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AI Can’t Lead. Healthcare Needs Leaders

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It’s the caliber of leadership that brings teams together, demands accountability, and drives purposeful, decisive action.

Kevin Riley

Kevin Riley
President
Aetion

The healthcare landscape is in relentless flux. Markets pivot, funding ebbs and flows, and entire sectors are reshaped overnight. In this volatile environment, the true differentiator isn’t the latest technology or the sheer volume of data—it’s the caliber of leadership that brings teams together, demands accountability, and drives purposeful, decisive action.

Key Takeaways

  1. Automation can accelerate processes, but it cannot inspire a team, foster accountability, or cultivate a shared mission.
  2. AI systems can analyze vast datasets in milliseconds, but it takes the insight of doctors, scientists, and analysts to transform data into life-saving decisions.
  3. Integrating HITL into healthcare systems requires a strategic framework that unites every facet of the organization under a shared purpose.

How can leaders adapt to AI?

The pandemic reshaped the trajectory of digital health. In 2021, U.S. digital health startups secured $29.1 billion1—nearly double the previous year’s total. Telehealth emerged as a vital lifeline, and AI became a focal point for investment and innovation. The global AI in healthcare market,2 valued at $11.2 billion in 2022, is projected to reach $427.5 billion by 2032, expanding at a compound annual growth rate of 44%.

Investment surged, and with it, expectations. AI was positioned as a solution to clinical inefficiencies and operational challenges—a predictive force capable of streamlining workflows and generating insights at unprecedented speed. But as AI systems grew more complex, the narrative narrowed. Automation can accelerate processes, but it cannot inspire a team, foster accountability, or cultivate a shared mission.

The rush to position AI as a cure-all misses a fundamental truth: healthcare is not just a data problem. It is a profoundly human endeavor that relies on trust, context, and ethical discernment. Systems can process data rapidly, but they cannot grasp nuance or consider the broader implications of a decision. When systems misclassify a patient or misinterpret clinical data, the consequences are real and significant.

"Human-in-the-loop" (HITL),3 a concept advanced by Google, reinforces a powerful truth: data alone is incomplete. AI systems can analyze vast datasets in milliseconds, but it takes the insight of doctors, scientists, and analysts to transform data into life-saving decisions. HITL integrates human expertise at every step, embedding clinical judgment and ethical oversight into every action. In healthcare, where context defines outcomes, HITL ensures that technology aligns with real-world patient care.

Integrating HITL

HITL is the anchor that keeps AI grounded—a guide that steers algorithms with human insight, ensuring that every recommendation reflects the complexities of clinical care. Leaders who embrace HITL foster alignment across clinical operations, data science, and product development, positioning AI as a force that amplifies human expertise.

Integrating HITL into healthcare systems requires a strategic framework that unites every facet of the organization under a shared purpose. Leaders set the standard for collaboration in an industry where lives are at stake. Engineers, clinicians, and analysts must move in sync, ensuring every AI-driven decision is informed by human expertise and anchored in clinical realities.

Data can inform decisions, but it takes leadership to align them with purpose. Systems deliver information, but strong leaders mobilize teams to act with conviction and responsibility. In a sector defined by complexity and high stakes, those who bring people together to take decisive, intentional action will set the course for the future of healthcare.

Empowering teams

Alignment creates cohesion across functions, uniting departments around common objectives. In healthcare, where the consequences of missteps are significant, alignment ensures that engineers, clinicians, and product managers work as one, advancing initiatives to reinforce shared objectives.

Autonomy empowers teams to act within defined parameters. Leaders set clear expectations and then step back, allowing professionals to lead within their areas of expertise. Autonomy without accountability risks fragmentation and undermines results.

Accountability connects strategy to execution. It fosters a culture where every action is intentional, outcomes are measured, and initiatives are subject to rigorous scrutiny. In healthcare, this structure ensures that data scientists understand the clinical implications of their models, marketers align messaging with validated capabilities, and engineers validate systems against stringent clinical standards.

According to PwC’s 2025 AI Business Predictions,4 nearly half of technology leaders report fully integrating AI into core strategies. Meanwhile, a Pew Research Center survey5 reveals that 52% of U.S. workers remain more concerned than optimistic about AI’s impact on their work. This gap between adoption and confidence signals a leadership imperative, not a technological one.

Leaders must recognize that data is only as reliable as the context it captures. Incomplete or biased data can perpetuate inequities, distort outcomes, and undermine trust. Effective leadership establishes guardrails—rigorous validation, ongoing audits, and clear standards for transparency—to ensure that systems are accountable, trustworthy, and aligned with clinical integrity.

Healthcare cannot afford to delegate critical decisions to systems alone. Automated evidence generation risks obscuring biases and perpetuating inequities when applied without oversight. Leaders must demand transparency, insist on rigorous validation, and ensure that systems serve as extensions of human expertise—not replacements for it.

Trust isn't a feature

Trust remains the most valuable asset in healthcare. It is not a feature that can be coded or automated. Trust is earned through transparency, integrity, and a commitment to aligning actions with purpose.

Systems can simulate human behavior and replicate patterns of empathy, but they lack insight, ethical reasoning, and the ability to weigh context. Algorithms execute pre-defined logic; leadership applies judgment, considers impact, and fosters accountability.

The lesson is unmistakable: systems can process data at unprecedented speed, but they cannot inspire, galvanize, or unite a team around a shared mission. They cannot engage people in purposeful work, cultivate a culture of integrity, or drive the transformation that compels people to think critically and act decisively.

As technology continues to reshape healthcare, the future will belong to leaders who unite diverse teams, foster accountability, and elevate human judgment. Those who use data to strengthen connections, encourage critical thinking, and uphold ethical decision-making will define what comes next. Those who cede leadership to systems risk being sidelined by those who understand that technology is a tool, not the mission.

Leadership turns information into decisive action, aligning vision with execution and setting clear expectations for accountability. It transforms complexity into clarity and uncertainty into strategic advantage. In an industry where the stakes are high and the consequences of missteps are severe, the leaders who will define the future are those who lead with integrity, drive with purpose, and elevate the power of human connection. Those who grasp this will not just keep pace with change—they will set it in motion.

Sources

  1. 2021 year-end digital health funding: Seismic shifts beneath the surface. Rock Health. January 10, 2022. https://rockhealth.com/insights/2021-year-end-digital-health-funding-seismic-shifts-beneath-the-surface/
  2. AI in Healthcare Market Size to Reach USD 427.5 Billion by 2032 growing at 44.0% CAGR - Exclusive Report by Acumen Research and Consulting. Acumen. July 28, 2024. https://www.acumenresearchandconsulting.com/press-releases/ai-in-healthcare-market
  3. What is Human-in-the-Loop (HITL) in AI & ML? Google Cloud. https://cloud.google.com/discover/human-in-the-loop?hl=en
  4. 2025 AI Business Predictions. PWC. https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html
  5. U.S. Workers Are More Worried Than Hopeful About Future AI Use in the Workplace. Pew Research Center. February 25, 2025. https://www.pewresearch.org/social-trends/2025/02/25/u-s-workers-are-more-worried-than-hopeful-about-future-ai-use-in-the-workplace/

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