India Energy Week 2025 (IEW) brought together more than 70,000 of the world’s energy professionals from 120 countries.

The world’s second largest energy event — and the first of 2025 —has grown significantly, more than doubling in size from the 30,000 that attended the second iteration in Goa in 2024.

This year’s edition featured more than 350 exhibitors and 400 international speakers, showcasing not only India's pioneering approach to diversifying its energy mix but India’s place in the world’s energy landscape. 

From biofuels to carbon capture and refining to investment, no stone was unturned.

Speaking on the subject of technology, IEW’s Harnessing AI and Digitalisation to Reach the New Frontier for Clean Energy panel saw leaders from technology and energy applications came together to discuss how rapid digital advances, such as generative AI, hold immense potential to revolutionise energy value chains, carbon intensive industries and entire economies.

Moderated by Energy Digital Editor Maya Derrick, Honeywell President & CEO of Global Regions Anant Maheshwari, Capgemini’s EVP Global Energy Transition and Utilities Industry Leader James Forrest and Saravan Penubarthi, CTO of AIQ shed light on AI’s contribution to the energy space, the challenges faced across industries and how energy and technology will continue to coexist and grow together.

Here, Energy Digital shares some of the panel’s highlights.

Speaker 1: Anant Maheshawri

Speaker 2: James Forrest

Speaker 3: Saravan Penubarthi

Question 1: Where are we in this journey where energy, AI and digitalisation mesh together?

Saravan:

I think the topic is red hot. AI is everywhere, but particularly in the energy industry. We have far gone the stage of innovation. We are, right now, at the stage of scaling and very soon you will see the stage of Agentic AI. 

AI in energy started as an augmented intelligence to give us better insights. 

But then slowly it moved into autonomous operations, where you can actually see the operations being tackled by AI at the site without any human intervention. What we are seeing right now is this accelerating, meaning we have gone forward to the stage of robotic process automation. Right now, you can have agents at every point of the energy value chain, right from subsurface interpretation and all the way to the transportation piece. This trend is becoming a reality.

We at AIQ have already done this and are doing this as we speak in our own group of companies.

James:

We're on the cusp of a revolution and that AI in energy could be as important as the invention of electricity in the first place. AI is used extensively at the moment in forecasting, trading and in optimising the grid on the utilities side, it’s also optimising batteries. We’re past the proof of value stage.

Anant:

There’s a lot of resonance in terms of what the opportunity is, but I first want to come from the perspective of the industry. Why do this? What's the outcome and the value of doing this? It's a great buzzword and folks in technology can get very excited to take the next level of innovation, but it’s about increasing the throughput and productivity of our energy assets. 

The world needs a lot more energy and therefore the more you can do with what you have, the better. Safety is very, very important. I think the one thing that is not recognised more deeply and it gets a lot lost in the debate is why do it? Skills shortages are also why you need it. This is not about AI replacing humans, but AI truly augmenting humans. 

Today, with the support of AI, you can have an operator with two years of experience operate like one which seems like it has 20 years of experience — and therefore creating that capability to bring a lot more people into the workflow.

Finally, I think AI aids innovation. With the energy transition, a lot of new opportunities are opening up and the use of AI can accelerate the different pathways that you can look at, both with the existing energy assets and the new ones that are coming through.

Question 2: How far have we come in using AI and digitalisation to push clean energy?

Saravan:

It's about energy for AI and AI for energy. Energy and AI are two things which can't be separated. For AI, you need energy. For energy efficiency, there is no other technology than AI that can bring it in terms of accelerating gains than the traditional technology. We believe at AID and ADNOC it’s not a notion but a programme for us every day. It's energy for AI and AI for energy.

James:

I think 2024 is when AI woke up to energy. It's a hot topic in terms of how much energy AI uses, but I think you have to be very careful of the forecasts of usage. That, for me, is exemplified by the huge range — by 2030, some people are saying it's a 35% increase from AI, some people are saying it's 250%. There's a massive range there.

I think the data centre load will end up being built in the US up to 2030, probably about 45GW, but I think you also have to keep a close eye on efficiency. There's been huge advances. The latest NVIDIA processes claim a 25% reduction in energy. There's Koomey's law which shows that over the 10 years the efficiency of compute has doubled and gotten better every 18 months. It's difficult to predict all of that and how there’s so much innovation and efficiency.

Even if you get to 4% of global energy from AI, AI will have a massive impact in reducing that energy and reducing energy demand. You have to put all of that together when it comes to the whole demand for energy question.

Question 3: What are the big challenges when it comes to adopting this kind of tech to bring in clean energy?

Anant:

The one challenge that I think all of us recognise — but don't understand too much in the context of operating assets in the energy industry — is cyber. A lot of the design of technology infrastructure is very well covered by cyber, but the operations technology is very different today. There's a lot of challenge in connecting operating assets because at the end of the day, you need to capture that data, which is in islands inside the operating assets. As soon as you start connecting it, you are opening the door to get the data as well as to these cyber risks. These operating assets are not just high value but they're also potentially high damage and therefore you've got to think through the cyber risks right at the outset. 

As you design AI, there's a lot of opportunity, but there's a lot of potential downsides.

James:

There's not really a decent governance framework yet around AI.

And related to that, the legal implications of decisions made by AI are not fully understood yet. I think there's more work needs to be done on what happens if AI makes a mistake — who's responsible for that properly. This is a challenge. 

There's still a lot of talk in the media about the accuracy of AI. That's maybe a training issue, maybe it's to do with how you use the models exactly, but there is definitely a perception of accuracy that needs to be addressed quite quickly as we go through. 

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

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