AI, energy crisis and climate change

Globally, efforts are underway to address the complex nexus between AI, energy and decarbonisation

- Arthur Mutambara

Artificial Intelligence (AI) is driving societies, economies and geopolitics worldwide but at what cost to the environment and climate?

There is a paradox of AI as both a catalyst for clean energy innovation and a growing threat to global energy supply, while worsening the climate crisis.

From the massive power demands of data centres and AI factories to the potential of AI to optimise renewable energy systems, policymakers and innovators need to rethink how technology, particularly AI, aligns with the Sustainable Development Goals, especially Access to Affordable Clean Energy (SDG 7) and Climate Action (SDG 13).

Optimisation of public transport systems

In public transport, AI-powered systems use real-time data, predictive analytics and machine-learning algorithms to optimise bus and train schedules in response to passenger demand, traffic conditions, and operational constraints.

By dynamically adjusting routes, departure times and fleet allocation, these systems reduce idle time, unnecessary mileage and congestion-related delays.

The resulting efficiencies lower fuel and electricity consumption, reduce operational costs and extend the lifespan of vehicles and infrastructure.

In doing so, AI-enabled scheduling not only improves service reliability and commuter satisfaction but also promotes energy-efficient, environmentally sustainable urban transport systems.

Access to clean energy in underserved regions

AI offers innovative solutions to expand clean energy access in remote and underserved areas by enabling decentralised energy systems, optimising microgrids and supporting off-grid renewable energy projects.

AI-driven microgrids (localised energy grids that operate independently from the central grid) provide a sustainable solution for remote communities with limited access to conventional energy infrastructure.