David Bellairian on AI Adoption Bias: Why Better Technology Doesn't Guarantee Faster Adoption

I'm David Bellairian, founder and CEO of Glencore Associates and founder of AIDiscover. Almost every conversation I have with a client at AIDiscover eventually comes back to the same question: Why isn't the market adopting this faster? The product works. The pricing is fair. The pitch is clear. Yet, adoption still crawls.

After enough of these conversations, I see a pattern. Adoption was never really about the technology. It’s about psychology, habit, trust, and culture. Whoever ignores that ends up building something excellent that almost nobody uses.

Adoption Bias Has a Name

In behavioral research, this shows up specifically with AI as algorithm aversion. Researchers Berkeley Dietvorst, Joseph Simmons, and Cade Massey coined this term in a well-known 2015 study. They found that people who watch an algorithm make even one visible mistake will often abandon it. They revert to trusting their own judgment, even when the algorithm is still demonstrably more accurate.

A 2018 follow-up from the same researchers revealed something almost as telling. People become far more willing to use an imperfect algorithm once they're allowed to adjust it slightly. Control over the tool matters as much as the tool's actual performance. Researchers also describe the opposite failure mode: automation bias. Here, people over-trust an algorithm's output without enough scrutiny.

Getting adoption right means navigating between those two biases. It’s not just about clearing the lower bar of building something that works.

Culture is Built, Not Assumed: The Coffee Case Study

One of my favorite examples of cultural adoption isn’t about AI at all, but it illustrates the principle clearly. When Nestle tried to introduce Nescafe to postwar Japan, sales went nowhere for years. Japan had strong buying power but no cultural relationship with coffee. Japanese consumers had tea ceremonies, not coffee habits. They had no childhood associations to draw on.

Rather than keep advertising to adults with no emotional footing for the product, Nestle shifted its strategy. They introduced coffee-flavored candy to children. This built a pleasant, caffeine-free association with the flavor years before those same people would consider coffee as a beverage. By the time that generation reached adulthood, the taste felt familiar rather than foreign. Japan eventually grew into one of the world’s largest coffee markets. Nobody ran a better ad campaign. Nestle changed who the adopters would eventually be.

Healthcare: Trust Has to Be Earned Twice

Healthcare is where the trust barrier shows up most starkly. The stakes feel personal in a way that a marketing tool never will. Physician adoption of health AI reportedly climbed to around 63 percent by early 2026. Roughly three-quarters of U.S. health systems now use at least one AI application. But adoption and trust are moving at different speeds.

Surveys found that around 60 percent of Americans say they'd feel uncomfortable with a provider relying on AI in their own care. Even among patients who trust AI-generated health answers, a similar share still expects their doctor to personally verify anything AI produced before acting on it. Clinicians report the same instinct in reverse. A large majority say they double-check AI outputs due to concerns about bias and error. That’s not irrational. It’s what trust looks like when the cost of being wrong is a person’s health rather than a wasted afternoon.

Real Estate: The Industry Everyone Assumed Would Resist

Real estate surprised me the most. The industry’s reputation is relationship-first and change-averse. Yet, the adoption numbers don’t match that reputation anymore. One survey found that the share of real estate brokerages with no plans to adopt AI in 2026 has fallen to under 2 percent, down from over 10 percent just two years earlier.

Separately, AI adoption among property management companies reportedly jumped from about 20 percent to 58 percent in a single year. The number of commercial real estate firms running AI pilots reportedly rose from 5 percent to 92 percent in three years. What changed? It wasn’t the technology maturing overnight. It was the psychological barrier breaking. Once enough respected peers in the industry adopted publicly, the remaining holdouts stopped seeing it as a risky bet. They began to see it as the standard.

Technology: What EV Adoption Actually Taught the Industry

I’ve watched the EV adoption curve up close, rather than just in the data. The resistance was never really about whether EVs worked. It was about an entirely new set of habits. Planning around charging instead of gas stations. Trusting range estimates instead of a fuel gauge you’ve read your whole life. Giving up a driving and refueling ritual most people never had to think about.

None of that is a technology problem. It’s a habit and trust problem wearing a technology costume. This pattern shows up again with AI.

What This Means If You're the One Trying to Get People to Adopt

If adoption bias is psychological, behavioral, and cultural rather than purely technical, then the fix has to work on those same levels.

Lowering the Initial Cost

In practice, this means lowering the initial cost of trying something. The first attempt should feel low-risk rather than like a bet.

Publishing Real Educational Content

It means publishing real educational content. Articles, guides, and plain explanations of the new way of doing things help people build familiarity before they’re ever asked to commit.

Giving Control Over the Tool

It means giving people some control over the tool rather than a black box. This aligns with the algorithm-aversion research directly.

Showing Early Benefits

Finally, it means being honest that the financial or time benefit needs to show up early, not in year two. People rarely adopt a new habit purely on faith that it’ll pay off eventually.

This is the actual day-to-day work at AIDiscover. We don’t just build or recommend the AI tool. We build the on-ramp that makes adopting it feel like the obvious next step instead of a leap.

I'm David Bellairian, founder and CEO of Glencore Associates, a Los Angeles private investment and asset management firm, and founder of AIDiscover, an AI-powered marketing and brand discovery agency. This is my own read of public research and reporting, not professional or medical advice.