The Energy Industry Doesn’t Have a Talent Shortage. It Has a Leverage Shortage.

CX on-invitation Newsletter: Ruchir Punjabi:

Most leaders in energy I speak with bring up the talent gap. The numbers get quoted, not enough engineers, a war for talent with tech companies. I think this framing is mostly wrong, and it leads companies to hire badly.

The real story is different: energy is quietly becoming a software industry that happens to install hardware. And in today’s technology landscape, the question is not how many people you can hire, it is how much each person can do.

The industry changed. The org charts didn’t.

We finance, build, and operate solar and battery systems for businesses across India and Africa. A decade ago, a business like ours would have been organised like a construction company: project managers, site engineers, liaison officers, layers of supervision.

Look at where the value actually sits today. A solar plant is built once and then operated for twenty years. The margin lives or dies on those twenty years: performance monitoring, fault detection, generation forecasting, billing, battery dispatch. Every one of those is a data problem. The panels and inverters are increasingly commodities. The intelligence layer on top of them is not.

That is why we built Atlas, our own monitoring and operations platform, rather than treating software as something you buy from a vendor. Once your operations run on software, the profile of the people you need changes completely.

The scarce person bridges electrons and code

The talent everyone fights over is the electrical engineer with ten years in solar. The talent that actually moves the needle is rarer and mostly ignored by job descriptions: the person who understands both the physics and the software.

Someone who knows why an inverter clips and can also spin up an agent that finds every site where it is happening. Someone who understands a power purchase agreement commercially and can model its cash flows without waiting for an analyst. These people are almost never produced by energy companies, because energy companies still train specialists for one box on the org chart. They come from fintech, logistics, SaaS, anywhere people learn to treat operations as a data problem.

My own path shaped this view. I spent my first career building a digital business, Langoor, which I later exited. When I moved into energy, the biggest surprise was not the technical complexity. It was how little of the digital operating model had crossed over. Practices that were standard in tech in 2015, instrumenting everything, automating reporting, shipping improvements weekly, were exotic in energy in 2020. Much of that gap remains, which means the opportunity does too.

AI collapses the pyramid

Now add AI, and the argument becomes urgent.

The traditional energy company is a pyramid: a few decision-makers on top of a large base of people doing analysis, documentation, monitoring, and coordination. AI eats the middle of that pyramid first. Performance reports that took an engineer a day now take minutes. Regulatory research across multiple markets, first drafts of contracts, tender analysis, fault triage: all of it compresses.

We operate across 7 countries, each with its own regulators, currencies, and grid quirks. On the old model that footprint demands a country office and a full team in each market. We run it with small teams because AI carries work that used to need departments. I use these tools daily myself, for regulatory research, financial modelling, and first drafts of almost everything. Not because it is fashionable, but because the alternative is hiring ten people to do what two people with good tools do better.

This is what I mean by a leverage shortage. Most energy companies are still staffed as if every analysis needs an analyst and every report needs a reporter. Their talent problem is not that they cannot find people. It is that they need far fewer people than they think, of a different kind than they are looking for.

What to hire for now

If I were building an energy team today, I would change three defaults.

First, hire generalists who compound. The specialist’s knowledge is increasingly available to everyone through AI. What cannot be downloaded is judgment: knowing which question matters, spotting the number that looks wrong, deciding under ambiguity. One curious generalist with strong tools now outperforms a department of narrow specialists in most functions outside core engineering.

Second, treat AI fluency like Excel fluency in 1995. Not a specialist skill, a baseline. The gap between someone who uses these tools daily and someone who does not is already a multiple, not a percentage, and it widens every quarter. I would test for it in interviews the way we once tested for spreadsheet skills.

Third, recruit from outside the industry, deliberately. Energy knowledge can be taught in months. The instinct to automate, instrument, and question how things are done takes years to build and is best learned in industries that were forced to learn it earlier.

The energy transition needs an enormous amount of building: in India, across Africa, everywhere demand is growing rapidly. But it will not be built by the giant workforces the panels keep forecasting. It will be built by small, dense teams with very high leverage per person. The companies that understand this will out-execute the ones still hiring for the industry that existed ten years ago.

About Ruchir and Distributed Energy

Ruchir Punjabi is Co-Founder & CEO of Distributed Energy (de.energy), an AI-first distributed utility. DE finances, builds and operates solar and battery systems for businesses in India and Africa. A serial founder, he previously built and sold the digital agency Langoor, and co-founded the School of Policy and Governance, renewables.org and the Zero Prize.

The CX Founder & Industry Voices Series: CareerXperts brings together founders / Industry leaders to share their perspectives on building from 0→1, hiring and building teams, and the talent realities shaping their industries.

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