The healthcare sector in low-resource settings faces ongoing challenges that directly affect accessibility, continuity, and quality of care. In this context, emerging technologies – particularly Artificial Intelligence (AI) – have the potential to make healthcare more efficient, support overworked staff, and improve both clinical care and daily operations. 

On 17 July, the Future of Hospitals and Health Systems Initiative, in partnership with l’Agence Française de Développement (AFD) hosted a webinar on: “AI in Action: Supporting the healthcare workforce in low-resource settings.” With low- and middle-income countries expected to face a shortfall of 11 million health workers by 2030, speakers explored scalable innovations, potential pitfalls, and policy implications. Here are the main takeaways: 

Reducing waiting time and boosting capacity 

Vivek Rajagopal from Narayana Health in India highlighted how AI is helping tackle one of healthcare’s most persistent inefficiencies: waiting. Patients often wait hours for doctors, while doctors waste time waiting for lab results. In countries where health data is not fully digitised, patients often arrive with 200-page physical records of past medical history – documents impossible for doctors to fully review in a few minutes.  

“Now imagine AI in this scenario. AI can fill in the gap by automatically going through the 200 page document and summarising it for the doctor.” Vivek shared.  

Tools like automated record summarisation and real-time scheduling can double the number of patients treated – delivering more care without needing more infrastructure. He also stressed that AI tools must be simple, practical, and fit into daily routines.  

Putting people first, empathy and equity 

Professor Asad Mian from Evercare challenged participants with a powerful question: What if innovation followed empathy instead of hype? His work across Pakistan, Nigeria, and Kenya focuses on co-creating AI tools with frontline workers – individuals who are crucial to delivering care but often feel invisible. From emergency triage systems to multilingual paediatric storytelling programmes, his team places human-centred design at the core of innovation. 

“ Co-create with the people on the ground and the technology will be much more powerful and sustainable.” 

Evercare team’s AI philosophy is about using AI to scaffold safety, empathy, equity, not erase them. Every tool is tested with frontline staff and built with clear rules and accountability. 

AI for training and workforce development 

Shaukat Ali Khan of Aga Khan University (AKU) shared how long-term institutional commitment has made AI an integral part of both operations and education. Today, AKU embeds AI across 40+ use cases – from outpatient scheduling to real-time clinical transcription in multiple languages. AI is not just a tool for operations, it’s also built into AKU’s medical training system. All staff receive support to build AI skills, and medical students learn AI literacy as part of a five-year curriculum. 

“AKU’s ICT division is on a mission to ensure access to quality digital resources and technologies for all”. 

AKU’s approach ensures not just technological implementation, but responsible, inclusive adoption built on policy, education, and collaboration. 

Ethics, equity, and governance must guide AI 

Scott Mahoney from the Gates Foundation, closed the webinar by tying together AI’s growing capabilities with the ethical responsibilities that must guide its use. With AI tools increasingly developed for high-resource contexts, there’s an ever-present risk of bias and exclusion in LMICs. 

He outlined some of AI’s biggest benefits: 

• Making expert knowledge more widely available 

• Reducing paperwork and admin burden 

• Lowering costs per patient visit 

• Improving system-wide visibility 

“Co-creation across the board helps with the engagement with systems change and it also leads to improvements in the AI literacy of staff as well.” 

He also stressed the importance of gender-sensitive approaches to AI design, rigorous monitoring and evaluation and interoperability, ensuring AI tools are connected and sustainable. 

Whether it’s scheduling appointments, training medical students, or creating empathetic care experiences, the message from all speakers was clear: AI should enhance – not replace – the human touch in healthcare. From ethical design to responsible deployment, participants were reminded that the process has to focus on ethical AI, democratisation, co-creation, people-first design and training, retraining, and reskilling.