AI and the energy transition: Go beyond the optimization

AI can accelerate the energy transition, but it can also lock it into old growth logic. In his essay Beyond Optimization, Marco Derksen examines the dual role of artificial intelligence and introduces a 'transformation matrix' that shows where space may be created for a regenerative energy system. The essay was commissioned by the National Program for Regional Energy Strategy.

The energy transition is inevitable, but its course is far from certain. In his essay 'AI in the Energy Transition: Beyond Optimization', digital strategist and lecturer Marco Derksen poses the uncomfortable question: Does artificial intelligence (AI) truly contribute to a sustainable future, or does it primarily reinforce the logic of growth and efficiency that has led us to our current predicament?

“AI is often presented as the key technology for making grids smarter, predicting maintenance, and better balancing supply and demand,” writes Derksen. “But as long as we don't question the underlying assumptions, AI mainly reinforces the existing system.”

The optimization paradox

The essay is full of paradoxes. AI can make existing systems more efficient, but precisely because of this, it can also keep us trapped in a system that relies on extraction and overconsumption. Derksen calls this the “optimization paradox”: technology that is intended to solve problems can actually perpetuate them if it is only used to increase speed and reduce costs.

That is why he advocates going a step further: “beyond optimization.” This means not only doing what we already did in a smarter way, but also redesigning from different assumptions. What role can AI play in an energy system that not only strives for sustainability, but also actively restores nature and society?

The transformation matrix

To make this quest more concrete, Derksen introduces the transformation matrix. With this, he shows how AI applications move between two axes: optimization versus transformation, and extractive versus regenerative.

An example: AI that solves grid congestion more intelligently by distributing energy more efficiently is on the optimization side. It helps the existing system run more smoothly, but does not change the fundamental logic. AI that enables citizens to build local ownership in energy cooperatives, on the other hand, opens the way to regeneration: a system that not only causes less harm but also actively contributes to resilience and recovery.

The matrix serves as a framework for thinking: where are we currently using AI, and where could we position AI differently?

The transformation matrix consists of two axes. Horizontally, the scale ranges from optimization (efficiency and cost reduction) through redesign (new processes and decentralized organization) to regeneration (ecological integration and social justice). Vertically, the scale moves from operational (daily implementation) to tactical (coordination and alignment) and strategic (long-term values and system design). © Marco Derksen

Writing in dialogue

What is striking about Derksen's approach is that he did not write the essay from an ivory tower. The thinking and writing process took place partly in public, via his blog Koneksa Mondo and on LinkedIn. There, he presented ideas, preliminary concepts, and questions to his network. The responses, whether approving, critical, or supplementary, fed his own thinking.

In this way, the essay grew into more than a personal analysis: it became a collective quest, in which Derksen allowed himself to be challenged and inspired by the questions and insights of his readers. The result is a text that reflects not only his own intellectual development, but also the sensitivities, concerns, and perspectives of a broader community.

Methodology and motivation

Derksen is not an outsider speculating from behind a desk. With over 25 years of experience as a digital strategist, he guides organizations through digital transformation. In recent years, he has focused primarily on the public sector: education, healthcare, government, security, and water boards. That practical experience forms the basis of his essay.

What drives him? According to Derksen himself, it is the urgency to look beyond the technological hype. “Every technological revolution requires a new institutional framework that gives direction to its potential,” he writes, referring to economist Carlota Perez. Without that institutional renewal, AI will not be a catalyst for systemic change, but merely an accelerator of business as usual.

Beyond the logic of growth

Central to the essay is the question of whether AI reinforces the existing logic of growth or whether it opens the way to a regenerative energy system. That is a fundamental difference. In the first case, AI is used to make energy cheaper, faster, and more scalable, but still within an economic system that is structurally dependent on growth. In the second case, AI is designed to reinforce values such as recovery, ownership, and resilience.

Derksen thus describes AI not as the panacea for which it is so often praised, but as a mirror of our own choices. The technology itself is not neutral; it acquires meaning within the system in which we use it.

An invitation to think differently

With Beyond Optimization, Derksen wants to do more than just list technological opportunities. He offers a methodology for shifting the way we think about AI: from optimization to transformation, from extraction to regeneration.

For those who view the energy transition primarily through a technological lens, this is a provocative message. AI can indeed help us move forward more quickly. But the real question is: forward in what direction?