In November 2025, McKinsey reported that 88 percent of organizations now use AI regularly in at least one business function, up from 78 percent a year earlier. The question for senior leaders has shifted from whether to adopt AI to how to lead an organization that runs on it.
The most useful finding in the research is about people, not models. The companies capturing the most value share a set of leadership habits, and nearly all of them can be learned.
Adoption is broad, and the frontier is moving fast
McKinsey's latest global survey drew on 1,993 participants across 105 countries and was fielded in mid-2025. It shows how quickly the tools have spread. Agentic AI, meaning systems that can plan and carry out multistep tasks, has moved from concept to practice in a short time.
- 88 percent of respondents say their organization uses AI regularly in at least one function.
- 23 percent say their organization is already scaling an agentic AI system somewhere in the business.
- Another 39 percent are experimenting with agents, so 62 percent are at least exploring them.
- 64 percent say AI has improved innovation, the most widely reported benefit in the survey.
Those numbers describe a large, energetic middle. The more instructive story sits at the top.
A small group of high performers is setting the pace
McKinsey identifies about 6 percent of respondents as AI high performers: organizations that attribute more than 5 percent of EBIT to AI and report significant value from it. They are not simply buying more software. They lead differently.
Three practices stand out. Senior leaders at high performers are about three times as likely as their peers to strongly agree that they demonstrate ownership of AI initiatives. About 55 percent of high performers have fundamentally redesigned workflows, compared with roughly 20 percent of other respondents. And more than one-third devote over 20 percent of their digital budgets to AI.
High performers also aim higher. They are more likely to set growth and innovation objectives for AI alongside efficiency goals, treating the technology as a way to build new value rather than only to streamline existing work.
Leadership ownership is the strongest signal
The same pattern appeared in McKinsey's March 2025 edition of the survey. Of 25 organizational attributes tested, CEO oversight of AI governance showed the strongest correlation with reported bottom-line impact from generative AI, particularly at larger companies. McKinsey notes that this is an association rather than proof of cause, but the direction is clear.
Ownership looks practical in daily life. It means the chief executive sponsors a short list of priority use cases, reviews progress in the same forum as other strategic initiatives and uses the tools personally. In the March 2025 survey, senior leaders actively driving adoption, including role-modeling their own use of generative AI, was one of the practices linked to stronger results.
Visible personal use sets a stronger example than any memo. When a leadership team shares what it learned from drafting a board update or pressure-testing a forecast with an AI assistant, it gives everyone else permission to experiment.
Turning ambition into new value
When 64 percent of respondents say AI has improved innovation, it suggests the technology is already widening the range of ideas that teams can explore, test and bring to market.
High performers act on this. Because they pair efficiency with growth objectives, their AI agendas tend to include new products, new services and new ways to serve customers. That orientation keeps the program energizing for employees, since the work is about building something new rather than only doing familiar tasks faster.
Agents extend the opportunity further. With 23 percent of organizations already scaling an agentic system, leaders are beginning to design processes in which software handles well-defined multistep tasks while people focus on judgment, relationships and creative problem solving.
Questions for your next leadership offsite
- Where would a redesigned workflow create the most value for our customers?
- Which two or three metrics will tell us our AI program is working?
- Who on the leadership team owns adoption, and how will we report progress?
- What growth objective belongs on our AI agenda this year?
Working through those questions together usually produces a short, shared plan. For many executive teams, that shared plan is the most valuable output of the whole exercise.
Five habits for building AI fluency at the top
Executives who are building fluency fastest tend to follow a similar routine. None of it requires technical training. It requires curiosity and a regular cadence.
- Use the tools weekly on real work. Draft, summarize, analyze and brainstorm with an AI assistant on live priorities rather than practice examples.
- Redesign one workflow end to end. McKinsey's data links workflow redesign closely to impact. Pick one process, map it and rebuild it with AI at the center.
- Track a few clear metrics. In the March 2025 survey, tracking well-defined KPIs for generative AI had the strongest link to EBIT impact among 12 adoption practices.
- Invest in role-based learning. Training tailored to what a sales leader, a controller or an engineer actually does lands faster than generic courses.
- Set an ambitious goal. Pair efficiency targets with at least one growth or innovation objective so the program stays focused on new value.
Building the organization around the opportunity
The companies moving fastest treat AI adoption as a leadership program with a roadmap. McKinsey found that larger organizations are more than twice as likely as smaller ones to have clearly defined adoption roadmaps and dedicated teams driving adoption. Smaller firms can borrow the same structure on a lighter scale: one accountable executive, a short roadmap and a monthly review.
Talent strategy is evolving too. Many respondents in the March 2025 survey said their organizations had reskilled part of their workforce over the prior year and expected to do more over the next three years. Executives who frame this as career growth for their people tend to find enthusiastic early adopters in every function.
Peer exchange accelerates all of it. Leaders who compare notes with counterparts in other industries quickly see which use cases are delivering, which governance models are working and how others are bringing their teams along.
Where to start this quarter
The research points to an encouraging conclusion: the advantage in AI comes from leadership habits that any executive team can adopt. The tools are widely available. The differentiator is how personally and consistently the top team engages.
- Block one hour a week to use AI on your own priorities and share what you learn.
- Choose one workflow to redesign this quarter and assign a single owner.
- Set two or three metrics and review them alongside your other strategic goals.
- Add one growth objective to your AI agenda so the effort builds new value.
The organizations pulling ahead started with leaders who chose to learn in public. That opportunity is open to every executive team.
Sources
- McKinsey & Company, "The state of AI in 2025" (McKinsey Global Survey on AI), November 2025.
- McKinsey & Company, "The state of AI: How organizations are rewiring to capture value," March 12, 2025.