What leaders need to know about AI is changing quickly in 2026, as companies move from early experimentation to real business decisions. AI is already affecting workflows, customer interactions, employee routines, risk, cost, and decision-making. Leaders now have to decide where AI belongs, how it should be governed, who owns the output, and how the business will know whether the work is actually improving.
To understand what matters most, I asked a wide range of executives to share what leaders need to know about AI right now.
What Leaders Need to Know About AI
Rex Briggs, Chief AI Officer of Claritas: AI is entering what Gartner would call the “trough of disillusionment,” but leaders should be careful not to mistake the source of that disappointment. The technology is not the bottleneck. People, processes, and legacy ways of working are. Throughout history, transformative technologies have rewarded organizations willing to rethink how work gets done and punished those that simply bolted new tools onto old operating models. The Abbott-Downing Company, builder of the famous Wells Fargo stagecoach, disappeared because it remained tied to an outdated production model. Wells Fargo survived because it understood its mission was moving money, not building stagecoaches. AI presents leaders with the same choice: use it to improve existing workflows incrementally or redesign how value is created. The biggest challenge is adoption. In most organizations, innovators and early adopters embrace AI while the majority remain skeptical, disengaged, or even resistant. Training alone is rarely enough. AI is a learn-by-doing technology, and leaders cannot delegate learning it to others. They must model the behavior themselves, create time and accountability for skill development, reward those who embrace change, and make difficult decisions when individuals refuse to adapt. Resistance is natural because AI pushes experienced professionals back into beginner status, but transformation only occurs when organizations push through that discomfort. Ultimately, AI transformation is a people and process problem disguised as a technology problem. The organizations that win will not necessarily have the best AI tools. They will be the ones that maintain relentless focus on the value they deliver, redesign processes around AI rather than layering AI onto old human-centric workflows, and sustain accountability long enough to change how work gets done. The technology will continue to improve rapidly. The harder challenge, and the true leadership test, is helping people and organizations evolve alongside it.
Michael Bradshaw, former CIO of Kyndryl and Kyndryl’s Global Practice Leader for Applications, Data and AI: What leaders most need to understand is that AI is not simply a technology shift – it is a business transformation that will fundamentally change how enterprises operate. Too many organizations still treat AI as a tool or a side initiative, when in reality, it must become foundational to how work gets done. The companies that will pull ahead won’t just adopt AI. Instead, they’ll embed it into workflows, decision-making, and the fabric of their business. More importantly, they’ll recognize that the future isn’t AI replacing people. It’s people and AI working together to drive better outcomes. The biggest misconception about AI is that it’s primarily a technology challenge. It isn’t. The real challenge is organizational readiness – aligning strategy, culture, governance, and your talent to support new ways of working. Success requires more than investment in technology. It requires building trust, establishing clear guardrails, and cultivating a culture of continuous learning and innovation where employees are empowered to experiment, adapt, and develop new skills. This is also why we’re starting to see the emergence of new roles, like the Human Systems Architect at Kyndryl, focused on designing how people and AI interact in ways that actually deliver value. At its core, AI is redefining how value is created. It goes beyond productivity and requires redesigning workflows, reshaping roles, and creating new models of collaboration between people and agents. Leaders who focus on business outcomes, while continuing to prioritize their people, will turn AI into a competitive advantage. Those who treat it as just another technology deployment will fall behind and fail to realize its full impact.
Jeremy Suard, co-founder and CEO of Exodigo: The most important thing leaders need to understand about AI right now is that its greatest impact is on productivity. We are entering a period where individuals and organizations can accomplish significantly more in the same amount of time by using AI to accelerate analysis, improve decision-making, and uncover insights that would otherwise take far longer to find. At Exodigo, we see this firsthand. Our platform combines AI with advanced engineering, geophysics, and technology expertise to transform how subsurface intelligence is gathered and infrastructure projects are delivered. Instead of relying on incomplete information and making decisions with uncertainty, our clients gain a comprehensive understanding of underground conditions before construction begins. The result is faster decision-making, fewer surprises in the field, and more efficient use of time, capital, and resources. The broader lesson for leaders is that AI creates the most value when it helps people make better decisions and work more effectively. The organizations that benefit most will be those that use AI to augment expertise, reduce friction, and unlock new levels of productivity across their operations. Leaders should view AI as a growth engine. Its potential lies in enabling teams to solve more complex problems, move with greater confidence, and deliver better outcomes at scale. For our clients, that means safer projects, lower risk, and faster delivery. For leaders everywhere, it means rethinking what their organizations can achieve when human expertise is amplified by AI.
Zach Burnett, CEO of RadarFirst: Leaders need to understand that AI is not simply a technology investment. It’s an operational and governance challenge. Most conversations today focus on what AI can do, but leaders should be asking how they’ll govern it at scale. As AI becomes embedded across the enterprise, the volume of decisions, outputs, and potential incidents increases dramatically. Organizations need clear definitions of what constitutes harm, risk, or an incident, along with established processes for responding when something goes wrong. The companies that succeed with AI will be the ones that pair innovation with strong governance frameworks. Leaders also need to take a hard look at ROI. While the cost of AI models continues to decline and tokenization becomes cheaper, lower costs don’t automatically translate into greater efficiency. In fact, Jevons paradox suggests the opposite can happen. As a resource becomes more affordable and accessible, overall consumption often increases. With AI, organizations may find themselves generating more content, analyzing more data, and creating more workflows than ever before. Rather than reducing work, AI can expand the amount of work organizations choose to do. The key question for leaders isn’t whether AI will make work disappear. It’s whether their organization is prepared to manage the increased scale, complexity, and opportunities that AI creates while ensuring those investments deliver measurable business value.
Marco Matos, co-founder and CEO of Adora: AI can easily be overwhelming for leaders, so I offer two considerations. One, treat this as a moment to up-level your team’s skills, and give them the guidance and access to figure out where automation and agentic workflows actually fit. Two, AI is just a tool, so anchor it to a real business problem or outcome; using AI for the sake of AI does nothing for you. The teams that win are the ones working on tightly scoped problems with focus, not the ones chasing the technology.
Russ Reeder, founder and CEO of KeyDelta: The biggest mistake leaders make right now is treating AI as a feature instead of a foundation. AI does not fix broken execution. It compounds it. If your decisions are slow, your ownership is fuzzy, and your operating model leaks, AI just helps you do the wrong things faster. The order matters: fix operations first, then deploy AI. The second thing leaders miss is that AI has just commoditized knowledge. Everyone has instant access to expert-level answers now, so what your people know matters less than whether they can direct the tool, challenge it when it’s confidently wrong, and own the result. The premium has moved from knowledge to judgment. Hire and build for that. The companies that win the next five years won’t have the best AI strategy. They’ll have an operating model strong enough to absorb it. Heroes don’t scale, and neither does blind trust in a model. Systems and judgment do.
Adam Harris, co-founder and CEO of Cloudbeds: If leaders want to shift their businesses, they need to shift their leadership. I think about the CEOs who brought their companies through the internet in 1995. There was no roadmap for that, other than a conviction and a responsibility to their people. That’s exactly where every one of us sits right now, myself included. The best thing you can do is help your teams pull together what they know, getting your data into one place everyone can read and work with. AI only compounds when context is shared. It’ll feel slow at first, but that’s the trade: a slow start now buys speed that compounds later. Sitting in that slow stretch is itself a leadership test. The question we regularly ask ourselves isn’t “are we using AI?” It’s “am I the kind of leader my team needs to get through this?” Some days, yes. Some days I’m still figuring it out. And by the way, anyone telling you they’ve got it fully figured out is selling something.
Daniel Wagner, CEO of Rezolve AI: AI is not a project. It is a mindset. It is infrastructure, and the window to make it structural rather than cosmetic is closing faster than most boards appreciate. There is something specific I want leaders to understand about the capability question. General-purpose AI is not sufficient in high-stakes commercial environments. Ninety percent accuracy is a consumer proposition. In commerce, ninety percent accuracy is a liability. The question is not whether an organization is using AI. The question is whether they are using the right level of AI, built on the right data, calibrated for the specific context they operate in. How are they issuing tokens to employees and measuring their workforce AI usage? I’m interested in AI efficiency and productivity. That specificity is where the real work lives, and where most organizations are still operating on assumption rather than architecture. AI does not reduce the need for clarity at the top. It raises the stakes for it. The teams navigating the most significant technological shift in a generation need leaders who have decided what they believe and are prepared to act on it. Ambiguity at the top has always been corrosive, and those who don’t move fast enough risk being obsolete.
Bob Rossilli, Chief Commercial Officer of Global Business at Kedrion Biopharma: Most leaders still view AI primarily through the lens of operational efficiency. That perspective is too narrow. In healthcare, and especially in rare disease communities, AI has the potential to help organizations make meaningful improvements faster than ever before. The organizations pulling ahead are not simply adopting new tools; they are aligning AI innovation with the mission they serve. We are already seeing AI accelerate patient identification, support drug development, strengthen decision-making, and create opportunities to improve outcomes across the continuum of care. The same promise of precision, speed, and empathy that is transforming patient care should also shape how leaders think about AI adoption within their organizations. Many organizations struggle to scale AI pilots into fully integrated operating models. The challenge is rarely the technology itself; it is often a question of leadership, governance, and organizational culture and readiness. Every month spent waiting to integrate AI is a month spent learning more slowly than competitors and partners. A strong foundation starts with data, infrastructure, responsible governance , and a culture to support innovation, but leaders must also ensure that AI initiatives remain connected to the people they ultimately serve. Those who successfully scale AI will be the leaders who balance innovation with trust, responsibility, and measurable impact.
Alessio Lorusso, founder and CEO of Roboze: The most important thing leaders need to understand about AI right now is that its impact goes far beyond automating tasks or improving productivity. AI is fundamentally changing how organizations operate, make decisions, and create value. We are entering a new era where AI is no longer confined to software. Through the rise of Physical AI, intelligence is becoming embedded in machines, factories, and industrial systems, enabling them to learn, adapt, and optimize continuously. This shift is driving the emergence of Autonomous Manufacturing, production environments that can monitor themselves, respond to changing conditions, and continuously improve through AI-driven process optimization. In these systems, software, machines, materials, and production data are connected in a continuous learning loop, creating levels of speed, quality, and efficiency that were previously impossible. For leaders, this means that AI should not be viewed simply as a technology investment, but as a strategic capability that will redefine how work gets done. The most successful organizations will be those that combine human creativity, expertise, and leadership with intelligent systems capable of learning and improving in real time. The future workplace will not simply be more automated. It will be intelligent, adaptive, interconnected, and increasingly autonomous.
Mark Steffe, President and CEO of First Command: The biggest mistake leaders can make right now is treating AI as either a magic solution or an existential threat. It’s neither. What AI does is create more opportunities to meet people where they are and serve them more effectively. At First Command, we’re focused on using technology to deepen the relationships our Advisors have with military families, not replace them. The human element — the trust, the coaching, the personalized guidance — that’s irreplaceable, especially for the military community we serve. What leaders most need to understand is that AI changes the how, not the why. Your mission, your culture, your people — those don’t change because of a new tool. The leaders who will navigate this well are the ones who stay grounded in their purpose while staying curious about what’s possible. Use AI to eliminate friction. Use it to free up your people to do the work that actually matters. But never let it become a substitute for genuine human connection. That’s where the real value lives.
Andy Macdonald, CEO of Consilio: It seems to me that the role of humans in the AI race continues to be undervalued. Sure, the technology deserves the hype, but what I keep thinking about is that owning the tools isn’t the same as owning the outcome. AI moves work faster than anything we’ve seen before, but speed doesn’t transfer responsibility. When the technology produces an answer, a person still owns whether it holds up, and in high-stakes work, that ownership only gets heavier. Human judgment has to remain in the loop. No single tool decides this. What becomes most critical is how you orchestrate and govern the growing set of AI tools and outputs within a company’s workflows, bringing the technology, the data, and the people who know how to use both into one system someone is accountable for. We build AI and we run the expert work that depends on it, so I get to see this directly. That coordination is what turns AI from a faster tool into something that changes how the work actually gets done.
Seth Collins, Managing Partner of martinwolf: AI is going to have an effect on your employees and pretty much every aspect of your business, your customers’ business, and your partners’ business. Even so, don’t rush, don’t panic, and resist the urge to overreact and force-feed AI into your business. Be smart and calculating when implementing AI. It can be an enormous resource, but think about governance, compliance, security, and optimizing employee productivity, not simply reducing headcount.
Sam Kidd, co-founder and CEO of LawVu: The biggest mistake leaders can make right now is treating AI as a technology initiative rather than a business transformation. The question isn’t “Are we using AI?” It’s “Are we creating more value because of it?” Is it making our people more effective? Is it improving decisions? Is it helping us move faster? And do we actually understand what it’s costing us? One area I think many organizations are underestimating is the economics of AI. As businesses move from simple AI assistants to autonomous agents operating across multiple workflows, consumption-based costs can grow quickly. Leaders need visibility not just into what AI is doing, but whether they’re using the right models, for the right tasks, at the right cost. In some cases, AI will be the best solution. In others, traditional automation or a simple process change may be more effective. More broadly, leaders need to recognize that AI isn’t just changing out technology we use to do work, it’s changing the nature of work itself. The organizations seeing the greatest success aren’t using AI to replace people. They’re using it to remove friction, automate low-judgment work, and allow their teams to focus on creativity, problem-solving, relationship building, and strategic thinking. The leaders who thrive in this next era will be the ones who stay focused on the jobs to be done, not technology. AI is just a tool. The goal is building a more effective organization, and in my view, that’s always about outcomes.
Jeff Meredith, CEO of Chamberlain Group: The most important thing I’d tell any leader about AI right now is this: don’t let the technology lead the strategy. At CG, our approach has always been to design the experience first, then use technology to create that experience, not start with what we can do with a certain technology and work backwards from there. That distinction matters greatly when it comes to AI. A lot of companies are pushing to implement AI for the sake of AI. We’re really trying to be thoughtful about deployment. For us, that means asking: what specific experience do we want a customer or employee to have, and how can AI enable it? That question leads to very different outcomes than asking “where can we apply AI?” Here’s a concrete example. We have a camera integrated into our garage keypad. As a dad, I can see my daughter safely come home and have peace of mind. That’s the experience. AI is what makes it possible: through anomaly detection, video verification, and real-time alerts. But we didn’t start with the AI capability. We started with the emotional need. The same thinking applies inside the organization. AI will amplify whatever your people and culture already are. If your teams have clarity of purpose and are close to the customer, AI makes them faster and better. If they’re operating without a clear vision, AI will accelerate the noise. So before asking “how do we implement AI,” leaders should be asking “do our people understand what we’re trying to accomplish and why?” If the answer isn’t a clear yes, start there.
Fred Voccola, Chairman and CEO of Simpro Group: AI is no longer just a productivity tool. It is reshaping how companies operate, how decisions are made, and how work gets done. What leaders need to understand right now is that AI’s greatest value is not at the margins. It is in taking on operational heavy lifting, reducing friction, preserving institutional knowledge, and helping teams work more effectively. This is also not simply a job-replacement story. In most organizations, AI will reshape roles more than eliminate them, freeing people from repetitive tasks so they can focus on judgment, execution, and customer value. The leaders who will come out ahead are the ones who treat AI as core infrastructure, not a side experiment.
Chris Pantaenius, founder and CEO of Onspring Technologies: AI is here to stay, and at its core, it does something bigger than automation: it democratizes intelligence. The opportunity is real: do more, and do it better. If history is any guide, every time we’ve handed humanity a productivity gift, people didn’t sit back; they strived for more. AI won’t replace our work and drive; it’ll just raise the ceiling on it. So use it. Your competitors already are. The leaders who win won’t be the ones who let AI do all of their thinking. They’ll be the ones who use it to sharpen and heighten their original thoughts.
Scott Abbott, co-founder and CEO of Five Star Franchising: The biggest mistake leaders are making right now is treating AI as a technology problem when it’s actually a behavior problem. The tools are already in your building. Your people are using them — to draft communications, summarize documents, work through problems — whether you’ve sanctioned it or not. So the real question was never whether to adopt AI. It’s whether you lead that adoption intentionally or let it happen by accident. Here’s what most leaders underestimate: AI is only as good as the data underneath it and the judgment around it. It’s powerful, but it isn’t infallible: it can be confidently wrong, and the data your team feeds it can end up somewhere you never intended. The organizations that win with AI won’t be the ones that move fastest. They’ll be the ones that move fast on a foundation of clean, governed data, with a clear sense of what data goes where, who’s accountable for the output, and where a human has to stay in the loop. We tell our team plainly: AI can draft it, but you own it. Your name and the company’s name go on the work, not the model’s. Here’s what I’d leave leaders with. AI doesn’t replace judgment. It raises the premium on it. We’ve spent two decades in home services building systems that empower our owners and partners to succeed, and that principle hasn’t moved an inch: the technology is only as good as the operator behind it. The leaders who get this right won’t be the ones chasing every new tool. They’ll be the ones who give their teams the right platforms and teach them to think clearly about when to reach for AI, how to check it, and why their own discretion still matters most. Get the foundation and the behavior right, and the technology takes care of itself.
Frequently Asked Questions
Why is AI a leadership issue in 2026?
AI is a leadership issue in 2026 because it affects how companies make decisions, manage risk, serve customers, design workflows, and measure productivity. Leaders can’t treat AI as something owned only by technology teams. They have to decide where AI belongs in the business, how it should be governed, and how people will stay accountable for the outcomes it helps produce.
How should business leaders decide where to use AI?
Business leaders should decide where to use AI by starting with problems that already matter to the business. Good candidates include slow analysis, repetitive work, inconsistent decisions, fragmented knowledge, customer friction, and workflows that keep talented people stuck in low-value tasks. The goal should be a better business outcome, not simply more AI activity.
What are the biggest AI risks leaders need to manage?
The biggest AI risks leaders need to manage include unreliable outputs, weak data, security exposure, compliance issues, bias, unclear ownership, and overreliance on tools people do not fully understand. Risk grows when AI moves from experiments into daily operations. Leaders need guardrails people can follow, clear accountability, and a process for checking the work before it affects customers, employees, or business decisions.
How can leaders measure the business value of AI?
Leaders can measure the business value of AI by looking at whether it improves outcomes the company already cares about. Useful measures include time saved, quality improved, risk reduced, decisions made faster, customer experience improved, costs controlled, or employees freed up to do higher-value work. If leaders can’t connect AI to a business result, the initiative probably needs a clearer purpose.
What role should human judgment play in AI decisions?
Human judgment should remain close to any AI decision that affects people, customers, risk, strategy, or reputation. AI can process information quickly, but people still need to evaluate context, consequences, ethics, and whether the output is actually useful. Leaders should be clear about which decisions can be automated, which need review, and who owns the final call.
