KPMG on How AI Will Shape the Electrical Grids of Tomorrow

Right now, the global energy sector has to contend with conflicting demands.

First is the demand for renewable energy, without which our world will be at the mercy of climate change.

Second is the demand for greater amounts of energy overall. Population growth, the rise of AI and computing, and the growing electrification of technologies previously powered by fossil fuels all necessitate more power.

Then, the energy sector must also consider the distribution of energy. Electrical grids are, for the vast majority of civilisations around the world, the means by which energy is transported.

These complex, sprawling pieces of infrastructure were first introduced in the late 19th century and have been upgraded and modernised in piecemeal fashion in the years since.

Today, though, the simple truth is this: electrical grids will require huge renovations to cope with the demands of tomorrow.

Unlike fossil fuels, the supply of most renewable energy is inherently intermittent.

Solar panels require sunlight, turbines require wind and tidal power is inextricably tied to the natural ebb and flow of the oceans.

This means that our energy infrastructure must be able to cope with surges and droughts in power, which experts worry our grids will be unable to manage, potentially leading to unreliable supplies and voltage instability.

“Grids were not originally set up for such a fast-paced energy system,” McKinsey stated in a 2024 report. 

“Their tools and processes were developed in a slower, less volatile world.”

Are ‘smart grids’ the solution?

Increasingly, AI is being touted as a solution to grid problems that are giving energy executives sleepless nights.

According to KPMG’s latest Global Tech Report, many energy companies are actively exploring AI’s applications in grid infrastructure and beyond.

"AI is set to change the future of energy, and investing in it will bring value," says Daniel Fisher, Principal at KPMG US Digital Lighthouse and co-author of the Global Tech Report.

One of AI’s main applications in the sector is in real-time energy management.

AI can monitor the grid in real time, identifying imbalances and adjusting power flow to prevent overloads and blackouts.

It can also automatically reroute energy or isolate affected areas quickly in case of a fault, which could minimise the impact of outages.

AI can also manage energy demand by optimising consumption patterns incentivising users to shift their energy usage during peak periods.

This would help to balance the intermittency of renewable energy sources. 

"June can be an interesting time of year in Europe," explains John McCalla-Leacy, KPMG's Global Head of ESG. 

"It can be both windy and very sunny, meaning lots of renewable energy, but other times, we don't have what we need. AI can play a crucial role in getting that energy to the right place."

Cautious curiosity: The energy sector’s relationship with AI

Despite all the enthusiasm, energy companies are taking a rather measured approach to AI implementation. 

KPMG's report reveals that 33% of energy companies remain in the ‘proof-of-concept’ stage for AI experimentation, piloting the technologies before committing to rolling them out. 

Still, this is 8% higher than the cross-sector average, which shows that the energy sector is open to new ideas.

"Energy executives are showing an increased interest in AI," explains Daniel. 

"But while they're eager to explore AI's potential, there are three main factors tempering the pace of their adoption."

First, the sector is wary of maximising the value of its investments. 

Having been early adopters of enterprise resource planning systems, energy companies are today facing some challenges in modernising entrenched infrastructure to access the cloud capabilities necessary for AI projects.

Secondly, many companies that begin implementing AI struggle to scale it across operations, simply because they fail to sufficiently redesign the roles and processes involved. 

Then, there’s the issue of data.

"Many energy firms lack robust, unified data foundations, which hinders their ability to benefit fully from AI's capabilities," Daniel explains.

Nevertheless, 67% of energy executives report already seeing business value from AI implementations. 

One prominent application is predictive maintenance, where AI continuously monitors electrical grid performance to identify potential failures before they occur, which can hugely improve reliability for energy companies and their customers.

Is AI an adversary or ally of decarbonisation?

John describes AI as "neither friend nor foe", but rather "a tool that we can all use”. 

“We should ensure we use it ethically and in the right way," he posits. 

This sentiment echoes throughout KPMG's analysis, acknowledging both AI's potential benefits and risks.

Sushant Rabra, Partner at KPMG India, calls AI "a double-edged sword, both an adversary and ally of decarbonisation." 

The technology itself consumes significant power, raising concerns about its energy footprint. 

However, John believes AI "has the ability to have a net benefit – if managed appropriately – optimising grid management and improving the integration of renewable energy."

The energy sector’s relationship with AI is still in its infancy, but the opportunities are evident. 

"AI holds the promise to bring new business and operating models, optimise energy usage and drive the scale-up of renewables," explains Sushant. 

“The energy sector is optimistic about AI's potential to enhance efficiency, productivity and security,” he says.

To read the full article in the magazine, click HERE.

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