# Leadership Insight: The Real Danger for Your Right Now Is Making a 2027 Decision With a 2017 Mental Model
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Here's what I've come to realize with my last set of keynotes: the next great leadership crisis isn't simply resistance to change. It's the growing inability to comprehend how profoundly the world around us has changed. The simple fact is that the assumptions that worked a decade ago are being tested by a dramatically different world. Over the last several months, I've found myself in some fascinating conversations with senior executives and leadership teams across remarkably different industries. The details varied enormously. But I kept coming back to the same question: what happens when the world changes faster than the ability of a leadership team to understand what's happening? In a private briefing for the senior leadership team of iA Financial Group – Automotive, I explored what happens to warranty and protection services when the automobile itself is being reinvented. At Toronto Hydro, the conversation involved an electricity system being reshaped by electrification, AI, battery storage, and distributed energy. In Chicago, at the ECIA Executive Conference, executives were confronting multiple technological and industrial supercycles at once. And in San Diego, at the ISACA + IIA GRC Conference, I challenged risk and governance professionals to consider the consequences of threats that can move at machine speed. Four different rooms. Four very different sets of business decisions. One recurring problem. The real danger is making a 2027 decision with a 2017 mental model. I've spent more than three decades studying the future and challenging organizations to think about the forces reshaping their world. For much of that time, the familiar leadership question was whether people were willing to change. Today, I'm increasingly convinced the more fundamental question is whether we fully grasp how much the underlying conditions have already changed. It's not simply about moving faster Business leaders have been told for decades that they need to accelerate. Move faster. Innovate faster. Get closer to the customer. Shorten decision cycles. All useful advice, and much of it has been central to my own work. But there's a problem with assuming that speed alone is the answer. You can make a decision very quickly and still make the wrong decision, particularly when the assumptions beneath it no longer hold. A fast-moving organization with an outdated understanding of its industry can simply become very efficient at heading in the wrong direction. Think about the difference between 2017 and the world we're entering in 2027. In 2017, today's generation of generative AI and autonomous software agents had yet to become an everyday executive concern. Electrification was gathering momentum, but many automotive business models were still organized overwhelmingly around mechanical vehicles. For many utilities, distributed energy and battery storage were emerging issues rather than central operating considerations. And the idea that AI might industrialize cyberattacks, decisions, and workflows at scale was still largely a scenario for the future. Ten years isn't a long time for an organization with infrastructure, contracts, workforce planning, and capital investments measured in decades. Yet in several industries, ten years have been enough to challenge some of the most fundamental assumptions upon which those long-term decisions were based. The comprehension gap: an editorial illustration of assumptions that no longer fit the world they're intended to explain. Categories are illustrative, not a quantitative comparison. When the product itself is being reinvented That challenge came into sharp focus during my work with iA Financial Group’s automotive leadership team. We were looking not merely at new vehicle technologies, but at what those technologies might mean for a business built around warranty, protection, service, and risk. Historically, many of the industry's assumptions were grounded in mechanical wear, physical repair, dealership relationships, and past claims experience. But what happens when vehicles are increasingly controlled by software? When batteries introduce different failure modes and repair economics? When real-time diagnostics make it possible to anticipate failures before they happen? Or when manufacturers gain more influence over the ongoing relationship with the driver? These are not simply additional trends to include in the annual strategy review. They challenge the underlying definition of the product, the economics of the business and the data needed to manage risk. A conventional warranty model cannot be assumed to remain adequate in a software-defined automotive world. A customized strategic foresight briefing explored the 2025–2040 future of automotive protection services. Read the case study. When infrastructure outlives the assumptions behind it The challenge at Toronto Hydro was different, but the underlying issue was remarkably similar. Electricity networks are physical systems that must operate safely and reliably while meeting long-term demand. Decisions about equipment, capacity, and operating systems have consequences that last for years, sometimes decades. Now consider the collision of changes confronting utility leaders. Electrification is changing the scale and shape of demand. Battery storage creates new forms of flexibility. Distributed energy challenges traditional one-way assumptions about how electricity moves. AI can help predict, coordinate, and optimize operations, while simultaneously creating significant new sources of electricity demand. None of this means that the foundations of utility engineering should be discarded. Quite the opposite. Safety, reliability, and hard-won operational expertise become even more important. But a leadership team cannot fully prepare for the next decade by assuming that the grid of tomorrow will behave exactly like the grid of yesterday. I made a point in that keynote that is worth repeating: good leaders don't manufacture certainty. They create clarity even when certainty isn't available. That matters profoundly when the decisions are consequential, and the future is changing underneath them. The Toronto Hydro leadership keynote connected energy-system change with the practical challenge of leading through uncertainty. Read the case study. When the disruption comes from outside your industry At the Electronic Components Industry Association executive conference in Chicago, the comprehension challenge took another form. It involved leaders trying to interpret an electronics market increasingly shaped by things happening far outside conventional product categories. AI creates demand for chips and computing capacity, of course. But it also creates a need for power generation, transmission, cooling, optical networking, and specialized materials. Robotics expands the need for sensors, motors, controllers, and power systems. Defence priorities, supply-chain localization, and geopolitical volatility can reshape sourcing and investment decisions. The result is an industry influenced by multiple, overlapping waves of change that don't follow the same timetable. This is why I spend so much time researching not just an audience's own sector, but the adjacent industries that are changing its future. An electronics executive cannot understand tomorrow's demand merely by extending yesterday's component sales trend. A utility executive can't think about future load without considering AI infrastructure. An automotive executive can't forecast protection products without understanding software and data. In other words, the next disruption often arrives from a direction that isn't represented on the organizational chart. At ECIA, the keynote examined colliding technological supercycles and the implications for the authorized electronics channel. Read the case study. When risk moves faster than the governance designed to contain it This same problem becomes even more visible when we turn to governance, risk, and control. At the ISACA + IIA GRC Conference, my central message was the Acceleration Gap: the widening distance between the speed of emerging threats and the ability of organizations to assess, govern, and respond to them. Conventional governance processes remain necessary. But their cadence can become dangerously mismatched with the systems they're intended to oversee. An AI agent can complete sequences of actions faster than a committee can convene. An attacker can use automation to probe weaknesses far more rapidly than a traditional review cycle can document them. A highly interconnected software ecosystem can turn a flaw in one component into consequences for many organizations. My point was never that governance should disappear. It was that governance has to evolve to account for a world of continuous change, autonomous systems, and risks that can cascade across organizational boundaries. You cannot adequately govern machine-speed exposure if you misunderstand how the systems themselves now behave. The GRC closing keynote explored what happens when technology and risk move faster than traditional governance cycles. Read the case study. Even the organizations building AI face a comprehension challenge At Deloitte University’s Chief Data Analytics Officer Summit, I explored another form of the problem: the transition from experimentation with AI to the industrialization of intelligence. A company may have dozens or hundreds of promising AI demonstrations. That doesn't mean it understands what happens when intelligence becomes embedded in production workflows, customer interactions, risk decisions, and operational accountability. Scaling AI is not simply a software procurement exercise. It requires new thinking about people, processes, trust, skills, and organizational design. That's the comprehension challenge in a nutshell. Leaders can be very enthusiastic about a technology and still underestimate what it requires them to rethink. A specialized leadership keynote considered how AI moves from isolated experimentation toward enterprise-scale operations. Read the case study. Like I said - different industries, different executive audiences, a recurring challenge: understanding how the underlying rules are changing. From the Acceleration Gap to the Comprehension Gap I've long used the phrase Acceleration Gap to describe the growing distance between how quickly the world changes and how quickly an organization can respond. But these recent experiences suggest another gap that deserves just as much attention. I call it the Comprehension Gap: the distance between the reality of the world in which we now operate and the assumptions we use to interpret it. It's possible to suffer from both gaps at once. You may recognize that change is accelerating, yet fail to understand which parts of your business model are becoming obsolete. You may recognize that AI is powerful yet fail to understand how it changes liability, workflow, or infrastructure. You may see a competitor moving quickly, but overlook the possibility that the next competitor will emerge from an entirely different industry. Sometimes, accumulated expertise itself creates a challenge. Decades of experience are enormously valuable, particularly when leaders remain curious and willing to test what they know. But the same experience can make yesterday's assumptions feel permanent, even when the external evidence is telling a different story. You cannot respond effectively to a future you haven't learned how to understand. What should leaders do about it? In my keynotes, the research always begins with the specific reality of the audience. A utility needs a very different examination of the future than an insurance company or an electronics distributor. The underlying patterns may be similar, but the implications and the decisions certainly aren't. That's why the work involves understanding the industry, its customers, its technological dependencies and the assumptions driving its strategy. But regardless of the industry, I've come to believe that the starting point is often the same: leaders must become more deliberate about examining what they think they know. Audit the assumptions. Which facts about your industry are so familiar that nobody thinks to challenge them? Look beyond your industry. What development elsewhere could suddenly redefine your costs, customers, competitors, or operating model? Shorten the learning cycle. Don't wait for an annual strategy session to discover that a critical assumption has expired. Experiment to learn. Use small, disciplined tests to discover what is changing before placing enormous bets. Lead with clarity, not artificial certainty. Give people a credible framework for making decisions, even when every detail of the future remains unknown. Those practices are not a replacement for strategy. They are what allow strategy to remain relevant. It's time to update the mental model There's a reason these conversations continue to fascinate me after 33 years of working with organizations around the world. Each industry has its own language, its own history, its own institutional wisdom, and its own set of constraints. But across those differences, the essential leadership task remains surprisingly consistent: recognize what is changing, understand what it means, and have the courage to act. As we look toward 2027, leaders will face decisions involving capital, technology, people, risk, and long-term opportunity. Those decisions deserve more than a fresh coat of paint on an old strategy. They require the willingness to challenge the mental models that made yesterday's success possible. Because the greatest danger isn't simply that the future will arrive faster than expected. It's that we'll be making tomorrow's decisions with yesterday's understanding of the world. And that's a risk we can do something about, starting now. Explore the related keynote case studies: iA Financial Group – Automotive, Toronto Hydro, ECIA Executive Conference, ISACA + IIA GRC Conference, Deloitte University. For other examples across sectors, visit the keynote case study archive.

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Source: https://jimcarroll.com/2026/10/leadership-insight-the-real-danger-for-your-right-now-is-making-a-2027-decision-with-a-2017-mental-model/