Is AI the right medicine for healthcare or just the loudest conversation of the year?

As the year draws to a close, one signal stands out more clearly than any other across the digital health landscape: AI.

It has dominated conference agendas, policy discussions, vendor roadmaps, and boardroom conversations. Artificial intelligence has been framed as everything from a workforce solution to a clinical decision support revolution and, in some cases, a cure-all for deeply systemic challenges in healthcare.

But as the volume of conversation has increased, so too has a more nuanced and necessary question: is AI always the right tool for the job?

In this year-end edition of Vital Signs, we looked back across the themes that shaped the year and surveyed customers, clinicians, technical teams, administrators, government employees, competitors, and industry experts. The result is not a rejection of AI, but a more mature, evidence-driven perspective on its role in healthcare.

AI as the dominant Vital Sign of the year

There is no question that AI was the most prevalent topic across digital health this year. The reasons are understandable.

Healthcare systems globally are under immense pressure. Workforce shortages, rising demand, administrative burden, and growing data complexity have created an environment where automation and intelligence are not just attractive but increasingly necessary.

Against this backdrop, AI emerged as a powerful signal of possibility, promising scale, speed, and efficiency where traditional approaches have struggled to deliver.

However, prevalence does not necessarily equate to proof. While AI dominated the narrative, many leaders cautioned against allowing momentum to outpace meaning. The most consistent message we heard was not about whether AI belongs in healthcare, but where and how it should be used.

From potential to proof: the evidence gap in healthcare AI

Across stakeholder groups, optimism about AI’s potential was tempered by a clear demand for evidence.

While technical capabilities have advanced rapidly, confidence in real-world impact, particularly on clinical outcomes, remains uneven. Several respondents noted that, although AI tools are increasingly sophisticated, it remains challenging to consistently demonstrate improvements in patient outcomes, clinician experience, or system performance.

As one clinical leader observed, there is still limited evidence that many AI-driven clinical tools are meaningfully changing outcomes. This sentiment was echoed across the sector, reinforcing a critical point: healthcare cannot afford technology for technology’s sake.

Innovation must be anchored in measurable value.

Where GenAI is delivering the most clinical impact

To better understand where GenAI is delivering value today, we asked healthcare leaders to rank use cases based on their clinical impact.

The results were telling. Use cases focused on clinical documentation and information access ranked highest, including:

• Faster access to key patient information
• Reduced administrative workload for clinicians
• Improved accuracy and consistency in documentation

Lower-ranked use cases tended to be more speculative or further removed from day-to-day clinical workflows.

The signal is clear: GenAI is currently delivering the most value when it supports clinicians, rather than attempting to replace them.

Choosing the right tool for the right healthcare problem

One of the strongest themes to emerge from the survey was the importance of intentionality.

AI should not be deployed simply because it is available, but because it is the most appropriate solution to a clearly defined problem.

As Gillian Robinson-Gibb, Founder & CEO of Pegasus Health, noted:

“We’ve got to be very careful going down the AI track and choosing it to make sure it is the right solution for the problem.”

This reflects a growing maturity in the sector. Rather than asking “How can we use AI?”, leaders are increasingly asking, “What problem are we trying to solve, and is AI the best way to solve it?”

Enablement over restriction: rethinking AI governance in healthcare

Governance was another recurring theme, particularly in discussions around safety, ethics, and regulation.

While guardrails are essential, many experts advocated for guidance that enables progress rather than blocks it.

Rowena Woolgar, Director at Arise Consulting, captured this balance succinctly:

“We need guidelines instead of guardrails, so we are making sure that we are guiding people through the journey and not putting huge blockers in the way.”

Effective governance should support the responsible adoption of new ideas, not stifle innovation. That requires leadership that understands both the risks and the opportunities, and can navigate between them.

Freeing clinicians to focus on care

Where enthusiasm for AI was strongest was in its potential to reduce administrative burden and give clinicians back time.

Respondents highlighted value drivers such as:

• Clear condition and discharge summaries
• Improved handover and transfer of care documentation
• More consistent medication and symptom summaries

Rather than replacing clinical judgement, many see AI’s greatest value in handling repetitive, time-consuming tasks, allowing clinicians to focus on what humans do best.

As Harry Hawke, CEO and Managing Director of Webtools, explained:

“Where I see the opportunity is to really focus on how we can free up clinicians’ time to focus on the thing they’re really good at, which is the soft stuff with patients.”

This reframes AI not as a clinical replacement, but as an enabler of better human care.

Leadership, trust, and long-term transformation

Several leaders emphasised that AI’s impact will ultimately depend on leadership.

With the right vision, governance, and accountability, AI has the potential to fundamentally change how healthcare is delivered.

Stella Ward, CEO of the Digital Health Association, highlighted this transformational opportunity:

“With the right leadership and guardrails, it can fundamentally change how healthcare is delivered.”

Others pointed to how AI is unlocking possibilities that were previously constrained by cost, scale, or technical limitations.

As Ray Delany, Founder of CIO Studio, reflected:

“A lot of things we’ve always wanted to do have become a lot more possible, AI to me has removed the restrictions.”

A more thoughtful AI conversation for the year ahead

Looking back, AI may have been the loudest Vital Sign of the year, but volume alone will not determine its future.

What this year has revealed is a sector moving beyond hype toward a more disciplined, thoughtful approach. There is excitement, but also caution. Ambition, balanced by responsibility. Innovation, grounded in evidence.

As we move into the year ahead, the challenge for digital health leaders is not to adopt AI faster, but to adopt it more effectively. To ensure it is used where it adds real value, supported by strong leadership, clear governance, and a relentless focus on outcomes.

Because in healthcare, the most important Vital Sign is not how advanced our technology is but whether it truly improves care.

Authored by Tom Varghese, Global Product Marketing & Growth Manager at Orion Health.