Cheetah was not the fastest, AI feels like more work and more….

Hey people!

If asked to name the fastest land animal, chances are you’ll say cheetah without blinking. And you will be right.

But here is the interesting part.

For a long time, scientists believed that the story of speed, at least in North America, belonged not only to the cheetah, but to something completely different – the American pronghorn.

The general explanation was like this. Millions of years ago, an animal often referred to as the “American cheetah” roamed the continent. And he hunted the pronghorn.

The pronghorn, in turn, had to run faster and faster to survive. Over time, this evolutionary trait turned the pronghorn into one of the fastest land animals. A neat predator-prey story that is almost cinematic.

Except new research suggests it may not have happened that way at all.

A recent study from the University of Michigan took a close look at fossils of ancient relatives of the pronghorn. They specifically studied a bone called the astragalus in the ankle, which plays an important role in movement and running efficiency.

And what they found upended that old narrative. The fossils come from the Dove Spring Formation in California’s Mojave Desert, a site that preserves remains from about 12.5 million years ago.

Back then, the American cheetah never existed. In other words, the pronghorn was fast long before it had anything like a cheetah to run.

That alone changes the story. But it gets better.

When researchers compared the bone proportions of those ancient species to modern pronghorn, they looked remarkably similar.

So why were they so fast when they had no predator to run from?

One possibility is that speed was less about outrunning a single predator and more about flexibility. In a changing environment, the ability to travel long distances efficiently can mean finding food, water or a safer habitat faster than competitors.

So yes, the pronghorn didn’t become fast because a cheetah forced it to. It was fast because the world at the time rewarded it long before a predator arrived.

Here’s a soundtrack to get you in the mood…

Awake by Black Letters recommended by Sarang Menon

What caught our eye this week

Why AI feels like more work

When you first started using AI, it probably felt like cheating—in a good way. Emails took seconds. Drafts wrote itself. Boring tasks disappeared behind a flashing cursor. For once, work felt lighter.

And then something strange happened.

The time you saved did not turn into free time. This turned into more work. Faster deadlines. Higher expectations. And a tacit assumption that if AI could do this, you should be able to do even more.

This is the argument of a recent Harvard Business Review report. AI, it says, does not reduce work. It amplifies it – reshaping productivity, expectations and power within organizations in ways most companies didn’t anticipate.

Most of us signed up for AI tools with one simple goal: to make work easier. And at first they did. The small victories came quickly. Doing the work of a full team with a handful of subscriptions no longer felt over the top.

Work boundaries blur. A project manager can also code. A writer could design. With each assignment, roles expanded and expectations followed.

Once it became the norm, it didn’t stay personal. Drivers noticed. What started as a “nice to have” quickly became the baseline. AI didn’t just speed up work. It was to redefine what normal output was equal.

To see if this shift was real or merely anecdotal, researchers behind the HBR study observed hundreds of knowledge workers as AI tools entered their daily workflows. Instead of lab experiments or simulations, they focused on real jobs, real tasks and real deadlines.

The assumption was simple. If AI made humans faster, workloads should shrink. Deadlines must be relaxed. Working days should become shorter.

But that is not what happened.

Across roles and industries, AI has improved efficiency. But the time saved rarely translated into less work. Instead, expectations rose. More tasks were assigned. And projects expanded.

AI has not eliminated jobs. It redefined how much work was considered reasonable.

Think of it like ordering a pizza.

The app says it will arrive in 30 minutes. Seems fair. You plan around it. Then, by some miracle, the delivery appears in 15. You are impressed. You can even leave a better rating.

But the next time you order, you no longer expect 30 minutes. You expect 15. And when it shows up in 30, it suddenly feels late – even if nothing went wrong.

Now imagine that the restaurant is quietly updating its internal targets. Delivery partners face tighter timelines. More orders are stacked per rider. What was once an exception is becoming the standard.

This is what AI did to work.

This is not just a metaphor. The data backs it up.

In the Harvard Business Review study, researchers followed approximately 200 employees over nine months as AI tools became part of their everyday work, even though their employer did not make AI use mandatory. It tracked what happened after AI stopped feeling novel and started feeling normal.

The pattern was consistent. Employees completed tasks faster and produced more output. But the time saved did not translate into lighter workloads. Instead, they quickly reinvested in more assignments, which sometimes even translated into longer workdays. This is simply because doing more felt possible and also rewarding. Apparently, employees even shifted work in moments they previously designated as breaks, because they felt that with a few final instructions, AI could work in the background while they were gone. But since it misled the organizational line of employees, it simply meant more workload and unrealistic expectations.

AI, in other words, behaved exactly like that early pizza delivery. The first time felt like a bonus. Then it quietly resets expectations.

So where does that leave us?

Well, for starters, AI isn’t the problem. Unspoken expectations are.

If companies treat AI-driven efficiency as an individual performance upgrade, workloads will continue to expand. Faster tools will simply justify more work. But if organizations treat AI as something that lifts the system rather than pushing the worker, the outcome changes.

This means explicitly resetting the benchmarks instead of quietly raising them. Deciding up front where efficiency gains should go – better quality, deeper thinking, or yes, sometimes, less work, instead of letting “more output” become the standard.

If left on autopilot, AI will not give us back time. It will only make us deliver the same pizza faster, and then wonder why 30 minutes no longer feels acceptable.

Infographics

We’ve seen Formula 1 cars filled with a number of logos and advertisements all around. But have you ever wondered how much it costs to be there?

Readers’ Recommendation: Don’t Lose Your Mind, Lose Your Weight by Rujuta Diwekar recommended by Nidhi Dhanani

This is a diet book by Rujuta Diwekar, a renowned dietician who has guided the likes of Kareena Kapoor and Saif Ali Khan. It’s about how to lose weight without drastically changing your diet through three simple steps.

Thanks for the recommendation, Nidhi!

That’s it from us this week. See you next Sunday!

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