AI in Healthcare: A Clinician's Imperative

By Dr Bassam Nuseibeh

I work in a busy emergency department filled with highly skilled clinicians. Decision-making is relentless, the stakes are high, and inefficiencies are costly.

Like many healthcare settings today, we operate within systems that are often complex, fragmented, and administratively heavy.
Despite the best efforts of staff and leadership, inefficiencies persist—they are products not of individuals but of systems too fractured and too slow to evolve.

Several years ago, my hospital introduced an electronic medical record (EMR) system, amid the usual promises of streamlined care, faster workflows, and safer outcomes. The reality was less inspiring.
Requests for flexibility were met with shrugs; certain features, we were told, simply "could not be done." The result was a system that added administrative friction without easing clinical work, a burden on those it was meant to assist.

Such experiences are not unique. Across healthcare, clinicians navigate fragmented information, duplicative tasks, and wasted opportunities to teach and mentor the next generation of doctors. Much of this waste arises from technology that is poorly adapted to the realities of clinical work—technology implemented without authentic frontline leadership.

Artificial intelligence (AI) now looms as the next great wave of healthcare innovation. It carries extraordinary potential to help, but only if healthcare learns from the past. The adoption of AI cannot follow the same patterns as EMR deployment: vendor-driven, rigid, and detached from clinical need. Instead, it must be clinician-led, strategically deployed, and governed with rigour.

The first principle of responsible AI adoption is that solutions must be designed by the people doing the work. Clinicians understand where inefficiencies lie: documentation burdens, rostering frustrations, fractured handovers, and the countless small administrative tasks that sap the time and energy needed for teaching and patient care. Addressing these areas should be the strategic focus of early AI initiatives rather than diving prematurely into complex diagnostic decision-support systems.

Governance must be embedded from the start, with AI committees including clinicians, executives, IT specialists, ethicists, and patient advocates. Oversight should be ongoing, not a one-off compliance exercise. Clinician "champions" should be appointed within departments to help shape and oversee implementation at a local level. Without such mechanisms, AI risks becoming just another source of operational complexity rather than a tool for good.

The deployment of AI should begin modestly. Pilots should be run in areas where success is measurable and risks are low: clinical documentation, rostering, coding accuracy, and educational support. Success metrics must be clear: time saved, errors reduced, administrative load lightened, satisfaction improved. Expansion should be deliberate, not hasty.

Of course, there are pitfalls to be avoided. Healthcare’s fascination with shiny new objects often leads to purchasing technologies that solve no real problem. Technologist-led implementations risk alienating clinicians, who are forced to adapt to systems rather than vice versa. Poor governance allows biases, safety risks, and inefficiencies to persist unchallenged.

"Technology should amplify human care—not obstruct it."

From the emergency floor, it is evident: healthcare’s future will depend not on faster procurement, but on leadership that is practical, consultative, and grounded in reality—leadership that many organisations are already demonstrating, but that must now extend into how we engage with AI.

Healthcare executives today have an opportunity that should not be wasted. With careful planning, AI can lighten the administrative burden on clinicians, restore time for mentorship and leadership, improve operational resilience, and build care environments that truly serve patients and staff alike. Institutions that move thoughtfully will not merely digitise old frustrations. They will modernise the practice of care itself.

"The success of digital transformation lies not in the technology itself, but in the culture of leadership, trust, and collaboration that surrounds it."
— World Economic Forum, 2023

The success of healthcare’s next transformation will not be measured by how much technology it buys, but by how wisely it uses it to serve people.

At Clintix, we believe the future of healthcare must be shaped by those who know it best. AI offers a rare chance to rebuild healthcare’s technological foundation—with care, wisdom, and above all, humanity.

It is not technology that will define the future of healthcare, but the decisions we make about it.