I’ve now spoken with four healthtech founders in the past month who all said a variation of the same thing: “Once the customer sees our AI, it will sell itself.” It’s a dangerous and misleading mindset.
They’re right because, in each instance, the tech itself was pretty fucking cool. And yet, they’re wrong at the same time.In fact, it’s a pretty widespread phenomenon with founders who are so passionate and who believe so deeply in the tech they’ve built that they come to believe that it’s natural that anyone who sees it will obviously agree to buy it. “It makes them X times more productive.” Or “it allows them to develop Y new treatments that they couldn’t do before.”
Who wouldn’t want to buy it?
Two of the companies were looking to sell into enterprise-scale pharma companies, and the other two into large provider systems. In each case, they had spoken to their target audiences within those entities who all expressed enthusiasm and promised “rapid” adoption.
Here’s the problem: enterprise health buyers aren’t like you. And that’s the point.
That early, positive feedback, while great for future prospects of these companies, can also lead to unrealistic expectations. “Rapid adoption” for these organizations means something completely different than it does for the sellers. In three of these four conversations, I cautioned the founders about the realities of selling healthtech into enterprises. It’s complex. It’s lengthy. It’s far more rigid and difficult than it might seem, especially in the context of positive feedback from the ICP/users. It’s not going to be a 2-month transactional sale. You’re wading into a 12+ month purchasing journey.
Anyone selling into providers or enterprise life sciences has to understand the following obstacles.
Budget cycles:
First of all, these types of organizations operate on defined budget cycles. Just because someone likes your solution doesn’t mean they are able to purchase it right away. They may have to wait eight more months just to get into the budget cycle, at which point the long evaluation process actually begins.
Complex buying groups:
Moreover, it’s never one person’s decision. You are selling into a system with large buying committees, often composed of 20+ persons across multiple departments: the purchasing department itself PLUS InfoSec / IT, Legal, Procurement / Finance, Regulatory, Legal, etc. Those other department’s main job is to find reasons NOT to purchase your tool. And they all wield veto power. We’re talking about very conservative organizations operating in highly regulated industries. That old adage about “No one gets fired for buying IBM” is still true in the era of AI. Caution is the default position, and speed to purchasing is often associated with recklessness.
Regulations and industry standards:
HIPAA, GDPR, CCPA, ICH, GCDMP, GxP, FHIR, CDISC, HL7 and dozens of other acronym-laden rules, regulations, and industry standards must be adhered to. These aren’t nice to haves. They are 100% must haves. And your tech must be flexible enough to also accommodate potential future requirements as well. The healthcare buyer has more IT, privacy and security protocols to deal with than pretty much any other industry. Little wonder why those buying committees are so skeptical. And you can be sure that all of that caution doubles when AI is involved.
Competing priorities:
One of the founders said “We don’t have any competitors.” But they do, even if it’s not obvious. At any one time, those enterprise orgs have dozens of vendors pitching them their AI solutions. Even if not directly competitive, the org is already evaluating multiple tools. They can only absorb so much. And there are only so many dollars to go around. So even if there is no directly competitive tool, there is plenty of competition for dollars and attention. There is no such thing as a competition-less product in this industry.
Relationship-based sales:
Selling into large orgs like this is never transactional. The sales cycle typically takes 12-18 months. I’ve personally been on two 18+ month sales processes. Over that period of time, there will be plenty of turnover, both from the buyer and the seller. Developing and maintaining positive relationships over such a timeframe is complex. People get promoted, move departments, or leave the org all together. Champions one day are no longer relevant the next.
And it’s not just a matter of longevity. There are all types of internal politics and power centers involved, which the selling company is often not privy to. You may have the best solution in the world, but if a key stakeholder prefers another tool or hates your champion, well good luck….
Rip and replace, and the curse of user adoption:
Finally, remember that even when they actively want your AI, they still have to deal with the legacy system, the organizational inertia, and the training/adoption curve. Plenty of tools have made it through the purchasing gauntlet only to come crashing into the user’s reluctance to deal with yet another tool or system. Lack of adoption among users is real. No one wants to deal with yet another password, yet more tools to figure out, yet another workflow to incorporate. Especially if it’s imposed upon them from above.
None of this is to say that you shouldn’t sell into large providers or big pharma. It’s to caution that expectations ought to be realistic. And to have a process based on proven best practices rather than hopes and vision. We’ll get into that in the next article…
FAQ
Q. Isn’t great AI tech enough to win enterprise buyers in healthcare or pharma?
A. Not even close. Enterprise buyers care just as much (if not more) about risk, compliance, budget cycles, and internal politics as they do about product features. Cool tech doesn’t eliminate those hurdles.
Q. Why is early enthusiasm from buyers often misleading?
A. Because “rapid adoption” in enterprise healthcare means 12–18 months—not a quick win. Positive feedback is good, but it doesn’t equal budget approval or procurement alignment.
Q. What makes selling into large healthcare systems or pharma so complex?
A. You’re up against:
Long budget cycles
20+ person buying committees
Regulatory minefields (HIPAA, GDPR, GxP, etc.)
Internal politics
Legacy systems
Competing vendor noiseEven if your tech is unique, you’re always competing—for time, dollars, and attention.
Q. What’s the real challenge after making the sale?
A. User adoption. Even with leadership buy-in, end users often resist new tools—especially if they disrupt workflows, require new logins, or feel top-down. Many great products fail after the deal due to lack of buy-in on the ground.
Q. So what should healthtech founders do differently?
A. Adjust expectations, build for long sales cycles, and focus on relationship-driven selling. Understand the buyer’s world, anticipate friction points, and invest in enablement and post-sale adoption strategies. Great tech helps—but process wins deals.
