AI for energy systems

Energy companies and industrial manufacturers

Energy and industrial manufacturing companies are the main drivers of AI deployment as the end-users and owners of operational data. Prioritising high-quality data, cybersecurity and governance can help with implementation, while investing in scalable applications like AI-driven asset optimisation, predictive maintenance and real-time system balancing can help to generate rapid returns and resilience.

Technology companies

Technology companies are among the engines of AI innovation and key to tailoring to the needs of the energy sector. By investing in complementary technologies like Internet of Things (IoT) and digital twins and collaborating with energy and industrial manufacturing companies they can provide solutions for grid stability, demand forecasting, and predictive maintenance.

Financial services providers

Financial services providers are important for scaling sustainable and resilient AI-driven innovation. By deploying innovative financing instruments—green and sustainability-linked bonds, concessional loans, and mezzanine financing mechanisms—they can support deployment of sustainable, sovereign AI in energy projects adopting leading efficiency standards and flexible grid integration.

Governments and policymakers

Governments and policymakers can play an important role in creating the conditions for responsible sovereign AI adoption in energy systems. By establishing standards, harmonising secure data-sharing, investing in high-quality datasets, building local capacity through education and public-private partnerships, and maintaining flexible regulatory frameworks, they can accelerate innovation in AI and its adoption.