HTEC Research: Only One in Three Healthcare Organizations is Ready to Scale AI

AI is already embedded across healthcare and life sciences. Most organizations are deploying it, and confidence in its potential is high. Yet for many, the real challenge is only just beginning.

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HTEC, a global AI‑first provider of software and hardware design and engineering services, today released new research based on a global survey of 253 C-level HLS executives across the United States, United Kingdom, Germany, Spain, Saudi Arabia, and the UAE. The data suggests that AI progress in healthcare is becoming uneven—strong in pockets of innovation, but difficult to extend across the full complexity of care delivery and regulated operations.

“Real value emerges only when technology is thoughtfully embedded into clinicians’ everyday workflows, aligned with how care is actually delivered,” said Alfred Olivares, Managing Partner, Healthcare & Life Sciences at HTEC. “AI must complement clinical expertise—not disrupt it—if it is to deliver meaningful impact.”

AI Widespread, Scale Elusive

AI is now firmly on the strategic agenda across healthcare and life sciences. More than half of organizations (52.2%) report that AI is already embedded across multiple functions, and virtually all leaders consider it a priority.

Despite widespread adoption, scaling AI across clinical, operational, and R&D environments remains difficult—slowed by fragmented systems, capability gaps, and the need to balance innovation with safety, compliance, and trust.

Integration and Execution Alignment are the Biggest Barriers

The research identifies system integration and executive alignment as the primary obstacles to scaling AI in healthcare.

These challenges are amplified by:

• Fragmented clinical and enterprise systems
• Strict regulatory and compliance requirements
• Highly distributed ecosystems involving providers, patients, payors, and regulators

While 85.8% of leaders report strong or full alignment at a strategic level, 42.3% still cite lack of alignment as a barrier, highlighting a critical gap between intent and execution.

In practice, organizations often agree that AI matters, but diverge on how to prioritize use cases, allocate investment, and operationalize it safely at scale.

Edge AI Emerges as a Strategic Priority

Edge AI plays a uniquely strategic role in healthcare and life sciences. Nearly all leaders report familiarity with edge AI, and 97.9% express confidence in their ability to deploy it.

Notably, most organizations are adopting a hybrid edge-to-cloud approach—combining partnerships (61.7%), in-house development (53.6%), and third-party platforms (53.2%) to connect real-time data from devices and care settings with centralized clinical, research, and analytics systems.

This reflects the growing importance of distributed care models, connected medical devices, and the need to process sensitive data closer to the point of care.

Capability Gaps are Slowing Progress and Increasing Costs

Despite strong adoption, nearly all organizations (93.7%) report technical skill gaps that are directly impacting their ability to scale AI. The most critical gaps center around cybersecurity and data privacy, AI/ML expertise, and DevOps and automation. These constraints are already translating into measurable business impact, with 51.5% of organizations reporting higher costs, 41.4% experiencing reduced innovation, and 36.7% facing slower time to market.

Only One in Three Organizations Ready to Scale AI

Despite strong adoption and confidence in emerging technologies like edge AI, only about a third of healthcare organizations believe they can scale AI rapidly.

At the same time, leaders estimate that failing to act on AI and edge opportunities would set them back by 1.65 years on average, underscoring how narrow the competitive window has become.

This creates a clear inflection point: organizations must move beyond experimentation and isolated use cases toward coordinated, enterprise-wide execution.

The Next Phase of Healthcare AI

Healthcare and life sciences have already demonstrated strong momentum in AI adoption. But the next phase will not be defined by how widely AI is used, but how effectively it is operationalized and blended with the current clinician workflows.

The organizations that move ahead will be those that:

• Build governed, reusable data foundations
• Align leadership at both strategic and execution levels
• Invest in workforce enablement alongside technology
• Integrate AI directly into clinical and operational workflows

“The competitive window is narrow, but it is not yet closed,” said Stefan Mrsic, Managing Partner, Healthcare & Life Sciences at HTEC. “The next phase will be defined by the ability to combine innovation with safety, explainability, and human judgment.”

The State of AI in the Healthcare and Life Sciences Industry 2025-2026 is now available for download.

About the Research

The report was commissioned by HTEC and conducted by Censuswide. It includes the insights from 1,529 C-suite leaders across the USA, UK, Germany, Spain, Saudi Arabia, and the UAE, spanning CEOs, CIOs, CTOs, CDOs, CFOs, COOs, CPOs, and CSOs across industries, including financial services, healthcare, automotive, telecommunications, retail, and semiconductors.

About HTEC

HTEC Group Inc. is a global AI-first provider of strategic, software and hardware embedded design and engineering services, specializing in Advanced Technologies, Financial Services, MedTech, Automotive, Telco, and Enterprise Software & Platforms. HTEC has a proven track record of helping Fortune 500 and hyper-growth companies solve complex engineering challenges, drive efficiency, reduce risks, and accelerate time to market. HTEC prides itself on attracting top talent and has strategically chosen the locations of its 20+ excellence centers to enable this.

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