The Human Grid: Technology Will Accelerate the Energy Transition. People Will Determine Whether It Works.
AI, automation, digital twins, advanced analytics and predictive modelling are going to change the energy industry. They will allow organisations to process more information, model more scenarios and make decisions faster than ever before. But there is an important distinction between making decisions faster and making better decisions, and that is where people come in.
For all the discussion about AI replacing jobs, I think the more interesting question for the energy sector is which human skills and capabilities technology will make even more valuable. Judgement, curiosity, communication, commercial thinking, empathy and the ability to connect different perspectives may matter more as technology becomes more capable.
The energy transition is already incredibly complex. Network constraints, community expectations, market prices, project economics, regulation, construction risk and system reliability all interact. AI can analyse those variables at a scale no individual ever could, but somebody still needs to decide what matters. A technically optimal answer is not necessarily the commercially sensible, socially acceptable or ultimately right decision.
I recently spoke with Kate Vidgen on Powering Your Career about AI and the future of work. One of her observations has stayed with me: there are people using AI to learn, explore ideas and feed their curiosity, and others increasingly allowing it to do the thinking for them. Her broader message was simple - educate yourself, use the technology and make sure it improves your thinking rather than replacing it.
That is relevant for anyone building a career in energy. You do not need to become an AI expert, software engineer or data scientist, but I do think technology literacy will increasingly become part of almost every professional role. Understanding what AI can and cannot do, becoming more comfortable with data and knowing how technology could improve your own work will become increasingly important.
Curiosity is a big part of that. Daphne Yao made a great point when talking about developing financial acumen. She described grabbing a financial model, sitting down with someone who understood it and asking them to walk her through it from top to bottom. She did not need to become an accountant; she wanted to understand enough to ask better questions and make better decisions.
I think exactly the same mindset applies to AI and technology. You do not necessarily need to build the model yourself, but you should understand enough to know what sits behind the output, question its assumptions and connect it to the engineering, commercial, operational or customer problem you are trying to solve.
Data literacy is equally important. Jack Curtis from Neara made the point that much of the technology serving energy is “pretty dead on arrival, unless it starts with a good data strategy.” Before organisations become overly excited about AI, they need to get the fundamentals right: accurate, accessible and reliable data.
Jack also offered a useful perspective on AI itself. Rather than expecting technology to make decisions for us, he sees its role as surfacing better information and better options while allowing domain experts to act on that analysis. That feels particularly relevant in energy, where the assets are critical, the decisions are complex and accountability still needs to sit with people.
He also made an important career point. While AI may automate more routine work, developing a strong domain foundation - whether that is engineering, finance, law, technology or another discipline - still matters because those professions teach people how to think, solve problems and develop judgement. Combine that expertise with communication, lateral thinking and an ability to understand people, and you have a skill set that is much harder to automate.
For people working in energy, the opportunity is therefore not simply to learn how to use AI. It is to become better at identifying where technology can genuinely improve the way work gets done. Which repetitive processes could be automated? Where could better data identify a risk earlier? How could AI improve analysis or challenge your thinking? Where could technology free people to spend more time on customers, communities or their teams?
For anyone building a career in energy, my advice would be not to sit on the sidelines waiting to see what AI does to your profession. Get curious about it. Use it. Understand what it can and cannot do. Become more comfortable with data. Sit with people who understand things you do not and ask them to teach you. Continue building strong domain knowledge while developing the judgement, communication and problem-solving skills that technology cannot easily replicate.
The organisations that succeed will not necessarily be those that adopt every new technology first. They will be the ones that combine technology with experienced judgement, strong leadership and people capable of connecting disciplines, organisations and communities.
The physical grid is becoming smarter, and The Human Grid needs to become smarter with it.



