The 2025 Nobel Prize & the Lesson It Offers the AI Era

This year’s Nobel Prize in Economics carries a message that feels uncannily relevant to the moment we are living through in AI. Joel Mokyr, Philippe Aghion and Peter Howitt were honoured for explaining how innovation drives long run growth and why that growth sometimes stalls.

Joel Mokyr argues that inventions existed long before the Industrial Revolution, yet they rarely translated into sustained prosperity because useful knowledge was fragmented. Practitioners knew what worked, theorists knew why, but the two worlds barely interacted. Growth took off only when scientific understanding and practical skills converged, enabling technologies to scale and spread.

Aghion and Howitt formalised this idea through their model of innovation driven growth, built on creative destruction: new ideas displace old ones, raising productivity while disrupting firms and workers. Innovation requires incentives namely temporary market power, IP, patient capital but excessive protection allows incumbents to block future innovators.

This balance is exactly where the AI economy sits today.

Companies like NVIDIA, which invested for over a decade in CUDA and AI focused chips long before today’s boom, now illustrate how long horizon risks can become engines of new economic waves. At the same time, the disruptive edge of creative destruction is becoming visible in workforce anxieties, industry uncertainty and the widening gap between early adopters and late movers.

This makes AI policy a genuine tightrope walk.

On one side: competitiveness, first-mover advantage and national ambition.

On the other: job displacement, inequality and the need for retraining and safety nets.

Yet AI also democratizes knowledge in ways that echo Mokyr’s insights. High-level capabilities that once required elite skill are now accessible to small firms and individual workers. Theory and practice are converging again but this time at digital speed and risk of IP theft, thus disincentivising original work. 

The challenge for leaders is no longer just how fast we innovate but how widely innovation is adopted and how responsibly transitions are managed.

Creative destruction will continue to power progress but its impact, positive or negative, will depend on how intelligently we govern the shift.

The Nobel Committee honoured a framework for understanding growth.

AI is now testing that framework in real time.