Performance, not promise: The real AI premium in medtech
To view this article on the Today’s Medical Developments Magazine website, click here.
Artificial intelligence (AI) shows up everywhere in medtech right now. It’s in roadmaps, investor decks, and enough booth signage to make you think every device has a neural network inside it. The implied message is familiar: AI should mean higher valuation.
In real deal work, buyers are more careful than that.
Most buyers aren’t paying more simply because a company can truthfully say it uses AI. They pay more when AI changes the business in a way that shows up in economics and stays there. That usually means one of three things: stronger pricing power, more durable recurring revenue, or a margin profile that improves instead of drifting the wrong direction.
Diligence reflects that shift. When buyers get serious, the questions stop sounding like product marketing and start sounding like underwriting. What, specifically, gets better because of this capability? Do customers adopt it and keep using it? Does it reduce friction in a workflow that matters? Does it change the customer’s willingness to pay? And a question coming up more often than founders expect: what did it cost to build and maintain, and what are we getting back for that spend?
That last point is important because AI is rarely a one-time investment. Even when the product works, the capability often requires ongoing data work, model monitoring, validation updates, and engineering attention. Buyers don’t hate investment. They hate investment with unclear return.
The Philips SpectraWAVE deal is a useful illustration of when AI can matter in valuation without being the whole story. Philips agreed to acquire SpectraWAVE, whose platform integrates AI-enabled intravascular imaging and physiological assessment. The strategic logic isn’t that Philips bought an algorithm. It’s that Philips strengthened a broader image guided therapy ecosystem with intelligence embedded into a clinical workflow. That matters because workflow integration, clinical confidence, and platform pull through are economic levers. In the right category, that can translate into adoption, utilization, and longer-term defensibility.
On the manufacturing side, AI value tends to be less about clinical differentiation and more about operational outcomes. Siemens acquired Inspekto, an AI-driven machine vision company focused on automated visual inspection. You don’t need to stretch to see the economic rationale. Inspection and quality control are direct inputs to cost, yield, and scalability. If AI enables more consistent inspection, fewer escapes, and less rework, it can support gross margin. It can also make growth less dependent on adding headcount at the same pace as production volume.
That’s where the conversation becomes more grounded. Manufacturing-related AI doesn’t usually create a valuation premium because it sounds exciting. It can contribute to value because it improves performance in ways buyers can underwrite.
This is also where some companies get surprised. Many teams invest heavily in internal AI initiatives, then assume the mere presence of that capability will be rewarded in valuation. Buyers tend to separate effort from impact. If AI supports subscription analytics, improves service attach rates, reduces support burden, or drives clear operational leverage, it strengthens underwriting. If it adds cost and complexity without changing adoption, pricing, or margins, buyers may treat it as a drag rather than a moat.
In other words, the market has moved past paying for promise alone. Buyers still like AI, but they want proof. Proof looks like retained customers, measurable workflow wins, margin improvement, or a recurring revenue stream that grows without requiring an ever-expanding engineering budget to sustain it.
That is the real AI premium in medtech. It’s not automatic, and it is not emotional. It’s economic.
If AI strengthens margins, supports durable recurring revenue, or creates defensible differentiation driving adoption, buyers will pay attention. If it functions mostly as a feature set with an ongoing cost structure and unclear return, valuation rarely moves.
In a disciplined transaction market, performance – not promise – determines premium.
To view this article on the Today’s Medical Developments Magazine website, click here.
