Generative AI use on increase in energy sector

Increasing investment in and use of generative AI in the energy and utilities sector is revealed in new research from Capgemini.

Of the organisations surveyed in the sector almost one quarter indicated they had enabled generative AI in some or all of their functions and/or locations in the current year, compared with just 3% in 2023.

And almost half indicated having begun working on some pilots of generative AI initiatives in 2024, compared with just over one-third in 2023.

These figures are close to the average across all sectors surveyed, with investment broadly increasing in line with organisation size.

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Across the sectors the top use cases include IT, risk management and logistics and almost all the organisations’ employees are allowed to use generative AI in some capacity.

Energy sector use cases

For example in the energy sector, an example cited is BP, which is leveraging generative AI to assist employees with daily tasks such as email management and thereby enhance productivity and the business workflows.

Another example is Schneider Electric, which has integrated generative AI into its ‘finance advisor’ conversational assistant for enhancing decision-making across accounting and related functions.

Other use cases cited in the sector with piloting and/or implementation up in 2024 compared with 2023 include the generation of synthetic data, new material design, smart grid management and predictive maintenance.

With these and other similar examples across other sectors, generative AI is yielding benefits, such as an almost 8% improvement in productivity and almost 7% improvement in customer engagement and satisfaction, the survey found.

Further, the majority of organisations believe that generative AI will unlock revenue growth and foster innovation – over three-quarters in the energy and utilities sector now, compared with two-thirds in 2023.

“Generative AI is starting to transform business and organisations are already seeing concrete growth in revenue, whilst also accelerating innovation,” says Pascal Brier, chief innovation officer at Capgemini.

“As investment increases, the rise of more complex, autonomous AI systems signals a new era of generative AI that could impact the way companies operate.”

AI agents

A key area of generative AI innovation is AI agents, with the majority of organisations recognising significant value in these and in particular with them helping to drive higher levels of automation in workflows.

Capgemini defines an AI agent – of which the most basic form is a chatbot – as “technology designed to function independently, plan, reflect, pursue higher-level goals and execute complex workflows with minimal or limited direct human oversight”.

These agents can then be combined in multi-agent systems solving tasks in a distributed and collaborative way.

Currently, only around 10% of organisations employ AI agents but over 80% expect to integrate them within the next one to three years.

In conclusion, in its report Capgemini suggests that for organisations to propel their AI journeys forward, they should establish strong data foundations with clear processes to manage siloed data and enable data integration across functions.

“Trust, transparency, and accountability will continue to play a central role whilst embracing this next frontier of AI that has the potential to deliver significant value over time,” concluded Brier.