Everyone Has AI Now. So What’s Left?

Kirkland & Ellis committed $500M to build its own AI platform. They’re doing it while still licensing the same frontier models everyone can rent tomorrow. So why spend millions more?

The platform is being designed around the knowledge of approximately 250 of their lawyers. That’s the one thing a competitor can’t download.

Now consider this: the pressure to build an edge on top of commodity intelligence runs all the way down: to every org, every team, and each ONE of us.

Which is why this week’s other announcement matters.

NVIDIA and Microsoft just teased “a new era of PC” with Arm-based chips. This will put frontier-grade AI directly on the machine in front of you, including running agents locally instead of in the cloud.

Kirkland is doing it with half a billion dollars. The AI PC is about to hand the rest of us the same capability at the scale of a single desk.

Intelligence is becoming ambient, abundant, and local.

That’s the shift: intelligence is turning into infrastructure. And once something is infrastructure on every desk and in every tool, having it stops being an advantage.

We’re already living it.

Everyone sounds like ChatGPT, and writing is rife with Claudisms.

So the advantage migrates to the three things abundance cannot flatten:

→ Proprietary inputs.

A model trained on the internet gives you internet-average output. Mediocrity is free. Extraordinary holds its value and that comes from lived experience, something ONLY you can deliver.

→ Trust.

Generation is now more or less free. But knowing which of the 100 outputs is the right one? Trust becomes the product. Thomson Reuters even put a name to it: “fiduciary-grade AI.” When liability is on the line, “almost right” just isn’t enough.

→ A point of view.

AI is a consensus machine, optimized for the most probable, least objectionable answer. The edge now lies in anti-correlation with the mean. It lies in the ideas the model would never volunteer.

When the tools are everywhere, having them won’t set you apart. What you feed them and how you wield them will.

And I believe that’s the most democratic edge there has ever been. Because the hard part is your data: scattered, messy, locked in silos and PDFs and people’s heads.

Kirkland is spending half a billion dollars precisely because turning proprietary knowledge into usable intelligence is extremely hard. If it were easy, it wouldn’t be an edge.

Yes, eventually the machine will clean your data, it may mimic your style, and it can match every pattern in the book. It will out-search you on any defined problem.

So stop competing there.

It can’t live the experience that makes data worth having. It can’t make the call when the pattern runs out and the consequences are yours. Inside the game, the machine will out-think you. It just can’t tell you which game to play.

And the future of work spells opportunity for EXACTLY that. Until next time,

Ram — 

Ram Srinivasan

MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.

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Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Exponential Human."

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