At the Panoramai AI Summit, Reda Sadki, leader of the Geneva Learning Foundation, delivered provocative insights about AI's impact on global equity and the future of human work. Drawing from humanitarian emergency response and global health networks, he challenged comfortable assumptions about AI's societal implications.

The Job Displacement Reality

Reda directly confronted panel optimism about job preservation: « One of the things I've heard from fellow panelists is this idea that we can tell employees AI is not coming for your job. And I struggle to see that as anything other than deceitful or misleading at best. »

Concrete Evidence from Ukraine Project

« We needed humans, Ukrainian humans, for six months to help understand how the knowledge function was going to work... Once we had done that, we no longer needed them. » Reda provided specific evidence of AI eliminating knowledge worker positions in education support systems.

Global Access Inequities

Reda highlighted three critical equity challenges: geographic access restrictions ("geolocking"), transparency expectations around AI usage, and punitive accountability systems that discourage innovation in humanitarian contexts. « Somebody who uses AI in that context is more likely to be punished than rewarded, even if the outcomes are better and the costs are lower. »

Emerging Markets Disconnect

« Even though that's where the future markets are likely to be for AI, » Reda observed limited engagement with Africa, Asia, and Latin America among attendees, highlighting a strategic blindness to global AI market evolution.

Organizational Evolution Question

Reda posed fundamental questions about future organizational structures, questioning whether traditional hierarchical models with management layers will remain dominant « two years or five years down the line. »

Network-Based Innovation Vision

Through Geneva Learning Foundation's work, Reda demonstrated building large-scale networks of health workers sharing experience and taking action in climate change response, positioning human facilitation and peer learning as remaining uniquely human capabilities.

Exponential Learning Challenge

« These machines are already learning faster and better than us and that, and they're doing so exponentially better than us. It's pretty clear what, you know, what keeps me awake at night is what what's left for humans. »

Key Achievement: Reda demonstrated how honest assessment of AI's transformative impact requires abandoning comfortable narratives about job preservation, positioning global leaders to address equity challenges while identifying uniquely human capabilities in an AI-augmented world.