Part 7 of Talencio’s Series, “Navigating 2026: The Top 10 Health Technology Trends Every Leader Should Watch”
For many health technology companies, 2026 has become a year of disciplined decision-making. Capital markets remain selective. Investors are stressing operational resilience and sustained value creation. Health systems are balancing financial pressures with digital transformation initiatives.
Against that backdrop, leadership teams are finding that competitive advantage no longer comes from innovation alone, but from earning confidence in the decisions behind that innovation.1
Not long ago, those same leaders were asking whether and how artificial intelligence (AI) would fundamentally transform their organizations. Today, that conversation has evolved. Few executives question whether intelligent technologies will become integral to healthcare; they’re asking if they can be trusted.
Can clinicians understand and appreciate how a machine learning model reached its recommendation? Can customers be confident their sensitive data remains protected? Can appropriate governance be promised to boards in this digital age? Can regulators verify that intelligent systems continue performing safely after deployment?
The healthtech organizations that successfully answer these kinds of questions won’t simply deploy smarter solutions. They’ll become more trusted organizations.
From innovation to instilled confidence
Imagine sitting in a board meeting next spring.
Your CTO has just demonstrated a new intelligent platform capable of reducing documentation burdens, accelerating diagnostic workflows, improving utilization management, and streamlining clinical operations. Early pilot results are encouraging. Pilot customers are enthusiastic. The business case appears compelling.
Then someone asks a deceptively simple question.
“How do we know we can trust it?”
Suddenly, the discussion changes. The conversation is no longer centered on technology. It shifts toward related topics. Governance. Accountability. Cybersecurity. Transparency. Patient safety. Organizational risk.
This is precisely the conversation taking place across healthcare.
Machine learning, predictive analytics, intelligent automation, and other forms of computational intelligence are moving well beyond experimentation. They’re becoming embedded within clinical decision support, diagnostics, medical devices, revenue cycle management, patient engagement, research, and administrative workflows.
In fact, recent industry research found that more than 70% of healthcare organizations are already using or actively implementing AI-enabled technologies in at least one business or clinical function, underscoring just how quickly intelligent technologies are moving from isolated pilots into enterprise operations.2
As organizations move on from pilot projects and into enterprise-wide implementation, data governance has evolved from what was often a “check-the-boxes” compliance exercise to instead become a valued strategic capability.²
Healthcare technology leaders are recognizing that trust is no longer a byproduct of a successful innovation. Increasingly, it’s what determines if an innovation succeeds in the first place.
When trust breaks down
Healthcare executives don’t need to imagine what happens when trust is lost. Over the past two years, the industry has experienced several high-profile cybersecurity incidents that demonstrated just how costly compromised trust can be.
The ransomware attack on Change Healthcare became one of the most disruptive cyber incidents in healthcare history. Claims processing slowed or stopped nationwide. Pharmacies struggled to fill prescriptions. Providers experienced significant financial strain as reimbursement workflows stalled. By early 2025, UnitedHealth confirmed that approximately 190 million individuals had been affected, making it the largest healthcare data breach ever reported in the United States.³ ⁴
Mere months later, Ascension Health experienced a cyberattack that forced portions of one of the nation’s largest health systems to return temporarily to paper documentation, divert ambulances, postpone procedures, and manually coordinate patient care. The incident served as a powerful reminder that cybersecurity failures aren’t confined to IT—they can directly affect clinical operations and patient outcomes.⁵
More recently, healthcare AI company Xsolis, whose platform supports utilization management decisions for health systems, disclosed a phishing-related breach affecting nearly 1.4 million individuals.⁶ The incident underscored another important reality: organizations developing intelligent technologies face many of the same governance and cybersecurity expectations as the providers and life sciences companies using them.
More recently, medical device manufacturer Stryker reminded that cybersecurity risks extend well beyond hospitals and health systems. In March 2026, an Iran-linked cyberattack disrupted portions of Stryker’s global operations, affecting manufacturing, ordering, and shipping systems. While the company found no impact to connected medical products or patient services, the incident illustrates how cyberattacks threaten the entire healthcare ecosystem.
Although each incident differed in scope and impact, they share a common lesson.
They aren’t simply cybersecurity stories. They’re trust stories that hugely influenced purchasing decisions, investment strategies, regulatory oversight, partnership evaluations and competitive positioning throughout healthcare.
The new face of protected information
For decades, cybersecurity strategies focused on protecting information. Covered entities worked to thwart unauthorized access, encrypt sensitive data and maintain business continuity.
While those priorities remain essential, the rapid adoption of intelligent technologies is fundamentally changing the nature of cyber risk.
Healthtech organizations aren’t just protecting patient records, IP, or financial information; they’re safeguarding algorithms, clinical recommendations, automated workflows, model integrity, and the decisions those technologies help generate.
Ahead-of-the-curve leaders aren’t simply asking whether someone can steal sensitive information. They’re asking whether someone can manipulate a learning model. Whether training data can be compromised. Whether third-party intelligent systems might introduce unseen vulnerabilities. And whether clinicians, regulators, and patients can understand why an algorithm reached a particular conclusion.
This evolution is why cybersecurity, intelligent technology governance, and organizational trust are now inseparable strategic priorities and it’s why data governance is quickly becoming one of healthcare’s most valued leadership capabilities.
Mature governance and stakeholder management
One of the biggest misconceptions surrounding AI is that successful adoption depends primarily on picking the right technology.
The medical device, biotech, and digital health companies making the greatest progress aren’t necessarily those with the most sophisticated intelligent systems. They’re the ones building the governance structures, leadership disciplines, and organizational processes necessary to deploy those technologies responsibly at scale. Recent industry research consistently shows that the greatest gap is no longer technological capability—it’s organizational maturity.⁷ ⁸
That distinction marks an important shift in executive thinking. Savvy leaders are asking questions like:
How should intelligent technologies be evaluated before deployment?
Who approves new use cases?
What level of oversight is appropriate for administrative automation versus clinical decision support?
How will machine learning models be monitored after implementation?
What happens when an algorithm evolves over time… or produces an unexpected result?
Make no mistake, stakeholders are asking these questions too—and expect organizations to demonstrate that intelligent systems remain safe, effective, and appropriately governed throughout their lifecycle.2
As such, explainability becomes much more than a technical feature. It becomes a business capability.
Organizations capable of clearly explaining how their technologies function and are monitored, validated, and governed over time will inspire greater confidence… which creates trust… which accelerates adoption.
In today’s health technology market, that cascade results in meaningful competitive advantage.
Leading healthtech organizations are developing repeatable frameworks to thoughtfully answer questions like these. ensuring alignment among technology, clinical, regulatory, legal, compliance, quality, and executive functions.⁸
They see that this governance doesn’t slow innovation but enables them to innovate and scale with greater confidence and fewer setbacks.
Ecosystems of intelligence
Today’s health technology products increasingly rely on cloud platforms, application programming interfaces, third-party data sources, embedded machine learning models, software development partners, open-source components, and specialized AI services.
And while every new connection creates opportunity, it also introduces new governance responsibilities.
Recognizing this shift, the FDA’s updated February 2026 medical device cybersecurity guidance reinforces that cybersecurity must now be an integral part of product design, quality management, and lifecycle resilience—not simply a technical review before submission.¹⁰ Moreover, the Health Sector Coordinating Council (HSCC) recently published guidance encouraging healthcare organizations to expand their oversight beyond traditional vendor management to include AI-specific supply chain transparency, model integrity, data governance, and third-party cybersecurity practices.⁹
As healthcare organizations become increasingly interconnected, trust will depend as much on ecosystem governance as internal controls.
Leadership will determine who wins
When people think of company differentiation, they can easily overvalue the importance of technology and under-appreciate the role of connected leadership.
Both are critical. As intelligent technologies continue to evolve, organizations will absolutely need executives capable of connecting disciplines that have historically operated independently. Technology strategy can no longer exist apart from cybersecurity. Product development can no longer be separated from regulatory strategy. Commercialization, clinical validation, legal oversight, quality systems, and enterprise risk management are interconnected; failing to realize this can be disastrous.
The next generation of health technology leaders won’t simply understand how to spark and introduce innovation. They’ll understand how to systematically govern it and imbue trust into it.
At Talencio, we’re already seeing shifts in what organizations are looking for in executive leadership. Technical expertise remains essential, but so does the ability to substantively inspire confidence and build alignment and collaboration across engineering, clinical affairs, quality, regulatory, cybersecurity, legal, and commercial teams.
Whether organizations are deploying advanced diagnostics, connected medical devices, digital therapeutics, machine learning models, or future generations of computational intelligence, sustainable success will hinge on leaders’ ability to govern those innovations—not simply deploy them.
Looking ahead, looking within
Organizational confidence doesn’t happen by accident. It’s built deliberately and consistently through transparent leadership, thoughtful governance, clear communication, coordinated cybersecurity preparedness, and disciplined decision-making.
The companies that define the next decade of healthcare won’t simply build more innovative technologies. They’ll build more trustworthy organizations from within.
After all, innovation may create opportunity, but it’s trust that sustains enduring value.
Sources
- McKinsey & Company, What to Expect in US Healthcare in 2026 and Beyond (Jan 12, 2026)
- HIMSS, From Pilot to Production: AI Governance, Risk, and Readiness Across Global Healthcare (June 17, 2026)
- American Hospital Association, Change Healthcare Cyberattack Underscores Urgent Need to Strengthen Cyber Preparedness (Feb 1, 2025)
- Reuters, UnitedHealth Says Change Healthcare Breach Affected Approximately 190 Million People (Jan 24, 2025)
- Reuters, Ascension Warns Suspected Cyberattack Disrupted Clinical Operations (May 8, 2024)
- Healthcare IT News, New HSCC Guide Addresses Cybersecurity Risks Specific to Healthcare AI (May 7, 2026)
- McKinsey & Company, Generative AI in Healthcare: Adoption Matures as Agentic AI Emerges (Apr 16, 2026)
- Healthcare Dive, Balancing AI Innovation and Risk: Five Takeaways from HIMSS26 (Mar 16, 2026)
- U.S. Food and Drug Administration, Cybersecurity in Medical Devices: Quality Management System Considerations and Content of Premarket Submissions (Feb 3, 2026)
- Health Sector Coordinating Council, Guide for Third-Party AI Cybersecurity (May 1, 2026)
About the Author
Paula Norbom is the Founder and CEO of Talencio, an executive search and staffing firm serving health technology companies. She has worked in the health technology industry for over 30 years.