The Hyper Adaptive Enterprise

Narrator: Wonder about the future and how you'll be working and learning. Welcome to you in 2042, the future of Work, with your host, Danielle Wallace.

Danielle Wallace: Hello and welcome to you in 2042, the future of Work. Joining me today is Melissa Reeve.

Melissa Reeve: Hi. It's such a pleasure to be here today. And uh, so my background, I like to state the genesis of the book we're going to talk started on a factory floor in Tokyo when I was studying the Toyota production system. And I go all the way back there because that's really the through line in terms of systems thinking and lean manufacturing that led me into agile spaces, organizational transformation, and now the latest version of transformation, which is AI transformation.

Danielle Wallace: This is such a timely topic that we need a lot of, uh, support on in the circles that I'm in. And I know you have that upcoming book, Hyper Adaptive. In the book you argue that the biggest bottleneck to AI adoption is the organizational operating system, not the tech. So if I look out towards the future, 20, uh, 42, what outdated structures or habits do you think might be holding teams back from using AI?

Melissa Reeve: Well, yeah, so in the book I talk about the ghost of Frederick Taylor. And Frederick Taylor was the grandfather of Taylorism, which is the management theory. And that goes all the way back to 1911. And when you think about what was happening in 1911, it was the assembly line and we had the management class and the laboring class, and it was the management class duty to impart the one best way of doing things onto the laboring class. And when I think about the ripple effect of that, I can still think of organizations today who, who think of their managing class as having the one best way of doing things and imparting that onto individuals. And then we couple that with what happened around World War II, which is the functional specialization. We had the rise of global organizations, and now we start to spin up the sales function, the marketing function, the finance function, and we've been battling those functional silos ever since. And so when I Look ahead to 2042, the operating model that got us here is not going to get us there. And so what I talk about in the book is the rewiring of the organization from these, what I call linear structures into a more AI native hyper adaptive structure which starts to look more like orchestrated value streams.

Danielle Wallace: That sounds like where we should be heading, but also even within that, I feel the pull, the churn of where organizations are now. They're not looking at the restructuring of our systems. Even today, when I look across all the organizations that I Work with. There's this bifurcation. I see power users, most of our organizations have that, but, but I see a lot of this majority who really aren't doing much or not doing to the goals of the organization. How do we even think about that?

Melissa Reeve: Yeah. So when you think about the transition that needs to happen from that linear organization into that hyper adaptive, value stream oriented way of the future, we're really looking at the rewiring of roles, the people, the processes and the roles. And when you think about the amount of organizations organizational change that has to happen in order to rewire your people, your processes and your roles, it requires an entirely different way of thinking about your organization and thinking about the way people learn and how that flows through the organization. How that applies to the bifurcation issue is we want to start spinning up these pieces of infrastructure or support structures to support the human beings that are being impacted by AI. And so we start to spin up what I call the AI Learning flywheel. And I want you to think about your power users. And some organizations are calling them AI Leads or AI Champions. What kind of programmatic support are we offering these people? Are we simply anointing them as AI leads and then letting them figure out how to do everything for themselves? Or are we enabling them to become true change agents? And that means saying, here's how you start to spread your knowledge to others throughout the organization. The other part of this that's missing is a dedicated group or groups of people whose main role it is to keep on top of AI. We know that AI is moving at the speed, this incredible speed, I was about to say the speed of light. It uh, actually feels faster than that to me. But if you anoint a group to keep on top of that. So I want you to think about a large enterprise and I call these groups AI AI Activation Hubs. And it's a group of one or more people and their role is to scan the landscape. Let's just say that Claude 4.6 just came out and this particular AI activation hub sits in the legal part of the business. They can take that recent model release, understand how the impact it has on the legal organization, then give that knowledge, atomize the learning. You know, maybe it's a short video, maybe it's, it's just a quick synopsis. Atomize that for the AI leads. The AI leads who are your power users. I'm seeing that aha go off for you, then can apply that to their work and then get it into the hands of the practitioners. And so all Of a sudden, you create this flywheel where you have an organization and can keep on top of the changes as they're happening.

Danielle Wallace: That's a clever way we can take as a very practical approach to being able to keep up, uh, being able to harness the power of the organization so we actually can have that value stream. In essence, what you're saying is this AI activation hub, their task would be to keep up with what's relevant as it relates to artificial intelligence, then to support those change agents, those power users, to in turn disperse that through organization and disseminate that to within their own silos. And you've spoken before about, uh, our siloed mentality being a hindrance, perhaps that also is a throughput to help break down those silos.

Melissa Reeve: That's right. And so if you imagine this network of AI activation hubs, now you have a mechanism not only for sending the information down through the organization, but across. So the legal activation hub can talk to the finance activation hub hub can talk to the HR1 and say, hey, we uncovered some really interesting use cases over here in legal. You guys might be interested. They've got their own community of practice. Your AI leads might have their own communities of practice. And now you start to see learning going up, down across the organization in a much more deliberate way. I like to say that learning actually has a distribution problem within the organization. And so what we're trying to do is we're trying to create those dedicated channels through which learning can flow with this process.

Danielle Wallace: Would that help the organizations not just keep up, but could that also help them be better poised for that future growth to be this value stream enablement?

Melissa Reeve: Yeah. And so then in the model, there is one other piece of infrastructure that I recommend organizations spin up. And this is in stage three. So this is after we've injected our workflows with AI and now we're starting to move to automation. And when you think about AI automating entire workflows, this is when jobs really transition. And I like to say jobs transition from doing the thing to building, monitoring, and maintaining the AI that does the thing. In this case, I like to use the example of the washing machine. So we used to wash things by hand in a tub. Maybe we had a wringer to wring out the extra water. And when we stopped doing that by hand and we built machines that helped us wash and dry our clothes, the job shift from like doing the thing by hand to building, monitoring and maintaining the machines that now do it. And think about all the jobs that are created in building and maintaining those appliances. And so I only introduce that because there's this narrative going on out there saying jobs are going away. And I like to offer that as a counterpoint to that narrative. To answer your question, we spin up something called the AI Impact Hub. And this is a group of people who are responsible for the upskilling, the transitions that happen as people go from doing the task to building, monitoring and maintaining the thing that does the task. Because who better to build or maintain a system around automation than somebody who's been doing it for 20 years. I really believe in my heart of hearts that that's part of the shift that will happen as we move to

Danielle Wallace: 2042 and altogether that really helps drive value. In terms of continuing on that theme, then what would you think it actually looks like to become truly AI native for those future teams then?

Melissa Reeve: Yeah. So I like to define AI native as somebody who can sense and respond in near real time. So when you think about these orchestrated value streams, and a value stream is just something that goes from concept to cash, I like to give the example of a bank when maybe you have a value stream around high net worth individuals and so you put everybody related to delivering that value in the same value stream cross functionally. And so think about them who are able to sense and respond to changes with high net worth individuals in near real time with the help of AI. And that's what I mean by AI native. Not only leveraging the infrastructure, but organizing ourselves in a way that we can be more responsive, more competitive, deliver more customer value altogether.

Danielle Wallace: It's furthering the business goals while also helping those individuals who are uh, in your model, helps those individuals in those roles be able to themselves fully develop their capabilities and deliver. Then in turn the whole ecosystem within the organization actually supports that through this ongoing, even the role of learning seems to have changed. And in support of the tasks that have been redesigned and the processes that have been redesigned.

Melissa Reeve: That's right, yeah. And when you think about AI native companies, so the companies that uh, don't have that legacy of Taylorism, don't have the legacy of silos. This is how they're organizing themselves around customer value delivery with agents embedded in altogether.

Danielle Wallace: Would you say your framework can help those with those legacy linear systems as well as help the more modern organizations also be more hyper adaptive to this?

Melissa Reeve: Yeah, I mean I think if you are starting a company today and you are already organized around value, you already have your agents embedded, you might not need the hyper adaptive model. But for everybody else, those legacy enterprises, governments, nonprofits who are trying to get from where they are today into this more AI native stance. This provides that blueprint, the five stages where you can gradually rewire your people, your processes and your roles to try and stay more competitive with the up and coming organizations.

Danielle Wallace: This is brilliant, Melissa. Uh, so much of what I've been reading about and speaking to different people on the research level speaks to the need for this. Yes, we do need to rewire what's happening and look at it from the value stream perspective and we sort of rework the linear, uh, nature of legacy Taylorism. And yet nobody has yet found the solution. Everybody says we need to do this. It will happen. And you are offering the solution, a practical framework with how to achieve that. Melissa, where can people find out more about you, your book and your work?

Melissa Reeve: Thanks, Danielle. So the book is Hyper Rewiring the Enterprise to become AI native out on most places where you would buy a book, bookstores online, et cetera. And my website is Hyperadaptive Solutions and I'm always open to conversations on LinkedIn.

Danielle Wallace: I love this. Thank you so much for your time, Melissa, and this fabulous framework that can help all of us champion our organizations into the future.

Melissa Reeve: Thanks so much for having me, Danielle.

Danielle Wallace: Thank you for being a part of the future. Subscribe now to stay current.