Dedale Intelligence's take on HealthTech

HealthTech: Navigating Fragmentation, Innovation, and the Promise of AI

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HealthTech has become one of the fastest-growing technology segments. How do you define this space?

Soukeyna Ndiaye: HealthTech is often referred to as a single category, but in reality, it’s a collection of multiple, highly specific niches. Each niche reflects local clinical practices and healthcare systems, meaning that most vendors either remain within their borders or expand through acquisition rather than organic growth.

We typically distinguish between solutions deployed across different care settings, hospitals, GP and outpatient clinics, elderly care, radiology practices, and laboratories, each with its own dynamics.

HealthTech is not one market, but a constellation of localized ecosystems shaped by regulation, clinical pathways, and healthcare delivery models.

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What are the main categories of software within HealthTech today?

Soukeyna Ndiaye: Broadly, the industry is polarized between clinical and non-clinical functions.

• Clinical solutions support diagnosis and treatment, such as clinical decision support, medical imaging, patient triage, and digital therapeutics.

• Non-clinical solutions streamline hospital and facility operations, including hospital information systems, scheduling, and communication platforms.

At the core lies the Electronic Health Record (EHR), which records patient data and connects both sides of the ecosystem. Vendors like Epic Systems, Oracle Health, and Softway in France dominate this space, often providing both EHR and hospital information system capabilities.

The EHR remains the backbone of healthcare software; everything else connects to or builds around it.

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How has the market evolved in recent years?

Soukeyna Ndiaye: Over the past decade, and especially after the pandemic, we’ve seen a new generation of HealthTech players emerge, often focused on specialized, high-impact use cases.

On the clinical side, this includes AI-powered medical imaging or remote patient monitoring. On the non-clinical side, we see tools such as Nuance for automated medical reporting, Proximie for operating room analytics, and Doctolib for clinical communication and scheduling.

The pandemic accelerated digital adoption, but it also clarified the split between core systems and complementary innovations. These newer use cases are highly valuable but still perceived as complementary to large incumbent systems, rather than replacements.

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Despite innovation, healthcare still seems slow to digitalize. What are the barriers?

Soukeyna Ndiaye: Several, and they’re often structural. Healthcare systems are highly conservative and risk-averse, and facilities rarely switch vendors once a system is in place. Even when governments push for digitalization, like through France’s Ségur, Germany’s KHZG, or the UK’s Digital Health Plan, adoption remains uneven.

The main barriers include:

• Integration complexity with legacy systems and interoperability gaps.

• Staff training and change management challenges.

• Unclear ROI, especially for patient outcome–oriented software that doesn’t generate immediate financial returns.

• Vendor reliability concerns, particularly with newer entrants.

Healthcare doesn’t resist innovation; it just demands proof, reliability, and seamless integration before adoption.

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AI is often described as a game changer for healthcare. What’s the reality on the ground?

Soukeyna Ndiaye: AI is transforming healthcare, but it faces unique barriers compared to other industries. The tolerance for error is extremely low, rightly so, because we’re talking about patients’ lives here.

AI algorithms used for diagnosis are regulated as medical devices, requiring extensive testing and approval. This makes entry difficult, but it also creates strong moats for players that succeed.

Right now, AI in medical imaging is one of the most active areas. Vendors are leveraging large datasets and advanced image recognition to improve diagnostic accuracy and speed. But again, adoption depends on clinical validation and trust.

AI in healthcare is not just about technology; it’s about earning trust through evidence, safety, and proven outcomes.

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Looking ahead, how do you see HealthTech evolving over the next few years?

Soukeyna Ndiaye: I think we’ll see continued polarization between large integrated platforms and specialized innovators. Governments will keep driving digitalization through incentives and funding, but the real breakthroughs will come from technologies that improve care quality and reduce workload for healthcare professionals.

Ultimately, HealthTech will remain a highly local and relationship-driven market, but one where proven use cases, especially around AI and automation, will scale globally faster than before.

The future of HealthTech belongs to those who can combine medical rigor with demonstrated financial ROI.

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This interview is part of Dedale Intelligence’s ongoing series of expert insights, bringing research-driven perspectives on the most dynamic segments in software and technology. For more in-depth analysis, explore our latest articles, or contact us.