From awareness to action — why AI needs its renewable-energy moment
There is a moment I keep returning to. During the COVID lockdowns, when governments halted entire economies to protect lives, I believed we had crossed a threshold. That genuine awareness — visceral, shared, undeniable — might finally translate into sustained climate action. I wrote optimistically about that possibility at the time.
The pattern that followed was familiar. Once restrictions lifted, emissions rebounded. Markets reprioritised growth. Climate commitments lost urgency. ESG investments peaked, then declined. Regulatory momentum stalled. The rhetoric of crisis persisted while behaviours reverted.
We’ve done this before
Within the Greening of Streaming initiative, I observe the same contradiction: near-universal agreement that reducing streaming energy use matters, yet minimal actual decision-making based on that principle. Energy efficiency rarely ranks among top procurement priorities. Measurement exists without corresponding incentives to act on findings.
When the story softened
At France Telecom — rebranding to Orange — I first encountered sustainable development: a phrase implying direction and intentional growth. Over time, development quietly disappeared. Sustainability became a label to display rather than a direction to pursue. Corporate communication stripped away the challenging edges.
AI faces identical linguistic risks. Terms like responsible AI, ethical AI, and frugal AI sound appropriate but risk becoming empty signifiers without structural change. We excel at naming problems while struggling to redesign systems.
How change actually happens
Sustainability gained genuine momentum only when economics shifted. Renewable energy didn’t triumph through moral persuasion — it triumphed through cost advantage. When solar and wind became cheaper than fossil fuels for new electricity generation, behaviour changed rapidly. Economic logic proved more powerful than ethical arguments.
Could the same apply to AI?
Responsible design, transparency, and restraint will achieve scale only when they reduce expenses, mitigate risk, protect profitability, or attract customers. Currently, markets overwhelmingly reward speed, scale, and competitive advantage.
I acknowledge my own participation in this dynamic. AI is now embedded in my client work. My experience still provides value — yet that value’s nature is shifting substantially.
The next inflection
AI likely approaches its own renewable-energy moment, though probably following a correction first. Massive capital investments cannot fulfil all promises. When investment exceeds viable economics, markets eventually reprioritise.
That recalibration often introduces constraints — not through ethics-first reasoning, but through necessity. Transparency, efficiency, and accountability typically emerge once cost, risk, or regulation force them into fundamental business operations. If this occurs, responsibility may transition from optional to essential.
The modest lesson
Sustainability revealed how change becomes achievable: through the alignment of conscience, capital, and community.
Awareness is the beginning, not the turning point.
Originally published on LinkedIn Pulse, December 2025.
This article is part of a series on AI and sustainability. Also read: When the Road Is Gone: AI Burnout and the Death of the Journey