What Health Tech Leadership Looks Like in 2026: Lessons from Cera

Three forces rewriting the health tech leadership brief

AI governance is moving from aspiration to accountability. 2026 is the year health systems are expected to move past AI experimentation and into enterprise-wide governance. Organisations that position themselves as disciplined innovators, transparent about both the capability and the risk of AI, will win the trust of health systems over those that were simply early adopters. For CEOs and CTOs, that means owning AI governance as a board-level responsibility rather than delegating it to the data team.

The money is already following this logic: in 2025, AI-enabled companies captured 54% of all digital health funding and commanded roughly a 19% premium on average deal size compared to non-AI companies, a gap that makes the leadership-quality argument on its own.

Regulatory complexity is becoming a competitive moat, not just a risk to manage. Coverage rules, reimbursement models, and AI governance are shifting fast across the US, UK, and EU, and that volatility is what makes regulatory fluency scarce and valuable. Leaders who can model scenario outcomes and pivot a business model without compromising clinical credibility gain an edge over competitors built only for stable conditions. Search briefs should test for this directly, not just growth execution.

M&A is creating a specific kind of integration leadership demand. Targeted acquisitions in lower-acuity care segments and AI-enabled solutions are accelerating. For portfolio companies, this creates a particular profile requirement: executives who have lived through complex integrations, understand clinical credibility requirements, and can hold a culture together through rapid change.

Inside an AI-native health tech company: a conversation with Cera

To see what this looks like in practice, we spoke with Dr Ben Maruthappu, Founder and CEO of Cera, about how AI is reshaping the way his company operates and what he expects leadership to look like over the next five years. His view was direct: the most successful organisations won’t simply adopt AI tools – they’ll be led by executives who actively drive AI transformation across every function of the business, from engineering and product through finance and operations.

On what “AI-native” actually means inside the business: 

“In terms of being AI native, we look at that through a few different lenses. Firstly, what proportion of our code is written by AI. Second, how much of what we’re building is actually agentic AI itself rather than simply digital. And then how are we transforming other parts of the business using AI? But that’s a combination of what we build and off-the-shelf tools.”

On prioritisation rather than caution: 

Erevena asked where Cera has deliberately slowed AI deployment, Ben pushed back on the framing: “We haven’t really slowed AI deployment down. It’s more about prioritisation. What are the use cases that generate the best ROI for the company, that have clear business cases, that have the biggest impact on the P&L, either by reducing cost or retaining revenue, and are also the most differentiated products compared to what’s available on the market. That’s what we prioritise and focus on. We have a limited number of resources and team, and so we cut our cloth accordingly.”

That’s a useful distinction for boards evaluating leadership: restraint that comes from disciplined prioritisation looks very different from restraint that comes from an inability to deploy, even though both can get described as ‘going slow’.

On building a leadership team for an AI-first company: 

“If I had to build a leadership team from scratch, I’d opt for people who really lean into and grab AI. Martin, our CTO, is a great example. He ships and builds code using AI himself. He’s building a much smaller and leaner team, as the market continues to move quickly and less adaptive teams risk being left behind. Technology and engineering are the areas where this shows up first, but it will affect every leadership position over the next five years. Regardless of function, today’s C-suite leaders cannot just use AI, they need to lead its adoption and understand what it can do and get their teams building or using AI much more, and change workflows accordingly.”

This thinking shaped a recent search Erevena led for Cera: the appointment of Martin Samsa as Chief Technology and AI Officer, a brief that required exactly the AI-native leadership profile Dr. Maruthappu describes. Maruthappu credits the hire directly: “The gap in our team before Erevena was finding the right engineering and technology leadership. Martin is already making big, positive changes, and we’re very fortunate to have him.”

What founders should keep in mind

Pulling these threads together, a few things stand out for founders building a leadership team in this environment.

The workforce is being restructured by AI, not replaced. The near-term impact on health care labour is less about elimination and more about role transformation, with clinicians and administrators moving into AI oversight, validation, and interpretation functions. C-suite leaders need to be architects of that transition, not just adopters of the tools.

Regulatory fluency is no longer a nice-to-have parked in one function. It needs to sit with leaders who also carry P&L and product responsibility, because leaders who have only operated in stable regulatory conditions tend to struggle when the landscape shifts mid-execution.

The new health tech leadership bar: three questions for investors and boards

Bringing this back to Dr Maruthappu’s points above, three questions are worth building into any executive assessment for a health tech leadership role.

Can they govern AI, not just deploy it?  

The distinction between an executive who adopts AI tools and one who can build the governance architecture around them, the way Cera is doing across its product and engineering functions, is now material to enterprise risk and regulatory positioning.

Have they operated in regulatory uncertainty?  

The health care regulatory environment in 2026 is not stable, and a track record built entirely in calmer conditions doesn’t tell you how someone will perform when funding rules or coverage requirements shift mid-year.

Do they hold clinical and commercial credibility at the same time 

Search firms that understand this dual requirement and can assess it rigorously rather than screening for one or the other, are the ones worth partnering with for your most critical hires.

Choosing a health tech executive search partner

Choosing an executive search partner is a strategic decision. The instinct is often to reach for a healthcare specialist but the profile this piece describes is, at its core, a technology leadership profile: AI-native, comfortable in regulatory volatility, able to hold clinical and commercial credibility at once. That takes a search partner that assesses technology leaders and can test for the healthcare dimension rigorously, rather than one that knows the hospital market but not what an AI-first operating model demands of a C-suite.

The Cera appointment is one example of what that looks like in practice: a search brief built around AI-native leadership, assessed rigorously rather than assumed from a CV. As the leadership bar shifts, the gap between firms that can test for it and firms that screen on sector experience alone will widen with it.

Erevena partners with investors, founders, and boards at the moments that define their future; from fundraising and scaling to international expansion. Our senior partner-led executive search teams work across London, Paris, the Nordics, and Dubai, with a track record of building full leadership teams, not just filling single seats.

If you’re weighing a critical hire against the questions in this piece, get in touch.