The Coal Problem: Why AI Never Actually Saves You Time

Opening

Let me ask you something. Since you started using AI at work, has it actually gotten you out the door earlier?

I use AI pretty aggressively myself — for writing, research, organizing all kinds of things. Individual tasks are undeniably faster now. Something that used to take an hour now takes 15 minutes. And yet, strangely, my leaving time hasn’t budged. If anything, it feels like I’m getting out later.

I wondered if it was just me, when a study published in the Harvard Business Review (HBR) this past February landed a direct hit on the question. Associate Professor Aruna Ranganathan of UC Berkeley’s Haas School of Business and doctoral researcher Xinqi Maggie Ye spent eight months closely tracking a US tech company. Their conclusion gave me chills: the people using AI most enthusiastically are the very ones burning out first.

Today, I want to cross this study with a 160-year-old piece of economic theory to explain why AI is making us busier — and how we might actually escape the trap.

What 160-Year-Old Coal Can Teach Us

To understand this, we first need to travel back to England in 1865.

The economist William Stanley Jevons discovered something strange at the time. James Watt’s steam engine had dramatically improved coal efficiency — and common sense says coal consumption should have dropped, since the same amount of coal now did more work. But the result was the exact opposite. As efficiency rose, the cost of using coal fell; as costs fell, people built more factories, ran more trains, and found new uses for coal. Consumption exploded instead.

This is the ‘Jevons Paradox’¹​. Put simply, it’s the same logic as widening a highway expecting less traffic, only to have even more cars pour in and clog it right back up. The same thing happened when LED lighting spread and lighting usage actually rose, or when the internet made communication more efficient and total communication volume exploded.

And this 160-year-old paradox is at work again today. When the DeepSeek incident hit in January 2025, Microsoft CEO Satya Nadella posted on social media: “Jevons Paradox strikes again! As AI gets more efficient and accessible, usage will skyrocket.” Coal has simply been swapped for AI — the structure is identical.

But what caught my attention is that the ‘usage’ Nadella is talking about isn’t just API call counts. A surge in AI usage means a surge in the volume and density of the work we’re actually doing. And the UC Berkeley study captured exactly this.