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- [00:00]
A
Foreign. Welcome back to the AI to ROI podcast, the big Story edition. I'm Ray Reich, founder and CEO of BenchMarket, and joining me as always, is my co host, Peter Buchanan.
- [00:19]
B
Yep, I'm Peter Buchanan. I'm managing partner in New Plan. And Ray, it's great to be here. And I have to say that today's episode, I've been wanting to do something like this for a while and we found a market research report from one of the leading consultancies in the world that is, I think, one of the most significant research pieces on the state of AI in the enterprise.
- [00:43]
A
I agree. Peter McKinsey just published their State of Organization 2026 report. It's the second edition of what I think is becoming a landmark annual research initiative. And I really like the fact that they surveyed more than 10,000 senior executives across 16 countries, 16 industries, and I think they found some very interesting info.
- [01:04]
B
Right. Well, you know, when McKinsey calls, you know, people call back. And the, the central tension in that they identify in the report is, I think, something that every executive dealing with AI has to deal with. It's the vast majority of organizations are experimenting with AI. We've talked about that a lot. But the same, same time, that same vast majority is also reporting no meaningful impact on their bottom line. And that gap is what this episode is actually really about.
- [01:37]
A
Okay, so let's talk about the top themes we're going to discuss today. Number one, that AI transformation continues to fall short and specifically the relationship between humans and AI agents is evolving very rapidly. Second, what is the geopolitical disruption and the organizational complexity that are costing companies financially? And what does leadership need to look like in the future to navigate all of it? So hey, let's get right into it and start with the first thing. Peter.
- [02:09]
B
Yeah, the first thing here, it's the way McKinsey structures the report. And they identify three tectonic form forces that they think are just, they're not just headwinds, they are actually structural shifts that are going to affect every mid to large sized company in every industry.
- [02:32]
A
Okay, well, since you did a lot of research on this research, why don't you go ahead and walk us through those three?
- [02:38]
B
Sure. So the first is technology, specifically AI. Duh. And not just generative AI, but the emergence of agentic AI systems that execute multi step workflows. The second is economic and geopolitical fragmentation. So we have a lot more trade conflicts, we have tariff viability, we have declining trust in governments and in capitalism globally. And the third is workforce transformation. So Shifting employee expectations, demographic change. That's just a fundamental rethink of what leadership needs to do in this environment. And that's just frankly a ton of things going on at the same time.
- [03:25]
A
Yeah. And they're all interdependent. You think about AI could actually free companies from the current human based geographic constraints. You can run virtual global teams and outsource and offshore cognitive work much easier when they're agents versus humans. But at the same time, there's new complexity, particularly around how humans and AI systems will both interact and collaborate.
- [03:53]
B
Yeah, that's right. I think what really landed with me is a single finding that captures the whole moment, which is that three in four leaders say their organizations are not ready to face what's coming. And even the leaders who describe themselves as optimistic, only one in three feels prepared. So there's just, you know, they're just living under storm clouds or clouds of uncertainty here, you know, so you have
- [04:21]
A
these leaders and they see the opportunity. You have to be blind not to see the opportunity. And many believe that things are starting and heading in the right direction. But Peter, they don't feel ready. And I think this is a fear of the unknown because I talk to a lot of people who actually have worked in highly successful AI native companies like Lovable and Anthropic. But even they are feeling like they're falling behind because what they knew yesterday may have changed today. And I think it talks a lot about the magnitude of, of the challenges that we face, not just today, but heading into tomorrow.
- [05:03]
B
Right. And it sets up everything else that's in the report. These aren't technology gaps, they're leadership and organizational gaps. So let's get into the biggest, most data rich theme in the report, the AI enabled organization. Because McKinsey has done some very specific research and they have some very specific things to say about why so many AI initiatives are falling short.
- [05:29]
A
Okay, so let's just call a spade a spade here. Right. I talk to executives and SaaS companies, AI native companies, B2B, SaaS companies becoming AI first companies and AI courses, part of like 80, 90% of the conversation. And even though they're experimenting, they're learning, and a select few are actually seeing real benefits. They beyond personal productivity, the majority just can't say that the impact of AI is showing up in their financial performance yet.
- [06:04]
B
Right. And McKinsey has a clear diagnosis for why. So they say most organizations are taking a piecemeal approach to AI. They have scattered pilots, they have individual productivity improvements, they have point solutions that are Sort of fed into workflows that might do things for individual departments. But the problem is that none of it adds up. You're augmenting individuals, you're not really transforming the enterprise.
- [06:33]
A
Yeah, and I must admit I've been talking for about 18, maybe 24 months now that most of the benefit of AI and specifically generative AI tools was accruing to the individual personal productivity. And I think McKinsey says yeah, but to move beyond that, to get enterprise wide, that they're calling it double transformation. And it's where both the technical capabilities are deployed and fully leveraged and they have the organizational design for how they're going to do work across functions and across truly enterprise workflows. Hey, someone's call me right now to talk about that. So in fact they want us, they want to talk about having these end to end processes being designed or redesigned at the same time they're designing the work itself. And I call this systems thinking or you need a more holistic AI system design. And just for the listeners, you know, I was doing business process reengineering quite a while ago and there's two great books on systems thinking that I'd recommend anyone who's thinking about deploying agentic AI read. One is called Thinking in Systems by Donella Meadows. It's a great starting point. And then the fifth discipline by Peter Singe and it discusses this concept of the learning organization and what's more applicable to to agentic AI than continuous learning. So two books I recommend everyone should read.
- [08:14]
B
Right. And so the winners of those models described in those books are what McKinsey calls agentic enterprises. So there's organizations where AI agents are embedded in end to end processes, not individual tasks and the difference in outcomes is significant. So McKinsey's own research on the impact of Gen AI, the things you and I use all the time, so that most organizations that redesign entire domains, marketing, finance, operations, whatever, they see dramatically greater financial impact than those working on isolated use cases.
- [08:52]
A
Yeah, and hopefully I pronounced this right. I believe it was the company is Alliance. Is that the way you pronounce it?
- [08:58]
B
That's right, yeah. You're a good European.
- [09:01]
A
So you know, and they have a case studying there and it's a pretty good, I would say, initial illustration of what it works like in practice. So they built their own generative AI platform called Alliance GPT and they have over 60,000 active users across their underwriting department to their claims department to product design and tasks that used to take hours are being completed in minutes. Now, I do not believe that this was primarily a end to end agentic AI process story with minimal human action. Right. It was more of a human centric story about leveraging generative AI. But there's chief Human Resource officer say something that it gave me pause and I think it should give most executive pause. She said that in five years I think it might be quicker, but she said in five years, two thirds of the skills that their organization and their employees will need will be completely different than they are today. And she said it's already, basically tomorrow already.
- [10:09]
B
Right. That's not a technology prediction at all. That's a workforce transformation prediction and imperative. And it's something that McKinsey found a lot of barriers to getting these things done. And it's not budget and infrastructure, it's concerns about AI itself. So it's bias, its IP protection, it's job displacement, it's regulatory and ethical concerns and change management and organizational silos. So things that are obviously easy to solve over the weekend.
- [10:42]
A
And we're going to talk more about some of the best practices and the variables you need to have in place before you really move from concept to pilot and then a production. But one thing that the McKinsey research found was what they're calling AI pioneer organizations, the ones that have already moved decisively, experimenting and learning about AI, they're far more optimistic about the next two years than their peers. And they actually believe that their employees are being incented to, to aim higher and achieve more and that this AI kind of approach is facilitating that.
- [11:23]
B
Right. And these enablers in these AI forward organizations really move the needle because leaders champion adoption and they're very clear and disciplined about it. Dedicated teams drive it. The technology becomes easier to use every day. There are organizational choices that they fearlessly make that not technology choices. And that framing of organizational choices leads to a question of how the human workforce actually evolves alongside AI, because that's where much of the real complexity lies. So that leads us to humans and AI agents, which is a new collaboration. And I think it's where the report is. It's a little bit more nuanced, it's more honest about the gap between long term expectation and near term reality. So the leaders believe, leaders of these companies, they believe that AI capabilities in their workforce will unlock exponential productivity growth. That belief is genuinely widespread.
- [12:28]
A
It is. But when McKinsey asked them what did they expect AI to actually do in the next 2012-24 months, the picture that emerged was a lot more modest. The majority expect AI to function primarily as a support tool that co pilot helping people with routine task and basic decision making. But only about one in four. So 25% expect AI to take on truly agentic roles as acting as autonomous teammates. And I was a little surprised that they were that modest in what they expect over the next couple years.
- [13:08]
B
Right, because the people at the top of the organizations are the ones who are more conservative and a little bit more cautious about it. If you talk to young leaders who are on the fast track, they're much more optimistic about how quickly agentic AI can take hold. That suggests that as companies begin to shift their leadership demographics and these people get promoted, that the pace of expectations and also adoption are going to go up a lot faster.
- [13:38]
A
I think this is a result of experience in trying to implement transformational workforce change. And in fact, the Hitachi perspective in the report is worth reflecting on. Their chief HR officer made a point that cuts through a lot of the noise around AI and its impact on the workforce. And, and she said that scaling AI is as much of a leadership challenge as it is a technical one because it requires sustained commitment to building the skills, the trust with our employees and the execution discipline. And I've always said that I think the majority of successful AI initiatives will be more about the deployment decisions in change management than about the technology. And we're going to talk more about that later.
- [14:25]
B
But it's basically it's human skills connected to the AI. So it's judgment, it's problem solving, it's emotional intelligence, it's the ability to work with ambiguity. These become more valuable in an AI augmented world, not less. So AI might handle the execution at scale, but it fails without human context. Humans providing context, ethics, managing relationships, providing judgment that guides the strategy of how AI systems are deployed and operating.
- [15:03]
A
The research once again really encourage everyone to go read the report, but they found this isn't surprising that the demand for AI fluency has increased dramatically. In fact, it's up 7x over the next two years. So they put some real data behind it. And of course that's faster than any other skill as measured by mentioning AI competency and skills and job postings. But it also found that most of the skills employers need today are in both those processes and jobs that can be automated, but also non automated work. So I think the current use of generative AI to drive personal productivity is still going to continue to grow, but it's very different than the skills and experiences required to drive business process productivity using agentic AI.
- [15:56]
B
Right. So to get to agentic AI, the workforce challenge isn't a replacement, it's a redesign. And organizations that treat it that way, they invest in reskilling, they have hybrid human agent workflows, organization, all those sorts of things. Those are the ones that come out ahead. So let's shift to the second category of disruption McKinsey identifies, which is economic and geopolitical pressures that are reshaping how organizations are structured, what they focus on, how resilient they are.
- [16:30]
A
You know, McKinsey likes to do things in threes.
- [16:32]
B
I do, because people remember things in threes, Ray.
- [16:35]
A
That's true. Well, number one, this is a cluster of three related themes that I'm going to summarize in one phrase. It's really talking about the cost of inertia. And whether we're talking about the geopolitical exposure, the introduction of an increased organizational complexity or how resources are going to be allocated or reallocated, rigid organizations that aren't pliable and flexible are going to pay for it.
- [17:04]
B
Yeah. So let's start with geopolitics. So McKinsey found that three in four leaders report a very notable impact from geopolitical uncertainty on their organizations. But the interesting finding isn't that it's disruptive because obviously it's going to be. The interesting finding is what differentiates winners from losers when you have this geopolitical disruption.
- [17:30]
A
Yeah. You know, one of the things, it's the Tony story I believe that I think about in having a adaptable, flexible workforce and quite frankly, process. Tony's is a German toy company and its CEO was very candid to report that they'd been manufacturing all their hardware exclusively in China. And then last year on Liberation Day, when, you know, US announced all their tariffs, they launched the same day they launched a production facility in Vietnam. And that enabled them to quickly shift all their US based products and inventory from Vietnam versus China at far lower tariff rates. And they called it where luck meets preparation. But it wasn't just luck. It was organizational preparedness. And I kind of view being ready for the promise of agentic AI is very similar. You may not get all the benefit today, but you've got to invest and prepare for it to take advantage of that opportunity in the future for sure.
- [18:33]
B
And it's exactly what McKinsey is advocating for. It's not just resilience in terms of surviving shocks. It's also what they call bouncing forward. So that means building structures that turn disruption into competitive advantages. So companies that have diversified their supply chains, their geographic footprints, and they've got very flexible sourcing strategies and they have great processes and procedures and data about third party risk. Those companies are going to survive a big tariff shock in a lot stronger position than the peers around them.
- [19:13]
A
Yeah, and then there's this. You know, we've been talking about increased efficiency, increasing productivity, and. And there was an insight in a report that I think is really important for executives to think about their future transformation. And that is that two thirds of the executives in the survey said their organizations are overly complex and inefficient. Now, am I surprised by that? No, not really, if the executives are being very honest. But what is surprising is McKinsey's diagnosis of why traditional fixes aren't working.
- [19:47]
B
Right. So companies are very used to structural redesigns. Oh, we better flatten our hierarchy. We have to cut costs, we have to get rid of waste. These have been go to productivity levers for years. But now these companies, they know how to do those. Everybody knows how to do these things. So you get diversifying returns and so you can address the org chart. But if you don't touch the actual processes when you make those changes, you're not really getting an unlock. The unlock is reshaping how work flows across your functions, which of course is what agentic AI is designed to do. Eliminate duplication, synchronize information, streamline decisions, structure supports. That doesn't lead. But since everybody knows how to do this, if you want to get competitive advantage, agentic AI is definitely the next thing.
- [20:45]
A
Okay. Hey, Peter.
- [20:46]
B
Yeah.
- [20:47]
A
I'm going to put a little bit of my own thumbprint here on this. And if there's one thing I'd love for our listeners to take away from his podcast, this is it. And it's a what is old is new again. So I've been part of many different business process redesigns. We used to call it business process reengineering. And this business process redesign is critical to gaining the maximum benefit from AI. And here's five key variables to ensure that agentic AI success. And this is beyond what McKenzie said. Right. You need to have well defined redesigned AI centric workflows with clear inputs and outputs. And you want to start with constrained kind of smaller, highly measurable workflows and processes. So land it, nail it, and then expand it. And what I'm finding is starting with a vendor platform at the foundation, rather than trying to build it yourself is probably a good place to start because you're getting the collective benefit and wisdom from all their customers. And don't forget to start with that critical component of data hygiene and even field level data identification for every task and every action is within that process that you're redesigning. Governance is so important. Build it up front, don't add it on later. And right up front, identify who, where human oversight is needed and even human reinforcement for those edge cases that you've defined that upfront. And then this is the AI at ROI podcast. So one of the things that I also say is I've seen having an ambiguous measurable success criteria well defined even before the first task or first stage of the process deployed, highly critical.
- [22:36]
B
Oh for sure. Leaders need the vision to go through that innovation that you just described. They need to prioritize, they need to divest things that they don't need to do it anymore. The courage to divest that then leads to future focus is really important. The AI transformation challenge, the geopolitical complexity, the productivity imperative, all that eventually lands on the people and leaders. Next, let's talk about the performance and leadership themes that McKinsey surfaces.
- [23:11]
A
Yeah, this goes far beyond the impact of AI. This is truly about how to optimize companies performance. I think it's underappreciated, especially in today's AI centric executive conversations. McKinsey actually distinguishes those organizations that focus on performance. So I'm going to increase my productivity and performance versus those that focus on both the people aspect and performance simultaneously. And that difference in outcomes is stark. And I remember this was always a key part of any change management discipline we implemented in a business process reengineering program. It was the people in the process performance that we're looking at, not just one.
- [24:02]
B
Right. So organizations that invest equally in both. So McKinsey calls this PNP organizations, they are four times more likely to maintain top tier financial performance over a long period of time. They have half the earnings volatility of their peers, their revenue growth is twice as fast and than companies that just focus on performance. So those pesky people, all the people that work there, you can't underestimate their importance.
- [24:34]
A
Yeah. And another reason this is so important about the people. Employees are honestly scared about their jobs and what agentic AI specifically can do to possibly eliminate their job. So bringing in that human to how their job, more importantly the outcomes that they're responsible to help generate in the processes that they're engaged in. How can you define human involvement in AI agent development, oversight training and even management? Because what a lot of people aren't talking about there is going to be AI agent management required.
- [25:16]
B
Oh absolutely. So that which leads to the subject motivation, what motivates employees. So only 20% of leaders in McKinsey's survey believe that non financial rewards, meaningly boost employee performance. Which means that 80% are essentially leaving one of the most powerful motivational levers on the table. And that's, you know, you and I both work for ge. We were big believers in the Jack Welch version of ge. We drank all the Kool Aid. It was really delicious Kool Aid. And that purpose, autonomy, recognition and growth, they're not soft benefits, they're actually performance drivers.
- [26:01]
A
And this research report actually backed that up. I think what they found was that organizations that give people regular developmental conversations, how they link the individual's individual goals to the organizational priorities, that that builds cultures where employees feel they belong, even helping to develop their AI first organizational capability. And those organizations that make people feel like they belong and are critical significantly outperform their competitions on engagement, on retention, and most importantly to their financial performance.
- [26:42]
B
Right. So McKinsey calls this an inside out model. So in a world of AI disruption, of geopolitical complexity, workforce transformation, the things we've been talking about, the precondition for leading others yourself is self awareness and reflection, which means that you have to acknowledge which you don't know. You can't know everything. There's a lot of change going on. You have to figure it out as a team.
- [27:11]
A
Yeah. And there's a data point in the report that I think crystallizes that. It's that leaders who self identify as more reflective, who pause on a regular basis to examine their own assumptions and how they're showing up, are significantly more confident in their organization's ability to adapt quickly to change than their less reflective peers. Reflection isn't a soft skill. It really seems to be a strategic capability to enable companies to take advantage of all the transformation and opportunity in front of them.
- [27:43]
B
Right. So Schneider Electric's chief human resource officer was quoted in the report, she said, great leadership starts with that self awareness. So in a world where everything is changing at an increasingly rapid pace, that inner steadiness is what leads to through uncertainty. It's highly valued. Let's bring it all together because McKinsey closes the report, what I think is an important framing, which is the idea of business as change. Change is constant. So business as change.
- [28:19]
A
Yeah, I think that's the meta insight from the entire report. It's the one that requires the biggest mind shift for most organization transformation used to be something you did as a project or you did it periodically. Right. That program major Transformation program had a defined beginning and end, but that model's over. Especially when you're moving at the speed of artificial intelligence.
- [28:45]
B
Right. So McKinsey's describing business as change, as a permanent operating condition. So it's the ability to keep changing, to build change as an organization, as part of the muscle of your organization. That's what separates your organization from your peers. Because your peers won't do that and you will.
- [29:07]
A
Yeah. And in today's AI world I think there's four key implications that we need to be kind of thinking about. First, change is continuous. It's not episodic. You need to speed or be able to change at the speed of light, but in a thoughtful way. Second, that people, behavior, culture, they still remain the central variable. Technology can disrupt and improve, but the response is always human. Your customers, your vendors, your employees will never going to be 100% without humans. Third, AI itself changes how you manage change. You can't just roll it out like any other tool. You have to involve people to co create a new way of working, not just automating what they're doing today. And fourth, you're going to need clarity about where you're heading before you start moving. And I'm going to add the fifth, you need to have a North Star. It has to be defined and you're going to have to define how you're going to measure your progress towards reaching that North Star. Or like our astronauts just did, the other side of the moon.
- [30:14]
B
Right. So the McDonald's global chief people officer said she had a really insightful comment. She said, well, while there are short term changes to deliver specific outcomes, sustainable transformation happens over a long period of time. That means you've got to have a longer term view, which often goes against of course what the public markets want. So making things even more difficult. And you have to continue to reinforce the behaviors you expect. Drive accountability with leaders.
- [30:49]
A
Yeah, and she actually said the challenge is, and I hear this from other executives all the time, it's actually harder to drive transformation when you're doing well. Hey, there's no burning platform. So you have to create the urgency and the conviction to transform your business before crisis in a competition forces it on you. The organization is doing this proactively are the ones that are building that durable, consistent and continuous advantage.
- [31:17]
B
Right. So Ray, if I had to distill the entire McKinsey report into a single takeaway, that for executives listening right now, it'd be this. The gap between AI activity and AI impact is an organizational problem, not a technology problem. The tools exist and they are getting better every month. The models exist. So what's most important that most organizations are still missing is the willingness to redesign around the technologies. That's structures, workflows, skills, leadership approach. The redesign is the work that will make you successful and it can't be delegated to a technology team or managed as a side desk project. It's got to be owned at the top and it's got to be positively delivered.
- [32:09]
A
Yeah. And I talk to organizations like Anthropic Lovable and what's interesting is, and this is reflective of all organizations, the ones who are getting it right are the ones that say even though I'm doing well today, I've got to sustain and continue to improve because the market's moving fast, even though I might be in a leadership position today. And they're investing in their people with the same intensity that they're investing in the next generation of their technology.
- [32:39]
B
Right. Well, I think that's about it for us for today. A lot of organizational change tied in with AI there and a lot of discussion of businesses change, which I think is going to end up in many, many business textbooks over the next five years. So thanks for joining us today and any final thoughts.
- [32:59]
A
Ray I would recommend everyone to go search and read McKinsey State of Organizations 2026. And once again, thank you everyone for joining us. Hey, if you love or like the conversations, go ahead and subscribe to the AI ROI podcast and please give us that five star recommendation. We surely appreciate it. And reach out to us if you have a topic you'd like to see us discuss. Bye bye everyone.
- [33:24]
B
Bye.