With AI, The Tech Is Different. The Challenges of Selling It Are Not.
Over the past few years, I’ve worked with AI founders in healthcare, professional services, construction, GovCon, supply chain and other markets.
The products are different. The sales problems usually aren’t.
In AI sales, founders often start by proving the technology. Enterprise buyers are trying to decide something else:
Is the problem important enough to fund?
Will the outcome show up in revenue, cost, risk or capacity?
Is there a strong enough business case?
Is this a vendor we can safely bet on?
And what has to happen internally before anyone can actually say yes?
That’s where I’ve seen a lot of AI companies get stuck.
The technology may work, but the business case isn’t clear, the risk of buying from a smaller vendor hasn’t been addressed, or the champion isn’t equipped to get the decision through the company.
What I’ve seen change
I’ve helped founders make that shift in different ways.
One stopped leading with the technology and started showing the business outcome.
Another narrowed a broad platform to one painful workflow a CFO was already trying to fix.
Another stopped trying to replace an incumbent and focused on the problems the customer still needed solved.
One closed a $30K pilot. The next day, the company received a $300K investment. Amazing how a paying customer is a very different signal than a promising demo.
And an AI-native breast cancer detection client built a repeatable sales model around helping hospital systems increase patient volume and revenue. The company was later acquired.
A successful pilot can still become a dead end
I’ve seen promising deals go quiet when the seller thought things were going well.
The demo worked. The buyer liked it. The pilot went well.
But the economic case, decision owner, security and procurement path, or move to production still wasn’t clear.
A pilot isn’t the finish line. It should be designed around the production decision.
I don’t measure deal progress by seller activity. I measure it by what the buyer has actually done. Have they brought in the right stakeholders, built the business case, identified budget, or started the steps required to buy? Those are much better signals than another good meeting or demo.
Three questions AI founders need to answer early
Is the outcome worth funding?
What improves financially or operationally?
Are we a vendor they can safely bet on?
Can we support deployment, security, adoption and scale? And do the economics still work as usage, token and compute costs grow?
Can the buyer actually get this bought?
Who owns the outcome, who controls the money, who can block it, and what happens next?
The hard part often isn’t whether the AI works.
It’s whether the outcome matters enough to fund, the vendor is viable enough to trust, and the customer can actually make the decision.
That’s when interesting technology starts turning into revenue and cool products evolve into investable companies.
If you’re an AI founder and the technology is working but buyers still aren’t making decisions, that’s the problem I spend a lot of time helping solve.
If that sounds familiar, let’s talk.
About Mark
Mark Phinick is the founder of Let’s Make It Rain, and a B2B Deal Coach who works directly with founders, sales leaders, and sellers inside live enterprise opportunities that aren’t moving.
He coaches reps and selling founders on what’s blocking a deal’s decision, quantify financial impact, equip champions to build internal support, and turn buyer interest into revenue.
Bring me the deal that’s not moving.