your journey. We get those business cases. We have a lot of conversation within our innovation council, which again is a cross-section of the firm. And then ultimately we fund our strategic program portfolio very much like an entrepreneur would seek funding from a venture capitalist. It's a portfolio that stands on its own separate from just the core IT operating budget. And once we fund it and activate it, it's all about monitoring progress, reporting on success and failures and tracking the outcome. And then just again, iterations. The whole idea, I'm a big believer that done is better than perfect. And so sometimes you just got to get things going.
(13:11):
You got to get the feedback loop going and then you can make changes from there.
Will Ayers (13:14):
Now you talked about strategy. Let's lean into that a little bit more. As AI accelerates, how do you balance urgency with operational discipline, especially in areas like financial systems and client data where precision really, really matters?
Jason Schultz (13:30):
Well, it's very hard to do. So like I mentioned earlier, Will, I think we are still dealing with the hype cycle. I think there's a lot of noise in legal tech right now, and it's very, very challenging, I think, to find the winners. The other challenge is I don't think the hype necessarily matches the reality with regards to the effort it takes to be successful. So if I look at just how the legal tech ecosystem has grown, the amount of outside software companies that we have to try to evaluate and ultimately manage, it's skyrocketed. And so the complexity of the technology procurement process, trying to support all these various technologies and applications, trying to architect data integrations, and then all the while providing a seamless user experience, it's more challenging than ever. So one of the things that we do to make sure that we're making the right decisions is you got to start with the three whys, which is again, going back to our innovation strategy and how we approach identifying problems.
(14:27):
The three whys are, why should we do anything? Why should we do it now? And why should we do what's being proposed or recommended? And once we get through that, like I said, you got a business case, but even once you get there, you still have to look at the overall structure of the organization, like people. Is your team prepared? Do they have the capabilities necessary to make the transformation successful? Because again, a lot of things we're talking about with AI, it's not about the technological capability, it's about human adaptability. And so you need to make sure that the people piece is in a good place. The power of these tools is only good as the people that wield it or don't wield it. So the cultural aspects, cultural adoption, the change management, which you mentioned earlier, that's a big piece that ensures that you get trust upfront, you get buy-in and then you can sustain that momentum.
(15:12):
Also, the process. Are you identifying the right problems? You can't throw AI at everything, which I've heard suggested in a lot of peer groups that I'm in and some events that I've attended. You cannot automate an ad process. You got to redesign it. So sometimes you have to start there. What is the process? Do we have a process? Do we have a process that's documented and understood? Is it being applied the same, whether it's the right process or not? Let's start with the fact that we have a consistent process that everyone understands. From there, you can look for opportunities to augment or amplify. And then the technology piece is very important too because you don't always need to go and buy something new. Sometimes you already may have that capability in your portfolio. And if you do, you should really look at the incumbent technology.
(15:52):
Is that provider releasing new functionality? Are you tied to their roadmap? Do you know where they're going? Because sometimes it might just be waiting a little bit, as opposed to going and buying something new and adding it on. And the other piece to everything that we're doing too, which I think Adderall is a way out in front on, which I'm a big supporter of is the fundamentals. One of the biggest challenges a lot of firms are facing today, it's not a lack of data. It's a lack of usable, weld-structured information that can truly drive these outcomes. And so you can spend a lot of time, like I said, putting these very powerful tools on top of a bad foundation only to have to rebuild the foundation.
Will Ayers (16:28):
Now you mentioned people as a key part of that innovation strategy and Michael Best and Aderant are partners. I won't say you guys are our client. I will say you are a partner. And I've spoken to legal professionals and leaders at Michael Best before. And before modernizing your work to cast cycle, your team described black holes and visibility. Beyond lost time, what does that kind of opacity cost a firm strategically?
Jason Schultz (16:59):
Well, we've had a lot of discussions with other members of the Aderant team, and I've always walked away kind of feeling energized and inspired in some way. At the end of the day, we're in the practice of delivering value legal services to our clients. And so the people, the processes, the technology that we use to manage our revenue cycle, it's the backbone of the firm's business. So any improvements that we can make in this area, again, whether it's reducing administrative burden, improving efficiencies, removing areas of friction, all of that allows us to not only capture the work, but bill our clients and ultimately collect on those dollars, which again is the whole idea of work to cash, which I think your slogan's way better than what I said. So it's the whole idea of how do you optimize the work to cash? And we're looking at this because there's always opportunities for improvement.
(17:50):
You're never done. Now, sometimes the juice isn't worth the squeeze, but again, you can always identify opportunities for improvement because everything around us is changing. So we recognize a lot of inefficiencies, whether it was in timekeeping, billing, compliance with OCGs, all of it slowed down that work to cash cycle. And so some of the, I guess, pain points, if you will, we're like, we're recording time, but the bills weren't generated the right way, or there's manual handoffs in the workflow, or you'd get something pushed through only to find out that it was flagged because there was compliance issues. The lack of that centralized visibility adds time. And we are in an industry where time matters. It matters everywhere, but it certainly matters in the legal industry. I mean, our practitioners, we refer to them as timekeepers. And so when you have limited visibility or if you have multiple systems or processes that have to be run a certain way, there's a lot of room, a lot of variables, a lot of room for error.
(18:47):
And so when you have limited visibility, I think you have essentially an environment where you have impact blindness. You lose time, increase administrative burden, the client experience is at optimal, if things aren't happening smoothly, could be a revenue linkage. All the costs add up. If you have to touch something more than once, all that adds up in the end. So that was kind of the lens that we were looking at it through as it relates to how we think about modernizing some of those areas. By
Will Ayers (19:13):
Centralizing billing workflows, embedding compliance upfront and leveraging Aderant's integrated solutions, Michael Best reduced its collection cycle from 55 days to 47 days. What changed internally once you had that level of real-time visibility and control?
Jason Schultz (19:31):
Well, hopefully it's gone down even more since that case study was published. But again, I think there's value in running operations on an integrated platform. I'm a big believer in the right tool for the right job, but there's complexity when you're trying to make all these systems work seamlessly. And so I do think there's value in the integrated kind of work to cash platform suite of capabilities that Adderall offers the market. So when I think about some of the things that have changed, well, we are a subscriber to I Timekeep, which again is simplified and streamlined time entry for practitioners. And there's a ton of administrative burden in capturing time. And I'm excited about some of the opportunities to even grow further into the capabilities of that solution as it relates to passive time entry and some of the things that, again, will bring that administrative burden down even further.
(20:21):
OCG compliance, we subscribe to OCG live, which again has ensured that Bill's met our outside council guideline requirements upfront. Before past this stuff downstream, have to deal with a rejection and start the process over. It's like if you don't have time to do it right the first time, do you have double the amount of time to correct it when it comes back? It's like that whole conversation, right? And then Buildblast has become a real acre, I would say, in transforming Billing into a more centralized, automated, transparent process. We used to have to go to all of these different portals. It was a little bit of a mess. And I think with BuildBlast, our billing team has been able to reduce or in some cases eliminate a lot of the manual tasks. So there were communication gaps that have been closed. We now have real-time access and visibility into the entire billing workflow, which again, that insight allows us to see billing volumes, allows us to see email receipts, all the reporting, basically smarter financial management.
(21:14):
And so that was the whole idea of the black holes that you had referenced in your previous question. You don't know what you don't know sometimes, so it's hard to quantify the issues when you don't know what all the issues are until you start to go through this process of uncovering them. And so again, I think now with that visibility, we have more control and essentially it's our ability to audit and report on it and ultimately get paid faster, which is very, very important in our business.
Will Ayers (21:37):
Getting paid faster is very important. How did improved financial visibility impact leadership decision-making, particularly around the investments that you make at the firm, bringing in new talent and innovation priorities?
Jason Schultz (21:51):
Well, again, I think the visibility, it allows us to be, I would say, more informed, to be more proactive, to make strategic decisions. It's really the shift between decision-making that was reactive that had a lot of guesswork to proactive data-driven decisions. And I really am a big believer in that. Without data, everyone has an opinion. Data can cut through some of those conversations and some of ... And again, it enhances the decision. So if you have that visibility, you're able to evaluate investment opportunities more rigorously, you're able to assess the returns, you look at cashflow implications, basically making sure that you're making decisions that are aligned with the overall financial health of the organization. That is ultimately the outcome of
Will Ayers (22:32):
That. AI only works when ownership is shared. So let's talk a little bit more about AI and some of the things that you guys are doing at Michael Best as it pertains specifically to AI. What does true co-ownership look like at Michael Best when it comes to AI? Because I'm pretty sure your teams are working together across departments. So can you talk about that a little more?
Jason Schultz (22:56):
So at the end of the day, we are focused on driving our practitioners up the value chain and ultimately reducing the cost of fulfilling those legal services. We're really shifting from selling legal services to selling legal solutions as a result of what we're going up against here. You can't go at it alone. This can't be some siloed approach. It can't just be coming from the technology team or one practice group. It really requires a cross section of the organization, requires us all to level up together. And so I would say several years ago, we were having discussions around the approach, the strategy. How do you make sure that you are working together? You mentioned co-ownership. What does that look like? It's not any one person or one team. It's everyone rowing together. So our approach to that was creating an AI center of excellence where we could essentially identify team members to participate in a cross-functional team that would ultimately influence the direction.
(23:56):
And the idea there was get diverse perspectives, views, experiences. How do you position the organization to make sure that we're harnessing the collective knowledge, creativity, curiosity? Well, you can only do that when you're tapping people from around the organization as opposed to any one group. And so that center of excellence is kind of how we took our strategy forward. And again, it's a dedicated center, coordinates our efforts across the organization, helped us unify around our vision and made sure that we had consistent and efficient communication across all the stakeholder groups. We used the Center of Excellence to set standards and develop processes and our acceptable use policy. We also used that group as it relates to managing existing relationships with whether they're vendors or partners or potentially bringing on new ones. Also, it's a group that helps us continue to identify opportunities within our own team where we need to augment or amplify the folks that are helping us drive this strategy forward.
(24:58):
So you got to bring everyone together innovation typically as a result of collaboration, and that's something that we believe in very strongly at the firm, and it's something that we've used to move forward on the AI front.
Will Ayers (25:10):
There was a AI conference that I actually attended a couple of weeks ago, and the main theme was AI being more integrated into workflows. And I think that over the past two years, AI's transitioned from surface level automation to being deeply integrated into core systems at businesses. How do you distinguish between surface level automation and embedded intelligence that's deeply integrated into the workflows or the ecosystem at your firm?
Jason Schultz (25:46):
Great question. So I guess how I would think about it is surface level automation, again, that's been around for a while. Typically, you can use tools like basic robotic process automation, RPA, where you have a scripted workflow that can handle repetitive predefined tasks that are based on fixed rules. A lot of the processes documented or not are right for surface level automation. If X happens, do Y. Those surface level automations too are often bolted on. They're like an external layer to something that maybe a larger, a core system. When I think about embedded intelligence, I think about even AI, deeply integrated into core applications and workflows where it's operating natively where the work occurs. And there's technologies that we're using. I know that Aderant is using the deployer solutions, machine learning, natural language processing, predictive analytics, all that allows you to adapt in real time, make decisions, sometimes predict what's going to happen next and improve over time.
(26:48):
So that's kind of how I think about those two approaches. And there are distinctions. So the depth of integration would be one. Surface level is typically, like I said, it's an add-on, it's external, whereas embedded intelligence typically is built directly into the system. Think about all the AI that Adern's deploying with MADI in your practice management platform where it's starting to anticipate outcomes. That to me would be a distinction. Another distinction would be adaptability and learning. A lot of the surface automation follows static rules, and a lot of it doesn't even involve without some form of human intervention or manual reconfiguration, whereas some of the embedded intelligence learns from interactions, patterns, exceptions. It gets smarter over time, which is exciting. And another distinction I would call out would be the scalability and efficiency. So sometimes surface automation can give you a temporary lift or create a little bit of bump, whereas embedded intelligence is something that you can scale over time.
(27:46):
You can optimize resources and ultimately drive long-term productivity. So there's room to do both. I think it just comes down to what problem are you trying to solve and what tool do you need to solve it? And that's why sometimes I laugh when everyone's like, "Can't you just use AI?" And that scenario might be the very scenario where we'd be doing what you're suggesting, which is no, it's actually just surface level automation, like document automation, something like that. You don't necessarily need embedded intelligence to solve every problem, nor you might not even be in position to use it anyways. So I do think there is a distinction between those two.
Will Ayers (28:21):
Now, a common theme that always comes up when I talk to leaders in the industry like yourself is trust, governance, and responsible innovation. So law firms like Michael Best, all law firms actually always operate on trust. What does trustworthy AI mean to you and Michael Best?
Jason Schultz (28:40):
The practice of law, trust is, it's the foundational currency. It's what the client relationship is built on, confidentiality, accuracy, ethical judgment, accountability. Without it, there is no practice of law. So to me, trustworthy AI means systems and how those systems are used, it needs to preserve and demonstrate and reinforce that core professional obligation rather than undermine it. And it goes way beyond the technical performance or speed. It requires AI to be deployed in ways that align with the non-negotiable pillars of the practice of law. So we talk about rigorous governance. We talk about and make sure that you can audit it, permissions, controls, all of it. How do you govern the human elements of it? That is a big piece of it. So the components of trustworthy or responsible AI, there's many, but a few that stand out. The first would be your governance and policy framework.
(29:39):
Do you have clear firm-wide policies that define acceptable use, that communicate what is acceptable and what applications are prohibited? Is there an approval process? And then how do you manage the ongoing oversight of what's happening in the environment? Another would be, I mentioned audibility, the transparency of what it is ... You're using. You have to be able to audit that. You have to be able to understand how the technology came to that outcome. What was the data that was used? What was the reason? What was the logic? The explainability of the output. And I would say a lot of the discussions early on with a lot of the niche legal tech providers, we couldn't get past that. We couldn't get past explainability. Explain to me how this ... Give me a model card. Help me understand this. So that's a big piece of it because you have to understand this technology's a mirror of humanity right now, so there's going to be issues, there's going to be errors, there's going to be bias, there's going to be hallucinations, all that.
(30:36):
But as long as you understand it, you can manage to it. But you have to have that level of transparency and explainability. Another big area, everything we're doing today, I don't care what area of the business it is, I don't care what the solution does, you have to start with security, information security, data security. It has to be security by design. The state of the cyber crime landscape is so volatile and it's growing at such a fast rate that if you can't innovate safely and security securely, you just shouldn't do it. The stakes are too high. We have a pretty thorough vendor assessment and audit that we do to even let some of the providers into our environment, looking at access controls, looking at identity management, looking at all their documentation, looking at data encryption. There's a whole long list of things that we have to get through just before we even pilot something.
(31:26):
That's a big piece of it. And then ultimately I would say the accountability and the requirements around ethical alignment. Ultimately, the attorney is responsible. You can't shift the blame to AI did it. So you have to understand it and you have to audit it and you have to be able to explain it. And we need to make sure that we are putting our practitioners in a good place to do that.
Will Ayers (31:44):
Now, AI is augmenting a lot of daily tasks for legal professionals around the world. Where do you see AI augmenting professional judgment and where must humans remain in the loop? Because that's a huge topic every time I talk to someone.
Jason Schultz (32:02):
I think you're absolutely right. I think we are right now moving down a path where we are simultaneously enhancing productivity, efficiency, accuracy, scale, but we're also kind of destabilizing the industry as we know it. And there is a difference between what AI can do, whether you're augmenting something or automating something outright and what humans should do and where they play. And you could break down any body of work probably into three buckets. The first being, what are we doing today that is, like I said, rules-based, task-based, repetitive? We can automate that. There's a real opportunity for automation there. The second bucket is what are we doing where if we collaborated with AI with machines, we could amplify or augment what we're doing. We could get to different outcomes faster, better, for less cost. And then the third bucket is, what are we doing that's truly human?
(32:58):
And those human skills, those human capabilities, I think are valued at a premium and that premium will probably continue to increase. So some examples would be, I think AI can augment legal research, discovery, document drafting, review. There's capabilities around predictive analytics and risk management, forecasting. There's a lot of opportunity within the administrative back office functions. Think about tasks like transcribing, deposition, summarizing meetings, automating billing reviews. There's tons of stuff there where AI can run with it. I think there are certain aspects of the legal practice though that do demand human oversight. And again, there are ethical obligations. This is all governed in the ADA model rules, but there needs to be accountability and there needs to be inherent limitations of AI in handling some of the areas where there is ambiguity or where there needs to be human empathy. So the ethical and moral judgments, the complex reasoning and strategy decisions, the supervision and accountability of the outcomes.
(34:03):
And then ultimately where I think there's a huge opportunity for us to spend more time is around the client relationships, like building trust, counseling clients through crisis or helping them seize opportunities. And being able to interpret all the nonverbal cues in a mediation, for example, that is going to always require a human element. I don't think AI is going to be able to do that.
Will Ayers (34:25):
Now, I think in your role, you sit in a very interesting spot because you are the CIO at Michael Best. Technology is moving fast, but I would say maybe the legal industry overall as an institution doesn't necessarily move at the same speed, I would say. But I think that firms don't have the luxury of a five-year transformation cycle anymore either. How has that changed your change management approach as a leader?
Jason Schultz (34:57):
I think I spend most of my day selling change, telling stories, negotiating, debating, helping expand the imagination of folks that have the curse of knowledge because they've been very successful doing what they do a certain way for a very long time. It's hard to disrupt something that's still working today. Comfort is ultimately the enemy of change. If you want to grow, you got to get uncomfortable. How do you do that? A couple things that stand out. One is just the technology itself. A lot of organizations, certainly a lot of firms, all their technologies rolled into one operating budget. So the innovative strategic initiatives don't necessarily stand out. They're bucketed in. Now you can drill down and peel back the layers, but we found that separating where the dollars are going has allowed us to have a different conversation with leadership and with other stakeholders across the firm.
(35:47):
So through our budget cycle leads here, we have our standard IT operating budget, the blocking, the tackling, the keeping the lights on, keeping the systems and environment secure. And then we have programs portfolio where we're saying, "Hey, these are the initiatives that align with our strategic plan, our strategic priorities, and where we're trying to go. " And we really try to focus the conversation in that portfolio. Now, not everything in that portfolio gets funded approved, but the idea is we're having a very focused conversation on the initiatives, programs, and technologies that are moving the needle versus the ones that are keeping us operational. Those are two to meet very different conversations. You also have to make sure that you're managing the outcomes and you're telling that story over and over and over again. It all starts with a sense of urgency. We talked about the three whys early.
(36:34):
You get through that, then you got to get a guiding coalition. Most of the great ideas that we've been able to execute on were because somebody else raised their hand and we championed it. There's a quote I like that says, "It's amazing what you can accomplish when you don't care who gets the credit." So let other people get the credit, build that guiding coalition. And then again, you got to communicate over and over. We do a lot of things along the way. We're blazing trails, so you're going to take a branch to the face when you're out in the woods, but you have to be able to enable action, remove barriers. And some of that comes down to incentivizing the right behavior, showcasing work, funding pilots, rewarding early adopters, all of that. And then again, just start stacking those short-term wins. And I think that's really what helps sustain the acceleration and the world we're in today.
Will Ayers (37:18):
Now, as a part of that acceleration, that means that things are moving fast. There's a new AI startup or company that is trending, popping up pretty much every week. But at the same time, you guys are juggling AI pilots, system upgrades, still running the business. So you have client expectations that are still there as well. How do you prevent your firm from going through innovation fatigue?
Jason Schultz (37:45):
Well, I don't know if we're able to prevent it, but we try to minimize it. And I think you're spot on. There is innovation fatigue, there's AI fatigue, there's transformation fatigue, creates anxiety, quite frankly. And again, that's why you have to remain focused. I always like to say deep breaths and baby steps. And the idea is that sometimes slow is smooth and smooth is fast because you can get bogged down with taking on too much. And it's not just like, can the technology do it? Can we add it into the environment? Can we integrate all that? It's the human component. Can humans adapt? Are we throwing too much change at the organization at one time? And we manage to that. We have change management monthly meetings. We are looking at a change management schedule that extends throughout the year. We're constantly moving stuff around reprioritizing, sequencing when things are triggered, when we're communicating, how much in advance we're communicating, what are we communicating?
(38:37):
Who do we need to pull in? It's somewhat of a fluid state. It's not a set and forget strategy. It's dynamic. And I think that is the approach. You have to have a dynamic approach to going about this. I think you also have to set the proper expectations like, "Hey, we are piloting this. We are testing this. We are experimenting. This might make it through. This might be the tool, the opportunity, but it might not. " And I think when you tell folks that upfront, that's very helpful because you're setting the expectation that you might invest some time in something that doesn't make it to the next phase. We try not to overpromise, if you will. We try to be very transparent and again, reward people for their contributions. And that's very important because we need multiple people, multiple stakeholders, multiple groups participating to that strategy.
(39:21):
So I think just being clear, having a clear visible strategy tied to firm objectives and goals, I think making sure leadership's behind it, make sure we have the right mindset, growth mindset, and then start small and build and just keep communicating over and over.
Will Ayers (39:36):
As you continue to build and in times of acceleration, what signals tell you that a transformation or a transformative initiative like the things that you guys are doing to modernize work to cash, what tells you that those things are working and culturally taking hold? Because I think an interesting thing about change management is you are adopting new technology, but you kind of mentioned it earlier. You are changing the culture with inside the organization as well. So in terms of acceleration, what signals tell you that things are working and that culturally inside the firm, it's moving in the right direction? I
Jason Schultz (40:17):
Think there's a variety of signals. I think some of them are qualitative, some are quantitative. As an example, you can track surveys, there could be baseline success metrics where we say, "Here's how we used to do it. These were the outcomes. Here's how we're doing it. Now look what we've changed." And then there's a lot of behavioral observations. So an example would be employee or team member engagement and satisfaction. Early on, there's always resistance. You're moving people's cheese. And again, some people, they jump into those opportunities. They can't wait for you to change something, but others, it takes a little while. So I think when you see team members embrace the new process, typically they're going to report higher job satisfaction. That's a pretty strong sign. When you're showing, "Hey, this initiative is helping you do things better, helping you grow, helping you expand." That really helps foster a sense of ownership.
(41:11):
It allows them to fingerprint it and be a part of it versus just you must do this. That's why I'm saying there's a lot of storytelling that needs to occur even once you get something new into the organization. So the big piece I would say is employee engagement satisfaction. Another would be you see a lot of collaboration innovation. So I know culturally things are working when I'm starting to hear feedback, inputs, ideas from across the organization. It's almost like an informal collaboration that's happening, a focus effort to modernize our processes. And it's cool because we're trying to promote it, but some of it's happening organically. And there again, there's things that we look at to track this, everything from idea submissions coming into our pipeline to the successful outcomes of projects to how that impacts profitable, revenue growth, all of it. And then another big signal or thing we like to look at is overall performance and client feedback.
(42:05):
Ultimately, that's what matters is what we're doing is a transformation that we're deploying yielding tangible results. So are we shortening the work to cash cycle? Do we have higher realization rates? Are we getting more client feedback when we do our listening sessions? All of that, I think, really helps support the conversation.
Will Ayers (42:27):
Now, before we wrap, let's zoom out a little bit because we zoomed in on Michael Beth, but we're going to zoom out just a little bit. Michael Best is one firm, but the pressures you're navigating are industry-wide. If you zoom out beyond Michael Best and look at the legal industry as a whole, five years from now, what will separate the firms that truly transform from the ones that did not?
Jason Schultz (42:51):
So I think we're going through a very interested period in human history, and we've experienced this before, but I think the pace of change that we're experiencing now is a multiple of whatever we've been up against in human history. So when I think about the practice of law, it's hard to ignore how similar AI technology is to what ... Not everything that legal practitioners do, but a good portion of it. It is and will directly impact the business model and all the economics around the industry. And so we're already seeing it. When you look at some of these tools and what they can do and what they did yesterday and what they can do today, the marginal cost of a lot of foundational legal services, whether that's diligence, drafting, legal research, document summarization, when the marginal cost of those services approaches zero, I don't know how you continue to defend a pricing model that's based on units of time.
(43:45):
That's not to suggest that the billable hour will go away. I think the billable hour will be a part of the overall fee structure, but there needs to be other fee arrangements that need to be offered. And it's really going to come down to a conversation collaboration with the client. Right now, we are very much tethered to the billable hour. All of the success metrics, the productivity metrics, everything that's incentivizing the behavior of a practitioner is tied to that. So I feel like today leaders are faced with these impossible choices. Do you adopt AI and then hours fall, which your revenue falls if you do go make it up or do you resist it? Which again, there are firms that are resisting it. I think clients are going to defect at a faster rate because there's going to be cheaper competition that can do the same thing.
(44:26):
So the entire business model has to be transformed. The economics have to shift to outputs like valued outputs, not billable hours. The revenue increases need to be based on more outputs, not more hours. I think attorneys that are using AI will replace attorneys that are not. Attorneys that are using AI are going to scale their practices because they're going to be improving models, workflow, not adding more people. And when you start to look at that level of disruption, Will, we should experience higher margins. We should be able to get more predictable outcomes. We should have a more efficient service delivery model. And ultimately that has to be a better customer client experience. So the industry, I think in five, probably before this, but to answer your question, I think it's going to evolve from a traditionally human-centric, billable hour dominated field to a more efficient, data-driven, value-oriented ecosystem.
(45:21):
And I think good lawyers in the future are going to be delegators and leaders, not just document producers and experts. I think that is ultimately the big shift. And I think the firms and leaders that understand that and understand that this is a mindset shift, that they understand that we now have intelligence on tap and that's disruptive, but that's also very exciting. Abundance creates new work. We're so busy right now chasing urgent tasks that we never get to the important work sometimes. It's like we're working in and not on it. So think about, I think leaders that are asking the question today of, what problems could you solve with 4X, 10X, 100X growth of intelligence? What could we do with that? To me, that's the questions that we should be asking today. We should be looking at the fact that a lot of the routine hourly tasks can be automated, and what does that mean to firm economics?
(46:14):
How do we shift attorneys from being the firefighters to being strategic partners? And then all the while, I think the very clients that we serve, the in- house legal departments, they're having the same conversations and they're going to absorb more. They're going to absorb more work. And so we need to be, as outside counsel, we need to be prepared for that. We need to help our clients get there before they realize they need to. We need to change the value proposition. We need to work collaboratively with them in scoping work, scoping matters, coming to reasonable pricing agreements. We need to do this with them and not to them. I think those are some of the things I think about or how it's going to shake out. And I think the firms that figured that out give me a ton of growth potential because think about this too.
(46:58):
If AI does what everyone's suggesting, there's going to be a lot of economic growth. Well, if the economy continues to grow, there's going to be a lot more opportunity to provide legal solutions. Now, the number of organizations, number of firms providing those legal solutions might go down, but I think the overall portfolio of work or the overall size of the pie, I think is going to continue to grow. So the firms that are failing fast, learning fast, that are changing the culture that are leading and prescribing the change as opposed to waiting for people to opt in and volunteer, I think those are the ones that are going to make it. The ones that are disrupting versus waiting to be disrupted.
Will Ayers (47:35):
Well, Jason, thanks for an incredible conversation. As you know, I'm a huge fan and I was waiting for this conversation and it definitely delivered. I'm a fan of all of the amazing things that you all are doing at Michael Best and no doubt about it. You are one of the top innovators and voices in our industry. So I appreciate you taking the time out of your busy day schedule to stop by Studio A, and I definitely look forward to having you back on again. Hopefully, I can get an interview with you at Momentum 2026.
Jason Schultz (48:08):
Yeah, I would love to do that. Love to continue the conversation and appreciate the time, appreciate the feedback. And like I said, I'm a big fan of you, the Aderant team, everything you're all doing. I think there is something to be said about strategic partnerships and not just vendors selling solutions. And I've always viewed Aderant as a strategic partner. I think you're making the right moves. I think the market position, the growth trajectory, how you're innovating, where you're innovating makes a ton of sense. And we're just happy to be a part of that journey and to be a part of that collaboration. So appreciate the time.
Will Ayers (48:37):
And we feel the same way, Jason.
Jason Schultz (48:39):
Awesome. Have a great day.
Will Ayers (48:41):
That's Jason Schultz, CIO at Michael Best. In the AI era, experimentation is easy, but institutionalizing change is hard. But one thing is certain, the law firms that win will build integrated ecosystems. If you enjoyed this conversation, you can check us out on all major streaming platforms, Apple Podcasts, Amazon Music, Spotify, and YouTube. Thanks for tuning in to Studio A. Thanks for listening to Studio A. For more from this episode, visit adorant.com. Be sure to subscribe so you never miss a beat, and we'll see you next time in Studio A.
