Not Just A Faster Horse: Harnessing The Power Of AI

We are experiencing a technological breakthrough in healthcare as consequential as the advent of the internet — but at a much faster pace. Artificial intelligence (AI) is no longer just a promising frontier; it’s becoming a core driver of transformation across clinical care and operations.

Just as the internet enabled remote monitoring, patient portals, and telehealth, AI is reshaping the way care is delivered and managed. But unlike past innovations, AI is dynamic, adaptive, and self-learning . Its evolution is not consistently predictable or follows logical improvement paths. Thus, the potential is vast, and so are the stakes.

Healthcare has been slow to adapt to digitization — consider the decades-long crawl to interoperability or the challenges of integrating point solutions. In an AI-enabled world, keeping pace with change won’t be enough; organizations need to get ahead of it . This means being strategic and purposeful about the type of solutions needed for each organization versus being enamored with a new feature or product. The situation is made more complicated by the flood of pitches leaders get from vendors and requests from internal stakeholders asking for the latest and greatest solution. The pace and scope of opportunities are exciting, but leaders need to strike a thoughtful balance between being pragmatic and visionary.

It's still the early days of AI adoption

Although the AI genie is out of the bottle — for example, the Food and Drug Administration has OK’d more than 1,000 AI-enabled products for patient care with cardiology and radiology leading the way — these are still nascent days of advanced uses, including for generative AI.

Early adopters of clinical and administrative AI solutions, as well as those taking a more cautious approach, face a noisy and immature market. Compounding the problem is the shortage of industry benchmarks establishing common performance metrics and comparing solutions side by side. This immaturity makes it hard to use traditional processes like requests for proposals to evaluate vendor offerings. Additionally, many healthcare executives lack the technical expertise to assess how the emerging AI capabilities might support, hamper, or transform their strategic objectives. These challenges necessitate not only reevaluating existing procurement processes but also a strategic, informed approach to technology adoption — balancing immediate priorities with long-term objectives, risks, and constraints around budgets and bandwidth.

Setting strategic imperatives for adopting AI

To cut through the noise, healthcare leaders should follow a disciplined, strategic, and need-based approach to AI adoption. It starts with assessing strategic priorities and working backward to identify specific use cases and potential AI solutions. For some health systems, this may include attracting new patients, improving patient satisfaction, or expanding service offerings. Others might focus on enhancing employee engagement and well-being, optimizing operational efficiencies, or achieving better performance in risk-based contracts. It comes down to clearly defining and prioritizing strategic needs.

Health systems aiming to attract new patients, for instance, could tap into AI tools in marketing analytics or customer relationship management that provide valuable insights into patient acquisition strategies. If the goal is to improve employee engagement, AI-driven platforms for workforce management and communication may enhance staff satisfaction and productivity. For organizations focused on risk contract performance, predictive analytics and population health management tools can support better care coordination and cost management.

Embedding this way of thinking across an organization requires a shift in decision-making. For instance, strategic planning should transition from viewing technology as a means to enable and accelerate existing strategies to recognizing that technology gives rise to new strategies and can be a source of differentiation. When it comes to operating models, leaders now have unprecedented access to insights and forecasts about their demand, capacity utilization, and patient and staff experiences. Armed with these new superpowers, they can redesign jobs in a way that restores joy to the practice of medicine while commanding an army of AI-enabled agents that make administration more efficient.

To fully understand the potential, organizations should create venues for teams to explore new technologies while staying within the organization’s risk and budget envelope. Continuous monitoring and experimenting with new capabilities can enhance strategy .. Importantly, risk evaluation must also be adapted to consider factors such as interpretability, bias, alignment, and the impact on jobs.

Embrace a continuous learning culture

Like the technology itself, leaders need to constantly grow their base of knowledge. By becoming informed about the potential and limitations of AI, leaders can better envision how these technologies can be applied to their organizations' unique challenges and opportunities, including envisioning new use cases and new strategies, offerings, and business models.

To that end, healthcare leaders should implement robust governance frameworks to guide AI adoption. This includes establishing cross-functional teams that bring together clinicians, IT leaders, Legal, Compliance, and Operations. No single stakeholder group should own AI decision-making alone. Continuous education is also critical. Executives and boards need ongoing exposure to the rapidly evolving AI landscape. Much like leaders in the early internet era had to learn about cloud, cybersecurity, and digital marketing, today’s C-suite must get comfortable with terms like large language models, agentic AI, and explainable AI.

Healthcare leaders have an opportunity to shape how AI is used not just in their organizations, but across the industry. Whether they are an early adopter, fast follower, or deliberate slow-roller, it is vital to have a strategy that aligns people, priorities, and recognizes limitations.