How will artificial intelligence transform global health?
The Geneva Learning Foundation (TGLF)
Learn to connect. Connect to learn. Lead to impact.
Something unusual happened at the RAISE Summit in Paris last week.
Eric Schmidt revealed that tech leaders who usually compete fiercely have quietly reached consensus. They all believe the same thing about AI timelines.
Their prediction? Much shorter than most people expect.
But here’s what caught our attention at The Geneva Learning Foundation: these aren’t just predictions. These are the people building AI infrastructure and directing investment flows right now.
When they converge on a timeline, that timeline starts shaping reality whether the predictions prove accurate or not.
Why we’re paying attention (and why you should too)
As an organization connecting health professionals across 137 countries, we hear questions like these:
“How do we evaluate AI tools that might help our communities?”
“What should we prepare for, and what’s just hype?”
“How do we avoid being left behind OR wasting scarce resources?”
These questions led us to develop the #AI4Health Framework—the first comprehensive approach for AI in global health.
But Schmidt’s presentation revealed something we hadn’t fully grasped. The AI developments happening now aren’t separate trends.
They’re pieces of a coordinated transformation.
The four pieces that connect in surprising ways
Schmidt outlined specific capabilities emerging simultaneously. Each one challenges different assumptions about how health work gets done.
But the real insight? How they work together.
Piece 1: The consensus driving billions in investment
Silicon Valley leaders have converged on accelerated timelines. But what does this actually mean for health organizations making decisions today?
Hint: It’s not what most people think.
Piece 2: Why the most advanced AI tools are failing
Organizations are investing in sophisticated AI systems. Many see disappointing results. The problem isn’t the technology.
The problem is something most funders completely overlook.
Piece 3: The interface shift nobody’s discussing
For fifty years, humans have adapted to technology. That relationship is inverting. But what does this actually mean for health workers in practice?
The implications go deeper than convenience.
Piece 4: When AI started thinking like an epidemiologist
AI systems now reason through complex problems step-by-step. They form hypotheses, test them, and adjust their approach.
But there’s a catch that changes everything about expertise.
Piece 5: The coordination bottleneck that’s disappearing
AI systems are learning to work together on complex operations. This changes how we think about workforce development entirely.
But are organizations preparing for the right transformation?
The pattern most organizations are missing
Here’s what became clear after analyzing these five developments:
Organizations preparing for individual AI tools are preparing for the wrong transformation.
The real opportunity—and challenge—lies in something else entirely. Something that aligns perfectly with how humans actually learn and adapt.
Which brings us back to why The Geneva Learning Foundation is uniquely positioned for this moment.
For 15 years, we’ve been developing peer learning approaches that help health professionals navigate complex challenges together. Now we realize that collaborative learning might be exactly what’s needed for AI transformation.
Not because AI is just another tool. Because AI transformation requires the kind of collective intelligence that emerges when humans learn together.
What we want to know from you
As we develop our #AI4Health Certificate programme, three questions keep surfacing:
Which of these five pieces resonates most with what you’re seeing?
What challenges is your organization facing that these analyses might address?
How can we ensure AI transformation strengthens rather than fragments health systems?
Share your perspective in the comments. We’re building this learning community together.
Ready to explore these ideas more deeply?
Download the #AI4Health Framework and get early access to our Certificate programme: https://www.learning.foundation/ai
The Geneva Learning Foundation connects health professionals worldwide through peer learning approaches that create lasting change. Subscribe to join the conversation as we navigate AI transformation together.
Humanitarian Protection&CapacityBuilding| Education Institution Management |Teaching & Learning Expert | Talent Identification & Development | European PFA Focal Point |Mentors for Ukraine Group
3wThe biggest challenge to AI transformation is cultural and organizational inertia. For AI to strengthen healthcare rather than fragment it, we need to move from training on individual tools to creating an environment for collaborative learning. By guiding professionals to work together on common challenges and adopting a human-centered mindset, AI can be a catalyst for unity and improved patient care. This approach doesn't teach AI in the traditional sense; instead, it teaches AI by having teams start with a real-world problem and then learn and apply the specific AI tools needed to solve that particular problem, making learning practical and relevant. Or create "small" AI agents to help analyze or collect information training it to avoid biases. Then it becomes a matter of securing the process.