The integration of artificial intelligence into clinical care is transforming healthcare delivery, offering the potential to enhance diagnostic accuracy, streamline workflows and improve patient outcomes. However, with the rapid evolution of AI technologies, health systems face a critical choice in how they adopt these tools. Leaders must determine whether to embrace innovation early, follow closely behind successful pioneers or adopt a more cautious, step-by-step approach. Each strategy—early adopter, fast follower or incremental mover—comes with unique benefits, challenges and implications for risk, investment and organisational agility. Making the right choice is essential to ensure that AI strengthens rather than disrupts clinical care.
High-Risk, High-Reward: The Early Adopter Strategy
The early adopter strategy is characterised by a proactive embrace of AI tools at their earliest stages of development. Health systems that take this route position themselves to realise the benefits of AI, such as improved clinical decision-making and workflow automation, before their peers. This can create competitive advantages, attract top talent and demonstrate innovative leadership. The promise of seeing positive clinical outcomes sooner can be highly attractive.
However, this approach also comes with significant risks. Early AI tools are often costly and unproven, and their implementation may demand considerable resources in training, integration and infrastructure. For organisations operating on tight margins, this financial risk can be a serious constraint. Furthermore, the fast-moving nature of AI development means that not all tools will prove viable in the long term. The early days of personal computing and robotic surgery offer instructive parallels: both saw a flood of manufacturers and tools, most of which eventually disappeared as the market consolidated around a few successful players. A similar pattern is emerging in the AI scribe market, with dozens of competing tools designed to automate clinical documentation. Over time, only a handful are likely to remain, leaving early adopters vulnerable to supporting obsolete systems.
Ultimately, the early adopter strategy can deliver high returns but requires a strong appetite for risk, robust change management processes and the flexibility to adapt quickly as technologies mature or fail.
Balancing Speed and Stability: The Fast Follower Strategy
The fast follower strategy offers a more balanced path, in which health systems wait to see which AI tools prove successful before adopting them. This approach reduces the risk associated with early failure while allowing organisations to benefit from proven technologies. Fast followers aim to capitalise on early adopters’ insights and experiences, avoiding costly missteps and aligning their adoption efforts with market-tested solutions.
The primary challenge of this strategy is maintaining sufficient speed. The pace of innovation in AI is exceptionally rapid, and waiting too long can result in missed opportunities and competitive disadvantage. Health systems that delay adoption may find themselves on the back foot, especially when the new tools become standard practice or deliver significant operational efficiencies elsewhere. Furthermore, even when decisions are made, the actual implementation of AI tools can be complex and time-consuming. If the organisation lacks the internal capacity to move swiftly from decision to deployment, the benefits of fast following may be lost.
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To succeed as a fast follower, a health system must have agile governance structures and well-prepared operational teams. This includes having processes in place for quickly evaluating new technologies, assessing return on investment and integrating tools into clinical workflows. Without such readiness, the organisation risks becoming a slow mover by default, rather than a fast follower by design.
Thoughtful Progress: The Incremental Mover Strategy
The incremental mover strategy takes a cautious, deliberate approach to AI adoption, prioritising long-term readiness and sustainability. Rather than rushing to adopt the latest tools, these organisations focus on building internal knowledge, enhancing cross-functional collaboration and gradually integrating AI into clinical and administrative processes. This method is especially well-suited to institutions that value stability and want to minimise disruption.
The strength of this strategy lies in its emphasis on organisational learning. Key departments—such as information technology, clinical operations, legal, compliance and security—are engaged early in the process, ensuring that each has a clear understanding of AI's potential impact. By investing in internal education and governance reform, incremental movers create an environment where AI can be adopted thoughtfully and successfully over time.
This approach also supports agility in the face of evolving technologies. Rather than committing early to specific tools, incremental movers maintain flexibility, reviewing developments in the AI landscape and adjusting their plans accordingly. They aim not to fall behind, but to keep pace with innovation in a measured and informed manner. This enables them to avoid the pitfalls of premature adoption while still benefiting from AI as it becomes more mature and integrated into healthcare delivery.
Importantly, incremental movers are less likely to experience the kind of clinician pushback often associated with abrupt or poorly supported digital change. As AI is introduced gradually and in alignment with user needs, it is more likely to be accepted and used effectively. This enhances not only implementation success but also staff morale and patient care.
The adoption of AI in clinical care presents both promise and complexity. Health systems must carefully evaluate their strategic position, resources and organisational culture when determining how to proceed. Early adopters can lead the way in innovation but must manage high levels of risk and potential instability. Fast followers may avoid early pitfalls but must remain vigilant to avoid falling behind. Incremental movers offer a model of deliberate, sustained progress, fostering institutional readiness and long-term success.
Whichever path is chosen, strategic clarity is essential. AI tools will continue to evolve and reshape the clinical landscape. There is no pause in technological advancement—health systems must move forward, whether boldly or cautiously. By aligning their strategy with their capacity and vision, healthcare leaders can ensure that AI becomes a powerful ally in delivering better care, supporting clinicians and navigating the future of medicine.
Source: HealthLeaders
Image Credit: iStock
