In 2026, most organizations aren’t debating whether to use AI. They’re stuck on how.
More specifically: “How should we use AI in our work?” We hear it from clients quite frequently and left unanswered, that question stalls their adoption.
Recently, we watched one team at a leading technology provider labor over that question and get nowhere.
It wasn’t until a leader paused and had the courage to change the question that momentum returned. Instead of asking, “What can we automate?”—a question that positions AI as the driver—they asked: “What’s one thing we keep doing, but no one is happy with the solution?” A question that put the team back in control.
That single shift unlocked not just action, but motion. Immediately, they identified a recurring customer intake process that had been persistently frustrating people for months. Within 45 minutes, they built a tiny AI-enabled assistant. Within a week, they committed to switching intake platforms to deliver a better experience at a lower cost.
The breakthrough wasn’t the AI tool they were using or their level of skill with it. It was the shift from “AI is happening to us” to “we’re shaping how the work gets done.” And that is the power of agency.
Why your people’s agency matters in AI adoption
Leaders everywhere are facing the same tension when it comes to AI: big expectations, unclear returns, and teams who are tired of feeling like AI is something being done to them.
That tension is showing up in the data. Recent INSEAD research points to a widening gap: AI investment keeps rising, while productivity gains remain stubbornly flat. Many organizations are caught in an experimentation trap; pilots multiply, but few scale, and frontline teams feel little impact on the work that actually matters, while still carrying the growing expectations of leaders far removed from it.
At the same time, public sentiment is shifting. As The New York Times noted, many people feel like AI is something they never asked for, but suddenly have to live with. That’s not a technology problem. It’s a crisis of agency. And we see this firsthand.
What puts AI workforce transformation at risk
In our experience, AI transformations are fraught with two equal risks: (1) doing nothing (and falling behind) or (2) doing the wrong things (and creating noise, cynicism, and rework).
Where we’ve seen stronger outcomes is when organizations treat AI adoption as a talent development challenge. As Ethan Mollick recently wrote, tools like Claude Code can make skilled programmers more productive, but they don’t magically create skill where none exists.
The same is true in innovation. AI accelerates teams that already know how to diagnose problems, test small bets, and iterate. But without those pre-existing habits, leaders can't expect real behavior change around AI.
That’s why organizations that succeed in AI adoption start by helping their people:
- 1. Build AI confidence
Give people hands-on experience using AI in real work, paired with clear guidance that strengthens judgment, safety, and responsible use.
- 2. Find the right use cases
Help teams spot friction in their day-to-day workflows, connect those pain points to business priorities, and test AI “assists” prototypes before scaling.
- 3. Communicate AI strategy
Support leaders and managers to explain the “why” behind AI strategy, address real concerns, and invite teams to shape how AI shows up in their workflows.
And when organizations are ready to move beyond isolated interventions, these approaches can be sequenced into a more holistic AI journey toward becoming AI-native.
But here’s the catch: none of these approaches to building AI adoption work without first addressing human agency. People need to feel they have the power to decide how this new tool reshapes their workflows; to have a stake in the game and a reason to keep reaching for it over time.
Without that sense of ownership and the permission to experiment, AI will likely stay idle.
If you want examples of what “restoring agency” looks like in practice, join our AI webinar on March 12th to see how leading teams are building AI capability that makes adoption tangible.A leader’s playbook for restoring agency & accelerating AI adoption
One of the fastest ways leaders can get AI adoption moving is to give people a clear place to start so they can regain a sense of agency in their work. This three-step playbook helps leaders create early momentum, then build from there.
Ask teams to:
- 1. Find the friction
Ask, “Where are we stuck right now?” in their real work. Look for a customer moment where delays, rework, or underwhelming results show up week after week.
- 2. Build a small assist
Next, build the smallest AI-enabled assist that helps with the next decision. That might be a draft email, a triage checklist, or a simple decision guide. Nothing fancy, just something that makes the next step easier.
- 3. Measure and scale
Finally, track cycle time and confidence, and then scale what works. If it helps one team move faster and feel more capable, turn it into a pattern others can adopt.
AI adoption accelerates, not when leaders push harder, but when teams can see its quantifiable value and/or joy in their own work. What starts as one small assist becomes a repeatable pattern and a repeatable pattern can eventually become a habit that moves the adoption forward.
In other words: that’s one small assist for AI, one giant leap for AI adoption.
Why AI adoption stalls without agency
AI adoption doesn’t stall because organizations lack ambition or investment. It stalls when people feel AI is being done to them, without any say in how their work changes.
Those making real progress with AI adoption are not necessarily launching the most pilots. They are the ones deliberately building workforce capability; equipping people to diagnose real problems, test small interventions, and develop judgment through use.
In the end, what will set the best organizations apart won’t be who had access to the best tools or pilots. It will be those who built the human agency and capability to use them well.
That work begins with a simple shift in the question “How should we use AI in our work?” and a willingness to let people own the answer.
Align your AI ambition with your workforce strategy
Your people are the difference between adoption and failure. Give them the skills they need to make your strategy a success.
About The Author
Andrew Webster is ExperiencePoint's VP of Organizational Innovation. He has spent more than 17 years helping leaders and teams build organizational change and innovation capability at the world's top organizations. His writing explores AI adoption, innovation practices, and how organizations build the human capability behind transformation. Recently, he led a hands-on AI training session for senior finance leaders at an Economist event, increasing attendees’ daily AI usage from 13% to 59% in just two hours.