BCG: "for many, the real risk in AI isn't spending too much; often, it's spending too little."
Wanting a business case isn't the mistake. Building it from someone else's numbers is.
I've built over 60 AI use cases. I've now taken the layer they were all built on out of production.
Companies are heading toward their own AI layer inside the business.
Tooling gets replaced every few months.
The layer underneath shouldn't.
Cut the grass = trim every edge, miss no patch.
Make it through special forces = get selected as chairman of the course.
Write the master's thesis = sell it to a listed company.
Build the deck = make it art.
Every one had a standard someone else already set.
The mental model that made me successful is the exact thing that made going from 0 to 1 hell.
"Do it once well and you don't need to do it twice."
That works everywhere someone else has already defined what "perfect" is.
When nobody has, momentum is what finds it...
AI is merely leverage.
Leverage something broken, and you'll make it worse.
Leverage something functional, and you'll make it better.
AI can accelerate a process. It can't fix a fundamentally broken one.
Ask what actually works today, and how could AI make it 5x better.
There will be 3 types of companies:
Purists ban AI on paper, staff uses it on personal accounts anyway
Automatons outsource decisions until nobody can maintain the outcome that everybody depends on
Renaissance AI carries the volume, expanding capability, people keep judgment
There will be 3 types of people in the future:
The Purists - reject AI and become new-age hippies
The Automatons - outsource every decision and become machines
The New Renaissance Man - maintains humanity and leverages tech to do what used to be impossible
Stripe is reportedly placing a $7B bet on where AI is heading.
The bet: no business will stay on one AI provider for long.
A new flagship AI model has launched every 5 to 6 days over the past year. Picking the eventual winner is impossible.
Second acquisition of its kind. The first went for $140M, three months after it raised $15M .
Stripe bought OpenRouter, which essentially removes the need to get married to one LLM provider.
I cancelled everything I had planned for tonight.
Anthropic reset the rate limits for every user.
So I'm working tonight.
I've made peace with what that says about me.
I cancelled everything I had planned for tonight.
Anthropic reset the rate limits for every user.
So I'm working tonight.
I've made peace with what that says about me.
them: "I think we could cut headcount because of AI"
me: "Nah, you should do the opposite"
Most companies should be using AI to increase headcount.
The parts of your business that already work usually work because of how specific people do them.
Replacing those people...
Three questions before any AI investment:
What can AI really do here?
What would it take?
Do the two line up?
No business is too unique for AI. The task is to find where it brings leverage, and where it brings chaos.
A broccoli farmer in Japan automated his 100-hectare farm with AI, with no engineering background.
He achieved this by asking what almost nobody does: will this actually move the business?
Cool and useful are not the same thing.
Want to come out of this AI shift ahead instead of behind?
It comes down to a few moves:
expand your skill tree,
become the one people turn to on AI,
and start building with it.
Hands-on experience is the edge. You can start all three this week.
The biggest gap I see inside companies right now is the ability to talk things into existence.
The people who can actually build with AI are becoming the most important people in the building.
Take the task that eats your day, ask AI to automate part of it, then build it.
Job requirements have always shifted.
The speed of the shift right now is what people underestimate.
AI will not replace you, but you will be replaced by someone who knows how to use it.
Stay current by building the judgment: what AI can do, and where it fits.
Knowing when and where to implement AI matters more than knowing how.
It sounds simple, and it's the thing most companies get wrong.
Most see zero measurable return on their AI spend, and it comes down to acting without a clear read on what AI can and can't do for them.