PhD defence: Digital innovation and sustainability transitions - Exploring the twin transition in energy-intensive processing industries

As the climate crisis and other societal challenges intensify, there is a spotlight on the role of digital technologies like artificial intelligence (AI). Promised as game-changers, these innovations are said to be key to cutting emissions and transforming industries. But does this promise hold up in practice? This thesis explores the "twin transition" of digitalization and decarbonization, studying how technologies like AI impact sustainability goals in energy-intensive industries like steel and chemicals. The research draws on an inventory analysis of 140 AI tools and 12 interviews with key global steel industry actors, alongside 28 interviews with stakeholders in digital innovation across the Dutch processing industry.

The findings reveal a double-edged sword. AI has the potential to optimize processes, reduce waste, and unlock efficiencies of all kinds. For example, AI can help predict and prevent equipment failures, saving energy and resources. Yet, there’s a catch: these same technologies often end up strengthening old, fossil-based systems instead of driving the radical shifts needed for a low-carbon economy.

This research shows that the way we deploy digital innovation matters just as much as the technology itself. The sustainability impact depends on how we steer its development and application. By designing better policies and frameworks, we can ensure digital tools actively support decarbonization efforts instead of delaying them. Purposefully aligning digitalization and sustainability requires policymakers and industry leaders to address systemic barriers, reorient innovation systems, and confront vested interests that exploit the twin transition narrative to maintain the status quo. Only by tackling these challenges can digital technologies like AI truly contribute to transformative change.