Powering the Future: How AI is Driving the Next Wave of Energy Innovation

At a time when sectors are keeping up with enhanced market risks and increased economic volatility, energy fundamentals remain strong. Consequently, unlike other sectors, influences such as economic uncertainty, complex regulatory developments and market competitiveness have not limited confidence on exploring new technologies, especially AI. The energy sector’s boldness toward technology adoption is illustrated in the findings of the above KPMG report, wherein 25% of energy professionals, compared to 17% of their counterparts across other sectors, have stated that risks rarely hinder the senior leadership’s attitude toward AI.

The impacts of AI have been revealed to be universal, potentially almost all aspects of corporate operations.  A big advantage of the energy sector is that there is a lot of data available, much of which is in digitised form. This availability of structured data complements with the broader structured and unstructured data available from external sources, creating a rich base for action in the energy companies. As a result, AI adoption in the energy sector is moving beyond proof-of-concept. Today, many energy firms are in the top two AI maturity stages, actively using AI to enhance operations, optimise grids, and improve predictive maintenance. Global energy firms are using AI for several activities including predicting demand, serving customers more effectively, optimising smart grids, integrating renewable energy and enhancing operational efficiency radically.

However, as is to be anticipated, the same KPMG Report states how a sizable 33% are still within the proof-of-concept stage, taking a cautious approach to AI experimentation. There are concerns about security, privacy, costs and adoption that prevail on the minds.  For example, there are evolving questions on integration of Operational Technology (OT) with Information Technology (IT) in an AI environment. As a result, for many of these to be able to drive the next wave of energy innovation, scaling AI responsibly will be the next big step. At a time when energy firms are scaling renewables while continuing with legacy technologies to serve demand, they need to take on the challenge of further unlocking the full potential of AI to optimise and improving overall system and financial efficiency.  

Investment in the supply of energy and natural resources will reach record levels in 2025, with spends exceeding $1.5 trillion over our forecasts, up 6% in real terms on 2024. At a time like this, the sector will have to embrace AI to accelerate energy production, but it needs to be done with care. As technological innovation opens new potential in the energy sector, a balance needs to be struck between rapid adoption and a strategic approach to extracting genuine value from technology. In particular the energy companies need to put in enterprise architecture that integrates all the applications and ensures value delivery and security. In the evolving world of Agentic AI there will be a need to also assess the degree of human control to retain through the core processes while allowing the efficiencies of Agentic AI to transform operations radically where practicable.

As the energy sector stands at the intersection of unprecedented challenges and opportunities, evidence-based decision-making will be key for tuning out of the hype and focusing on scaling AI responsibly. For CEOs of energy companies, Generative AI is both a risk and an opportunity. They will, however, have to gauge the opportunity to risk ratio for successfully leveraging advanced technologies and data driven insights to drive the next wave of digital transformation.

Modern AI is and will remain in continuous evolution, combining with other digital technologies, High Performance Computing (HPC) and quantum technologies. The potential of AI to drive the next wave of energy innovation far outweighs the risks of falling behind. The safeguards on privacy, ethics or integrity, among others will need to be integrally baked into every step and component of the enterprise technology architecture that AI rides on. This will require bold steps on envisioning the architecture, creating foundational technologies, integrating AI into core business options and effective change management.  The new AI environment has to be consciously engineered for success with strong design fundamental and essential guardrails that provide business leaders the confidence that AI is making their businesses efficient, responsive, and future ready.

A version of this article was published by CNBC TV18.com on April 02 2025. The same can be read here