Kenya’s healthcare system faces a divide between the adoption of artificial intelligence (AI) in its policy frameworks and its full implementation. While AI has become a dominant topic in health policy discussions, its integration into clinical workflow remains limited.
Despite advancements in technology, the World Health Organisation (WHO) notes that most countries, including Kenya, have yet to fully leverage digital health and AI for positive outcomes. The Kenya Artificial Intelligence Strategy (2025-2030) acknowledges infrastructure as a key limitation to full realisation in the healthcare space.
Kenya’s inadequate computing power, broadband connectivity and energy efficiency hinder large-scale AI deployment. These hindrances directly affect the scalability of AI-driven healthcare solutions.
Kenya’s health sector is overseen by multiple legal and policy frameworks which include: The Health Act (2017), National eHealth Policy (2016-2030), Data Protection Act (2019), Digital Health Act (2023) and the Social Health Insurance Act (2023). Whereas these laws provide a strong foundation for digital health, they also introduce complexities that affect the harmonisation and implementation of digital health solutions such as AI.
Besides, the fragmented approach of health as a devolved function between the national and county governments creates an additional barrier in digitalisation uniformity. This limits effective deployment and use of AI tools in healthcare, ultimately hindering optimal healthcare delivery.
AI is a transformative force in the healthcare system, aiding in diagnosing illnesses, assessing patients, detecting anomalies, and even in medical imaging, thereby providing faster, improved patient outcomes.
AI has many benefits, but it is not entirely faultless. The downsides, such as breach of data privacy, compromise its ethical use in society. Kenya has an inadequate health-specific AI strategy, and there is no dedicated steering committee to oversee and ensure the successful implementation of AI in healthcare.
Hence, formulated policies should not be restrictive, expensive, or burdensome for this developing field, which would rather benefit more from approaches that allow flexibility for developers and regulators to constantly explore and understand the latest developments.
Kenya continues to struggle with inadequate staffing and significant imbalances in the healthcare workforce. Statistics report the Kenyan doctor-to-patient ratio is estimated at 1:17,000 as of 2025, which falls below the WHO-recommended ratio of 1:1,000.
Limited resources and overstretched healthcare systems result in clinicians seeing a high volume of patients with a wide range of health complaints daily and making rapid diagnosis and treatment decisions, often with limited information.
These persistent shortages lead to stark disparities in the quality and accessibility of care across various health care settings. AI-based clinical decision support systems (CDSS) can support healthcare professionals by providing contextually relevant diagnostic and management suggestions. These systems can help minimize therapeutic errors and ensure appropriate referrals.
Penda Health, a private Kenyan Healthcare provider, demonstrates the feasibility of implementing AI in local healthcare settings. The hospital network has deployed AI-based clinical decision support systems into its clinical workflows, and its clinicians use them during consultations.
A study conducted across 16 Penda Health facilities in Nairobi and Kiambu counties demonstrated a gradual increase in the use of AI-enabled clinical decision support systems from 4 percent to 47 percent over an eight-month period.
The study also reported overwhelmingly positive feedback and increased confidence in interacting with the tool and in its ability to provide accurate management output.
Furthermore, the report demonstrated the AI tool’s ability to generate well-reasoned clinical suggestions and appropriate medications and to aid clinicians in reaching an accurate diagnosis. Penda Health AI adoption serves as a model for the healthcare sector. The use of these AI tools in the Kenyan context should augment clinicians’ decisions. Penda Health’s adoption of technology illustrates the successful integration of digital solutions into systemic infrastructure.
Beyond clinical decision-making, AI also has significant potential to strengthen health system operations, especially in pharmaceutical supply chains. Pharmaplus Pharmacy, a leading Kenyan retail pharmacy provider, demonstrates the value of AI beyond clinical care.
By integrating AI-driven tools into its pharmaceutical supply chain, Pharmaplus Pharmacy has improved demand forecasting, optimized stock management, and enabled early detection of near-expiry products. These efficiencies have reduced wastage and strengthened the consistent availability of essential medicines.
In contrast, recurrent drug stock-outs remain a significant challenge across many public health facilities in Kenya. This highlights a clear opportunity for policymakers to scale similar AI-enabled supply chain solutions within the public sector to enhance inventory management and address persistent medicine shortages.
Reliable internet coverage, improved electricity supply, and well-equipped health care facilities are the core foundation towards full realisation.
Besides, well-coordinated efforts between national and county governments that ensure policy alignment and resource allocation are equally critical. Kenya’s healthcare sector cannot delay harnessing these advancements, it must move with urgency.