Scaling AI is about reimagining the enterprise and meeting the energy trilemma head on, embedding intelligence across the value chain to secure supply, decarbonise and control costs. Our findings provide guidance for navigating that future.
AI in energy is about more than just adopting new technologies
At-a-glance insights:
The industry is preparing for an AI future, with early successes
0%
of companies are embedding AI into their offerings.
60%
have had ROIs greater than 10 percent
0%
of companies are scaling AI initiatives and 44 percent are integrating AI as a core part of their operations.
0%
have invested in an automated data fabric or hybrid cloud, cross platform, data integration
64%
operate an enterprise-wide cloud or hybrid-cloud IT infrastructure
Experimentation is a critical investment area
92%
believe that organisations that embrace AI will develop a competitive edge over those who do not
96%
are investing in future-focused projects without the expectation of immediate returns
AI adoption in energy has moved beyond pilot projects. Despite differences between regulated and unregulated entities (as well as the specific nuances of individual sub-sectors), the challenges and opportunities around AI tend to be broadly consistent. Companies across the energy value chain are converging on common AI use cases in areas like operational efficiency, asset optimisation, safety, sustainability and predictive maintenance.
Data-driven decision making tops the list of AI benefits
How you can realize value from an AI transformation journey
To address these challenges, ÀÖÓ㣨Leyu£©ÌåÓý¹ÙÍø introduces the three phases of AI value â€� a framework designed to guide energy companies through the AI adoption journey. This phased approach provides a structured roadmap, helping the energy industry prioritise investments, align initiatives with business goals, and position themselves effectively in the age of AI in energy.
The Enable phase establishes the foundations for AI adoption and focuses on creating awareness, experimentation and alignment to help ensure the organisation is prepared for broader AI integration. This includes developing an AI strategy, increasing AI literacy, learning from initial implementations and more.
The Embed phase integrates AI into end-to-end value streams and transforms ways of working across the enterprise. A senior leader, supported by a capable transformation office, oversees enterprise-wide change.
The Evolve phase transforms enterprises so they can anticipate market disruptions, forming new business models and ecosystems to solve larger, industry-wide problems. Energy companies move beyond internal optimisation and become orchestrators of interconnected ecosystems, seamlessly integrating producers, grid operators, industrial consumers, governments and sustainability initiatives.
Intelligent energy
This research outlines a detailed blueprint for AI energy organisations, helping organisations chart a path toward unlocking AI’s immense value.
Our executive summary provides a cross-sector view of how organisations are navigating the opportunities and challenges of implementing AI. Download the executive summary to see the blueprint for intelligent industries to help you become an AI-powered, customer-centric organisation ready to thrive in the intelligent economy.Â
How can ÀÖÓ㣨Leyu£©ÌåÓý¹ÙÍø in India help
Related Content
Key Contact
Anish De
Global Head for Energy Natural Resources & Chemicals (ENRC)
ÀÖÓ㣨Leyu£©ÌåÓý¹ÙÍø International
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