It’s a central rule of AI transformation: a firm’s strategy to use technology at scale is about adoption, and adoption is about people.
“Adoption means that employees are excited to embrace technology and redefine their work to make work work better for everyone,” says Debbie Lovich, a BCG managing director and senior partner. “And by everyone, I mean productivity for shareholders, innovation and delight or customers, and most importantly for adoption, more enjoyable and less toilful work for employees.”
This doesn’t happen on its own, of course. AI adoption requires a top-to-bottom transformation of the way an organization works. And the CEO is perhaps the most pivotal figure in that effort.
The CEO is perhaps the most pivotal figure in a company’s adoption of AI.
“The CEO must set the narrative that this isn’t just AI for AI’s sake,” says Julie Bedard, a BCG managing director and partner. “It’s about redefining work to create meaningful impact.”
How executives design pilots and adoption programs for scale is as important as giving employees the freedom to grow familiar with AI. The CEO’s guidance of a well-conceived adoption strategy will pay off both today and down the road—especially as emerging technologies like AI agents bring more decisive capabilities to every competitor, whether an established firm or an AI-first startup.
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What Drives—or Derails—AI Adoption
One in three companies are committing at least $25 million to AI. Yet deep pockets alone don’t guarantee adoption; even in a traditionally capital-rich industry like insurance, for example, overall AI maturity hasn’t moved beyond the experimental stage, according to BCG research.
“This is the most important thing for CEOs to remember: if people aren’t adopting AI, you’re not getting any impact,” says Matt Kropp, chief technology officer of BCG X and a managing director and senior partner at the firm.
Adoption can even fall short in a highly technical field, where a CEO might expect the population to have an affinity for new technology—for example, roughly 70% of software developers aren’t using GenAI.
Yet adoption will only become more instrumental to success; a company that’s fully engaged with AI now will be better poised to compete with fast-moving, AI-first newcomers in the future. “In five years, your competitors won’t be other companies adapting AI to fit their needs—they’ll be companies built with an AI-first approach from the ground up,” says Kropp.
In five years, your competitors won’t be other companies adapting AI to fit their needs—they’ll be companies built with an AI-first approach from the ground up. — Matthew Kropp
Meanwhile, missteps are happening today. “The mistake executives sometimes make is to say, ‘I have the technology, I have the tools,’” says BCG X partner Alex Duerloo. “‘And I gave the tools to the organization, so surely now they will use them.’ But access is only the starting point of a much longer journey.”
Employees’ attitudes toward AI—excitement for some, resistance for many others—can be the fuel for adoption or a barrier. It’s a vital task for CEOs to recognize the complex ways employees react to a new and rapidly changing technology.
Get Ready to Scale
Only one in four businesses are scaling AI. The rest struggle because they spread their efforts too thin, testing models and workflows across the company in fragmented pilots. Too often, siloed teams work with no system to share lessons with other test teams, so promising pilots wither before delivering results.
Designing for adoption at scale—which holds cocreation as a guiding principle—allows CEOs to avoid these mistakes and launch higher-potential projects.
As Lovich explains, firms can build momentum by bringing people from different teams to collaborate on pilots. When a cocreated project begins to show impact and it’s time to scale it across the function, it’s easy for project members to return to their teams and share what they’ve learned, helping AI take root across the organization.
“The employees who were part of the AI pilot will advocate for the transformation, act as internal influencers and coaches, and lead by example,” Lovich explains. “This is why I call it design for adoption—because if your best employees cocreate from the beginning, adoption should happen naturally.”
Employees are more likely to adopt AI when the technology reduces toil in their daily work.
AI adoption champions are key to getting this right. “Pick your best people who are not just super talented, but they're really looked up to by their peers,” says Lovich. These champions help bridge the gap between leadership’s vision and employees’ day-to-day experience.
This employee-centric approach also drives value creation. “Imagine how much value you’d create if every person on your team could be as motivated, impactful, and productive as your best ‘anchor’ employees,” Lovich says. “Now multiply that by every team in your whole company. The value creation opportunity is immense.”
Employees are also more likely to adopt AI when the technology enhances joy and reduces toil in their daily work. In one BCG pilot, participants saved up to two hours a week by using AI-driven calendar tools, with 79% reporting that it made the task of scheduling more enjoyable, 86% reporting higher effectiveness, and 92% saying they would continue using the tool.
“Of course, what feels like toil to one person might feel like joy to another,” says Lovich. So CEOs must understand their employees as well as they understand their customers.
Lovich’s research found that even among employees holding the same role, perspectives on AI vary widely. Staff members who are looking for advancement or job growth may see AI as a career steppingstone, while those who find pride in their existing jobs may see AI as a threat. Tailoring adoption strategies to these different segments is a necessary step for CEOs.
AI Adoption is a Human Challenge
“Adoption of GenAI is almost entirely about the psychological barriers—things like fear, habit, or just knowing what’s possible with the technology,” says Kropp.
It’s hard for anyone to give up proven, comfortable ways of doing things—especially at work, where routines are deeply ingrained. We can even be protective about mundane tasks and busywork, points out Kropp, and having to change trusted habits just to use an unfamiliar technology can be a source of worry.
Change can also roil a person’s sense of competence, pride, even their job security. “It’s an emotional process to bring employees through: ‘I became a software developer because I like to code, and it's really hard for me to reimagine my identity if coding looks different in the future,’” says Bedard. “It calls for some reassurance from leadership about how AI will be a positive part of the employee’s future.”
Companies that don’t get past these emotional barriers can come up against an “organ rejection” effect, says Lovich, where AI is technically deployed but culturally refused.
Leaders who frame and promote AI purely as a productivity tool are essentially telling their employees not to engage with it. — Deborah Lovich
But when CEOs approach AI with a goal of making work better for employees (as well as shareholders and customers), a much more conducive setting for adoption takes shape. “If I as an employee know that AI is being introduced to elevate my enjoyment of work, it makes me feel more valued and supported in engaging the technology—as well as cared for and respected in the organization,” says Lovich.
Workers feel heard and motivated to connect AI to their objectives when the organization chooses an employee-centric AI strategy. “Leaders who frame and promote AI purely as a productivity tool are essentially telling their employees not to engage with it,” Lovich explains.
“Productivity should be a goal, but the starting point should be ‘How do we delight our customers and make employees see how AI can empower them to make their work more enjoyable, rewarding, and meaningful?’”
Companies often find answers to those questions by giving employees permission and time to explore how AI fits into their work—something the CEO is uniquely positioned to grant.
A recent survey confirms the connection between adoption and mindset. BCG research found that among consultants who regularly use GenAI for work, 82% say it increases their confidence and improves collaboration with coworkers, compared to only 67% among those who don’t use it weekly. Employees adopt AI when they feel supported and see its value—so it’s up to leaders to design adoption strategies that make that possible.
How CEOs Can Lead AI Adoption at Scale
The ambition behind the company’s AI strategy, the messaging to employees—it all falls on the CEO’s desk. “CEOs have to set the tone from the top, because the companies that are doing better are the ones where the CEO has said AI is a priority,” says Kropp. “These leaders are public about AI; they’re consistently behind it; they're setting ambitious targets.”
Executives can focus on key adoption strategies defined by the 10–20–70 rule: while tech and data make up 10% and 20% of the effort, the remaining 70% of the focus should be on people and processes. Here’s how CEOs can make that happen.
Model AI adoption at the top. CEOs of businesses that successfully scale AI are vocal and visible about the importance of adopting the technology. During company meetings, say, a leader may praise front-running teams or advocates of new ways of working. Celebrating real moments of progress with AI is key to making the technology stick. “Don’t celebrate one-offs like shiny AI demos. Reward real, scaled impact,” says Duerloo.
Prudent CEOs and their teams also take the time to experiment with AI on their own—for instance, while planning a meeting agenda or organizing ideas for a speech. Talking about these experiences with employees helps normalize AI’s new role in daily work. When the executive team walks the talk with AI, adoption follows.
Let people experiment with GenAI, too. “One of the reasons people are frustrated is they are given zero capacity to try out the technology,” says Bedard. “But if you get permission and some capacity to learn, you will actually unlock more creativity around the process.”
Upskill managers to drive adoption. Along with the chief information officer and chief human resources officer, some of the CEO’s greatest allies in promoting adoption are middle and frontline managers, who can help employees see the purpose of the transformation.
These managers are well-positioned to address the different adoption mindsets on the team members and personalize how the technology will help individual employees.
To address low adoption of newly deployed GenAI tools, a global Fortune 500 company partnered with BCG U to upskill thousands of middle managers. The training focused not only on the fundamentals of GenAI but also on how to apply the tools effectively in day-to-day workflows.
Middle managers played a critical role in driving adoption, tailoring their approach to different employee mindsets and ensuring the technology was integrated in a way that resonated with their teams. As a result, the company saw an 89% increase in usage, significantly improving the overall return on investment.
Cocreate adoption with employees. AI adoption is strongest when employees feel involved in the process. Setting aside time for employees to explore AI—whether through pilot programs, team workshops, or internal AI communities—helps them find the points where the technology works best for their roles and objectives.
When employees can share what they’ve learned with AI, engagement rises—and adoption is more likely to take hold across the business. CEOs of firms that are successfully scaling the technology often stress cross-collaboration and identify internal AI champions to help teammates work through the transition.
Prioritize strategic AI investments. It’s shrewd to invest deeply in a few high-impact deployments. As Duerloo explains, “CEOs need to place very focused bets. There’s always a temptation to spread yourself too thin across tens to hundreds of use cases, which tends to result in disappointing outcomes.”
A targeted approach also helps AI scale more effectively. Duerloo suggests rolling out AI in select “lighthouse” projects to serve as proof points. Once AI is deployed end-to-end in those areas, adoption can expand systematically across the organization.
CEOs that succeed treat AI as more than a tool to cut costs or improve efficiency. They see it is a chance to rethink how work happens—how employees thrive, how companies operate, and how industries evolve.
And this moment isn’t only about GenAI. This is a time to perfect the act of transformation, readying a company for whatever comes next. CEOs who clearly set AI as a strategic priority, visibly champion the technology, and drive employee adoption will put their companies on the path to measurable impact.
“Technology revolutions will continue to come faster and faster,” Lovich says. Leaders who make AI adoption a core business priority today will build the adaptability and competitive edge their organizations need to succeed—not just now, but for the long run.
