
Why Every AI Startup Needs to Become a Consulting Firm
A couple of years ago, the playbook for AI startups was simple:
Build an API.
Wrap it in some branding.
Tell everyone to “plug it in” and watch the magic happen.
Fast forward to now, and that model is starting to look… limited.
Earlier this month, OpenAI quietly launched a new offering. But it wasn’t another model upgrade or developer tool.
They introduced a consulting arm.
A proper service, for $10M+ enterprise clients.
Not just tech — actual people, flying out to work onsite with large corporates and government organisations to help them implement AI.
It’s a big shift. And it says a lot about where we’re headed.
Big investors are buying this “unlisted” stock
When the founder who sold his last company to Zillow for $120M starts a new venture, people notice. That’s why the same VCs behind Uber and eBay also backed Pacaso. They made $110M+ in gross profit to date. They even reserved the Nasdaq ticker PCSO. Now, you can join, too.
Paid advertisement for Pacaso’s Regulation A offering. Read the offering circular at invest.pacaso.com. Reserving a ticker symbol is not a guarantee that the company will go public. Listing on the NASDAQ is subject to approvals.
Why consulting? Because enterprise AI is a mess.
It’s easy to think building the model is the hard part. But anyone who’s ever tried to sell AI into a large organisation knows: implementation is the real battle.
Corporates move slowly. They’re risk-averse. They have legacy systems, layers of approval, compliance issues, and politics.
So handing over an API key and hoping for adoption? That just doesn’t cut it anymore.
What OpenAI is doing now — embedding engineers into client teams, fine-tuning models, redesigning workflows — is exactly what these companies need.
It’s not glamorous. It doesn’t scale like SaaS.
But it works. And most importantly — it sticks.
I’ve seen the same trend from much smaller players too.
At one of our recent events, Chen Wang, CTO of Fifth Dimension AI, shared how they’re approaching this.
Their space is real estate — full of messy leases, outdated spreadsheets, and incredibly manual workflows. And like many AI teams, they started by building tools on top of existing models.
But it wasn’t enough.
Their clients didn’t just want AI suggestions. They wanted real outcomes:
“Help me process this data faster.”
“Show me which deals to prioritise.”
“Save me time and money — don’t just give me another dashboard.”
So Fifth Dimension built a platform that goes much deeper — integrating with client systems, automating specific tasks, and delivering actual business value.
They didn’t stop at the model.
They rebuilt the workflow.
This is where the bar is now.
The more I talk to founders and investors in this space, the clearer it becomes:
It’s no longer enough to just be “an AI company.”
Most models are starting to feel interchangeable — everyone’s building on similar foundations. GPT-4, Claude, open-source models… they’re all powerful in their own way.
But what will set you apart is:
✅ Who can integrate deeply
✅ Who understands the real-world use case
✅ Who can take something live and deliver results
And that’s rarely just a product play.
It’s about rolling up your sleeves and solving the full problem.
Big players are already going full-stack
OpenAI isn’t alone here.
Google has long been embedding teams through their cloud consulting division.
Palantir basically built their entire business model around deploying engineers to work side-by-side with clients.
And it wouldn’t be a surprise if Meta, Apple, or xAI follow the same route — or start acquiring companies that already know how to do enterprise AI delivery.
Why? Because there’s too much friction between “cool demo” and “real-world usage.”
Whoever can bridge that gap — wins.
So what does this mean for early-stage AI startups?
It means the game is changing.
Founders who want to win in B2B need to think bigger than a feature.
You need to own the outcome.
That might mean packaging your tech with:
Domain expertise
Custom integrations
High-touch support
Or even — yes — consulting
It’s not about becoming a services business forever.
But offering services now might be the fastest route to product-market fit, happy customers, and real revenue.
Consulting is not the goal — it’s the wedge.
Let’s be clear.
OpenAI didn’t wake up and decide they wanted to be Accenture.
They’re not doing this because they love client meetings and corporate politics.
They’re doing it because they want to control the full value chain — from model, to product, to actual business results.
Consulting is just a wedge.
It helps them learn faster, build better, and create stickier relationships.
And if it works for the biggest AI company in the world, maybe it’s worth considering in your go-to-market too.
Final thoughts
This shift won’t apply to every AI business. Some can (and should) stay product-led.
But if your goal is to serve enterprise clients — especially in complex, regulated industries — this move towards full-stack is not optional.
It’s expected.
OpenAI’s new arm shows us one thing clearly:
The future of AI isn’t just technical — it’s operational.
And if you can be the one who makes it all work for your clients —
you’ll be the one who wins.
✅ This isn’t hype — it’s the hard truth about selling AI to real companies. Send it to a founder who needs to hear it.
It’s time for a POLL (👉 Vote now — we’ll share the results in next week’s issue. All votes are anonymous)😀
AI startups that don’t offer consulting will fail. Agree or disagree?
INDUSTRY PULSE 🩺
(Last week’s poll results)
👉 If you’re not willing to work weekends as a founder, should you even be one?

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