Most Americans Have Heard of AI. Few Actually Use It. Here's What That Gap Means for Leaders
Fresh Gallup data reveals why your AI rollout might be stalling and five practical fixes that actually work
I’ve spent a lot of time in rooms where AI talk goes in circles. Big promises, real fear, then a polite “we’ll revisit this next quarter.” So when fresh, nationally representative data lands, I pay attention. Gallup, working with the Special Competitive Studies Project, just published a survey of 3,128 U.S. adults, fielded in late April and early May. It is clear, readable, and, in a few places, counterintuitive.
Why this report matters
Executives need a clear understanding of how employees and customers are thinking. This survey shows near-universal exposure to AI news, yet actual hands-on use and confidence lag. That gap explains adoption friction inside companies better than any slide I’ve seen.
At a glance, the baseline is as follows: 98 percent have seen or heard about AI in the last year. Only 39 percent say they use it sometimes or more. Just 8 percent feel “very knowledgeable.” About one in three trust AI to make fair, unbiased decisions, and trust is twice as high among users compared with non-users. That single fact points to a simple truth I see every week: good experiences build trust, not memos.
The headline findings, in plain English
79% of Americans believe AI is important to the country’s future, yet they are unsure whether the U.S. will lead. More think we are falling behind than moving ahead, and a large share say they do not know where we stand.
Security fears are widespread. Eighty-seven percent think foreign governments are likely to use AI to attack the U.S., with 43 percent calling it very likely.
The economy story is split. Most expect AI to raise productivity and drive growth, but many also anticipate it will lead to job cuts and business closures.
People rally around training. The most popular policy by far is workforce training and education on how to develop or use AI, with 72 percent support. Tax breaks and deregulation trail far behind.
What actually surprised me
1) The age gap runs the “wrong” way. Younger adults are less likely than older adults to say countries are competing on AI, and less likely to say U.S. leadership is very important. If you assume your youngest employees are your AI true believers, this should make you pause. Many are curious and skilled, yes, but the survey suggests a softer view of the global stakes.
2) Security beats the economy in people’s mental model of AI. When asked where AI matters most for the U.S. future, more people rank AI as very important to national security and military strength than to economic strength. That flips the boardroom script. We talk about cost and productivity first. Employees are thinking about safety.
3) Support toggles with threat framing. On autonomous weapons, opposition leads in a vacuum, yet support jumps to a majority if others move first. The public mood is conditional and reactive. Your internal messaging should expect the same behavior: people say yes when they see clear context and controls.
4) Use breeds trust, at scale. Users are about twice as likely to trust AI to be fair. It sounds obvious, but it’s a management lever you can pull.
What this means for leaders
Start with safe, hands-on use, not a platform parade. If trust follows use, then your first program is a protected sandbox. Pick three roles where AI can help this quarter, give people real tasks, and measure two things each Friday: time saved and confidence. Make it small, visible, and repeatable.
Frame AI as a risk and control topic, not only as an ROI topic. Employees are already primed to see AI through a security lens. Meet them there. Write down data-handling rules in plain language. Show which tools are approved, what is logged, and how private data is kept out. A three-page standard beats a 30-page policy no one reads.
Fund training like it matters. The public’s top request is training. Create an internal “AI skills stipend,” for example, 20 hours per quarter, with a short list of courses and a requirement to submit two work samples that apply new skills. Tie bonuses to adoption quality, not just usage counts.
Acknowledge job churn and plan for it. The report shows people expect gains in productivity and pain in jobs at the same time. Be candid about both. Map tasks, not roles. If 25 percent of a role can move to AI support this year, say so, then show the transition path: reskill to higher-value tasks, new targets, new review criteria.
Set a scoreboard. Pick five metrics you can post monthly: percent of teams with an approved use case, average minutes saved per task, error rate trend, number of employees trained, and number of safe AI automations deployed. Keep it boring and numeric.
One final cultural note. The age pattern suggests you cannot assume the 25-year-old is your AI champion or the 55-year-old is a skeptic. Treat enthusiasm and concern as cross-cutting. Put mixed crews on pilots and make them teach each other.
If you want the short version: make AI tangible, make it safe, and make it a skill you reward. The rest will follow, not by decree, but by experience.
Here’s a link to the report: https://www.gallup.com/analytics/695033/american-ai-attitudes.aspx
Moving Forward with Confidence
The path to responsible AI adoption doesn't have to be complicated. After presenting to nearly 1,000 firms on AI, I've seen that success comes down to having the right framework, choosing the right tools, and ensuring your team knows how to use them effectively.
The landscape is changing quickly - new capabilities emerge monthly, and the gap between firms that have mastered AI and those still hesitating continues to widen. But with proper policies, the right technology stack, and effective training, firms are discovering that AI can be both safe and transformative for their practice.
Resources to help you get started:
In addition to publishing thought AI leadership on a regular basis, I also work directly with firms to identify the best AI tools for their specific needs, develop customized implementation strategies, and, critically, train their teams to extract maximum value from these technologies. It's not enough to have the tools; your people need to know how to leverage them effectively.
For ongoing insights on AI best practices, real-world use cases, and emerging capabilities across industries, consider subscribing to my newsletter. While I often focus on legal applications, the broader AI landscape offers lessons that benefit everyone. And if you'd like to discuss your firm's specific situation, I'm always happy to connect.
Contact: steve@intelligencebyintent.com
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