Gakombe Kanyenje, CEO, founder, Metropolitan Hospital, Nairobi /HANDOUT
The greatest misconception about artificial intelligence in healthcare is that it is coming for doctors’ jobs. At a time when Kenya faces severe workforce shortages and rising healthcare demands, viewing AI as competition rather than collaboration is a costly mistake.
The crisis facing Kenya is not about technological disruption, but overwhelming pressure on an already overstretched system. Across the country, healthcare workers are managing rising patient volumes, staffing shortages, administrative burdens and increasing public expectations, often with limited resources and little room for error.
It is a Tuesday afternoon in one of Nairobi’s busy hospitals. The waiting area is overcrowded, temperatures are rising and frustration is beginning to show on patients’ faces. A nurse calls in the 50th patient of the day, while the specialist on duty, already mentally and physically exhausted, still has dozens of patients waiting outside the consultation room. This is routine for many healthcare workers not just in Kenya but across the globe.
Under these conditions, even experienced clinicians can miss warning signs, delay diagnoses or overlook critical details, not because they lack competence, but because the healthcare system is stretched beyond its limits. This is the context in which we must think about artificial intelligence in healthcare.
Yet AI in healthcare often sparks understandable anxiety among clinicians. Some fear automation could replace roles, especially in diagnostics, while others worry that algorithm-driven recommendations may undermine clinical judgment and weaken the human connection at the heart of medicine. These concerns are valid but they reflect uncertainty about implementation more than the danger of the technology itself.
Reframed correctly, AI is less artificial than assisted intelligence as it is a support tool that can help overstretched clinicians work more efficiently, consistently and safely while keeping human judgment at the centre of care.
AI in healthcare is no longer futuristic; it is already supporting aspects of clinical care globally. In diagnostics, AI-based systems can assist healthcare professionals in analyzing medical images and laboratory data more efficiently, helping clinicians identify patterns that may support earlier intervention and more informed decision-making. It can also help reduce administrative burdens that consume valuable clinical time in overstretched healthcare environments.
The same principle applies in surgical care, where robotic-assisted systems are increasingly being explored as tools that may support procedural planning and surgical consistency while maintaining full clinician oversight and decision-making authority.
A notable example is the robotic-assisted knee replacement robot at Metropolitan Hospital which is the first of its kind in East and Central Africa. This demonstrates how technology can enhance surgical precision, improve patient outcomes, and support surgeons in performing complex procedures with greater accuracy. Rather than replacing healthcare professionals, these technologies are designed to complement clinical expertise within appropriately regulated healthcare settings.
Kenya’s case for embracing artificial intelligence in healthcare is reinforced by mounting pressure on its health workforce and growing strain within the healthcare system. The country continues to face increasing demand for healthcare services alongside persistent shortages in healthcare personnel, particularly in specialized areas of care.
This strain is further compounded by migration of trained healthcare workers, resource limitations and rising patient volumes.
The result is a healthcare system operating under sustained pressure, with direct consequences for access, efficiency and continuity of care. These pressures are also influencing patient behaviour, with many individuals increasingly turning to self-medication, pharmacies or online health information before seeking formal medical attention. Research from institutions such as Harvard University has increasingly framed artificial intelligence as a support tool that may strengthen operational efficiency, support clinical workflows and contribute to more responsive healthcare delivery while maintaining human oversight in decision-making.
However, the growing enthusiasm around AI risks moving faster than the foundations required to support it responsibly. Kenya now has the Digital Health Act, 2023 and a National Artificial Intelligence Strategy for 2025–2030, with healthcare identified as a priority sector but regulation alone does not guarantee readiness. Many healthcare facilities still struggle with basic interoperability challenges, including the inability to reliably exchange structured patient information across systems and institutions.
There is also the question of context. Many clinical AI tools currently available globally were trained using datasets from Europe and North America, where disease patterns, healthcare infrastructure and patient demographics may differ significantly from those in Kenya and across Africa. Without proper local validation, there is a risk of deploying systems that are not fully aligned with local healthcare realities.
At the same time, Kenya continues to lose experienced healthcare professionals through migration and workforce attrition, raising important questions about the availability of the clinical oversight needed to guide safe and effective AI implementation. Technology can support healthcare systems, but it cannot compensate for unresolved structural gaps in workforce capacity, digitisation and health system investment.
While AI has an important role in healthcare, it cannot replace the human presence at the bedside offering empathy, reassurance and compassion during moments of pain and uncertainty. Like any technology, AI systems may also produce errors or reflect limitations in data, reinforcing the importance of responsible implementation, regulation and continued human oversight.
According to the World Health Organization, while AI presents important opportunities in healthcare, its adoption must address critical concerns including data privacy, algorithm bias, regulatory gaps and overreliance on automated systems at the expense of clinical judgment. These challenges do not diminish the value of AI; rather, they highlight the importance of ethical, well-regulated and human-centred integration.
For Kenya, this means focusing on three priorities: strengthening digital health infrastructure, ensuring local validation and accountability for clinical AI tools, and investing in the retention and development of healthcare professionals who will ultimately remain responsible for patient care and clinical oversight.
Kenya has an opportunity to approach artificial intelligence not as a replacement for healthcare professionals, but as a tool that can support overstretched systems, strengthen operational capacity and help healthcare workers deliver more timely, responsive and sustainable care. The future of healthcare will depend not only on the technologies we adopt, but on how responsibly and effectively we choose to implement them.
