• Why AI adoption stalls in clinical settings and what actually causes resistance
• The difference between AI adoption in the US versus Latin America
• Why there is no governing body vetting AI products for healthcare
• What clinical due diligence means and why doctors must lead it
• How the Global Medical and Dental AI Summit is building a framework for ethical AI governance

Val works extensively with premed, medical, and dental students across Latin America. What he sees is a generation comfortable with AI tools but blind to the risks.

“Most premed, medical school, and dental students, they’re completely unaware of AI outside of what can help them get their coursework done faster,” Val said. “They’re using tools like ChatGPT. There’s some blind trust. But there’s gaps in the middle, like real literacy.”

Students know how to prompt. They do not know how data privacy works. They do not understand hallucinations or how to verify outputs. They use AI to write papers without understanding the ethical boundaries.

The older generation presents a different challenge. Doctors over 50 who built their careers on paper systems struggle with basic adoption. The learning curve feels steep. The benefit feels unclear.

“Teaching young people is surprisingly easy compared to teaching the older generation,” Val noted. “Those 50 and above who are used to everything on paper, those are the people that are most challenging.”

The solution is meeting both groups where they are. For students, that means teaching safety, privacy, and verification alongside prompting skills. For experienced practitioners, it means demonstrating the time savings in terms they care about.

“You tell them, ‘Hey, something that takes you two days to get done, you’re done in a couple minutes.’ More golfing time for you,” Val said. “That’s how you hook the older guys.”

The dental industry has seen hundreds of AI products launch in the past two years. Some are excellent. Some are disasters waiting to happen.

The problem is that most dentists cannot tell the difference. The questions required to evaluate AI software are questions nobody in dental school ever learned to ask.

Consider a simple example. An AI system listens to phone calls between front desk staff and patients. It analyzes conversations to identify missed opportunities or training gaps. Useful product. But what happens to that data?

“Can an AI that’s listened to this call use information to train on another call?” Adrian asked during the conversation. “That could be a huge cybersecurity issue. I don’t know. Might be.”

That uncertainty is the problem. When a software company builds a product, they may train their models on data from one practice and apply those learnings to another. Patient health information could flow between systems in ways that violate HIPAA without anyone realizing it.

Lawsuits are already happening. Companies are being sued for exactly these kinds of violations. The legal precedent is being established not by thoughtful regulation but by courtroom battles after the damage is done.

“The precedent is the legal system,” Adrian observed. “It’s like, ‘Oh, I guess we’re just going to find out who gets sued and we won’t do that kind of thing.'”

Val believes the solution cannot come from technology companies. It cannot come from government regulators who do not understand clinical workflows. It must come from doctors themselves.

“Nobody’s coming to save us,” Val said. “We need to do what’s best for the patient, and it’s all up to us.”

This is why Dr. Kianor Shah founded the Healthcare Intelligence Board, a doctor-led, doctor-operated global AI governance body. The board spans multiple countries and specialties. Only those with doctoral degrees have voting rights on standards and recommendations.

The logic is simple. Doctors are incentivized to do the right thing. Malpractice insurance, professional licenses, and reputations all depend on avoiding harm. A technology company chasing venture capital has different incentives than a physician who will face a patient’s family if something goes wrong.

“Doctors don’t want to do anything wrong to jeopardize their medical licenses and their reputations,” Val explained. “Whether or not they have ethics, they’re forced to do the right thing for personal self-interest.”

The board focuses on what Val calls clinical due diligence. When a product is meant for healthcare, the experts who will use it should evaluate it. An orthopedic surgeon should not vet dental software. A marketer should not assess clinical safety.