The Expert-Public AI Divide: What 39 Points Tell CEOs About Their Own Blind Spot

The number worth knowing

Pew Research has tracked American attitudes toward AI since 2021. The March 2026 summary report, drawing on five years of survey data, contains one statistic that cuts through every AI headline you have read this year.

Fifty-six percent of AI experts expect artificial intelligence to have a positive impact over the next 20 years. Seventeen percent of the general public agrees.

This is not a story about public skepticism. Americans have become more aware of AI over the same period. The share of adults who say they have heard "a lot" about AI climbed from 26% in 2022 to 47% in June 2025. Roughly a third of Americans now interact with AI multiple times a day, up from 22% in February 2024.

The awareness is rising. The optimism is not following.

What four in five workers are actually doing

The same body of research tracks workplace adoption. As of September 2025, 21% of U.S. workers say at least some of their work is done with AI. Put another way, nearly four in five workers do not report AI doing a meaningful share of their work. Pew separately finds that 65% say they do not use AI much or at all in their jobs.

The number is often cited to argue that adoption is accelerating. That is true. It climbed from 16% in 2024 to 21% in 2025, a meaningful single-year jump.

But the read usually stops there. It does not ask what most workers are actually doing instead.

The answer from the data: they are watching. Fifty percent of U.S. adults say the increased use of AI in daily life makes them feel more concerned than excited. Ten percent are more excited than concerned. Thirty-eight percent feel roughly equal amounts of both.

The numbers describe an audience paying close attention and waiting to be convinced.

The divide does not come from ignorance

The 39-point expert-public split is easy to misread as a knowledge problem. The story goes: experts understand AI deeply, so they see its potential; the public does not understand it, so they worry.

The evidence does not support that story.

Americans who interact with AI more frequently are not automatically more optimistic. Younger adults use AI at higher rates, but their survey responses are not proportionally more positive. The divide between concern and enthusiasm runs across age groups, educational backgrounds, and usage frequencies.

What the data shows is a structural difference in how experts and the public encounter AI. Experts encounter it as a research subject. They control the conditions, define the benchmarks, and choose when to publish results. The public encounters AI as an employment pressure, a workplace decision, a headline about layoffs, or a tool they are told they must adopt before they understand why.

Those two experiences produce different readings of the same technology.

"Fifty percent more concerned than excited describes a workforce watching and waiting. They want someone to make the path legible."

What this means for leaders in Indiana

The U.S. itself ranks 24th globally in AI population diffusion, according to Microsoft AI Economy Institute data cited in the Stanford Human-Centered Artificial Intelligence 2026 AI Index. Indiana's IN AI initiative, launched April 28, 2026, signals that state leaders see adoption as an urgent competitiveness issue, especially for employers and small businesses. A 39-point optimism shortfall in a country already behind on diffusion compounds quickly.

The practical question for a CEO in Indianapolis or Fort Wayne or Terre Haute is not whether their team is skeptical about AI. Most of them are. The question is whether that skepticism produces useful caution or just slows down decisions that need to be made.

Two kinds of caution

Useful caution looks like this: teams that ask "is this the right tool for this task?" before deploying AI, evaluate outputs critically, and build AI proficiency incrementally rather than all at once. That posture maps to Levels 3 and 4 in The 7 Levels of AI Proficiency framework, the stages where systematic thinking replaces ad hoc tool use.

Paralyzing caution looks like this: organizations where AI is the subject of every leadership meeting but the action item of none. Where everyone has heard a lot about it and no one knows what to do with it.

The Pew data suggests most organizations sit somewhere between these two descriptions. Fifty percent more concerned than excited describes a workforce watching and waiting. They want someone to make the path legible.

That is the opening for leaders who are willing to move first.

Related reading: AI proficiency, literacy, and fluency: what the distinction costs you.

Harrison Painter

AI Business Strategist. Founder, LaunchReady.ai and AI Law Tracker.

Harrison helps teams build AI systems that cut cost and grow revenue. Nearly 20 years of business experience. 2.8M YouTube views. Founder of LaunchReady.ai and The 7 Levels of AI Proficiency framework.

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