This AI revolution is sweeping over the healthcare space, offering everything from assistance for health professionals taking care of patient data to expanded access to medical facilities. Healthcare around the world will look very different in the coming years as a result of this movement toward AI-driven care. The big question on the minds of many:
Will artificial intelligence deliver better care to those who need it the most?
Through the Global Initiative on Artificial Intelligence for Health (GI-AI4H), the World Health Organization (WHO) is exploring this very question. The initiative leverages an array of partnerships to guide ethical AI development by the world’s governments, health facilities, researchers, tech experts, and civil society.
This is a great movement for NGOs focused on public health, community-building, healthcare, and digital health to follow.
What Is the WHO Global AI for Health Initiative?
Co-convened by the WHO together with the International Telecommunication Union (ITU) and the World Intellectual Property Organization (WIPO), the Global Initiative on AI for Health’s objective goes beyond promoting the adoption of AI by organizations. It investigates the deployment of AI across the health sector that is safe, responsible, effective, and affordable. The initiative is multifaceted in scope and includes health data governance, privacy protection, standard setting, capacity-building, and how AI can be made to be part of the routine of a health sector. It is from here that NGO interest in the Global Initiative is derived, as most nonprofit entities were perhaps all testing technology around the globe, solving problems of daily needs.
WHO Wants Real-World AI Experiences
Among the most captivating aspects of the initiative is its request for actual health care case studies for AI. The WHO is soliciting organizations that are already delivering solutions based on AI at an actual health-care and health-system level. In this program, organizations need to submit their story about which healthcare problem they aim to address, the deployment method used for implementing their AI solution, and the achievements obtained (e.g., quantitative and qualitative improvements), in addition to lessons learned and best practices learned for the initiative.
This initiative comes to life with cases where AI is actually being implemented and moved from an AI model existing inside a laptop to a solution on the front line of care delivery. An organization could be using AI in different contexts (e.g., assisting healthcare practitioners, information management, health communication, data analysis, and accessibility): they need not be responsible for actually developing in-house AI models, but their AI solution must have already seen the light of day for healthcare decision-makers or patients or caregivers, with valuable data/results on how successful their AI solution has proved.
Why NGOs Have an Important Role
NGOs often work directly with communities that are underserved by traditional healthcare systems.
They may work with people in rural areas, low-income communities, humanitarian settings, or places where healthcare facilities and trained professionals are limited.
This gives NGOs an important perspective.
A technology company may build an impressive AI system, but a local NGO may be the organization that understands whether people can actually use it.
For example, an NGO may know that a health application is difficult to use because people have limited internet access. It may discover that health information needs to be available in a local language. Or it may find that communities are hesitant to trust an automated system.
These experiences matter.
Technology can provide the tool, but communities determine whether that tool actually works.
AI Should Solve Real Problems
One of the biggest lessons NGOs can take from this initiative is that AI should not be introduced simply because it is popular.
The first question should always be the following:
What problem are we trying to solve?
Perhaps health workers spend too much time organizing information. Maybe patients struggle to find reliable health information. Perhaps language barriers make communication difficult.
Once the problem is clearly understood, an organization can consider whether AI is actually the right solution.
Sometimes it will be.
Sometimes a simpler solution may work better.
This approach can help NGOs avoid investing time and money into technology that looks impressive but does not solve a real community need.
Responsible AI Is Just as Important
Using AI in healthcare comes with serious responsibilities.
Health information can be extremely sensitive, and NGOs may work with personal information about patients, beneficiaries, families, or communities.
Organizations therefore need to think carefully about privacy and data protection.
They should ask:
- Who can access the information?
- Where is the data stored?
- How is it being used?
- Is personal information protected?
- Could the AI produce incorrect information?
- Could certain communities be unfairly affected?
- Who reviews the AI’s decisions or recommendations?
These questions become especially important when AI is being used in healthcare.
A system that produces an incorrect answer in a general administrative task may create inconvenience. A system providing health-related information could have much more serious consequences.
WHO Is Also Exploring Privacy-Preserving AI Evaluation
The initiative also includes a global benchmarking challenge focused on evaluating health AI while protecting sensitive data.
The challenge explores ways to test AI models while allowing healthcare data to remain protected rather than simply being shared with model developers.
This is particularly relevant as more healthcare organizations begin experimenting with AI.
Organizations need ways to understand whether an AI system is accurate and reliable without putting patient information at unnecessary risk.
For NGOs handling health data, this is an important area to follow as responsible AI practices continue to develop.
How Can NGOs Get Involved?
If an NGO already has an AI project operating in a healthcare setting, it can start by documenting the experience carefully.
A useful case study should be able to answer simple questions:
- What problem were we trying to solve?
- Why did we choose AI?
- How was the technology used?
- Who benefited from it?
- What results did we see?
- What problems did we face?
- What did we learn?
These questions can help an organization turn an AI project into a meaningful real-world case study.
According to the WHO, the current call for implemented AI health case studies has a deadline of 23 August 2026 at 23:59 CEST. Selected case studies may be included in the initiative’s meeting report, while some may be invited to present at the September 2026 meeting in Hangzhou, China. Submission does not guarantee selection or endorsement.
Small NGOs Can Have Something Valuable to Share
It is easy to assume that global AI initiatives are only relevant to large international NGOs with technology departments and large budgets.
But that is not necessarily true.
A small NGO may have a much closer relationship with the people it serves. It may understand local healthcare barriers, cultural concerns, language needs, and community expectations better than a large organization.
That knowledge can be extremely valuable when evaluating whether an AI solution is actually useful.
The important question is not
“How big is the organization?”
It is:
“What problem did the organization solve, and what did it learn from the experience?”
What NGOs Can Start Doing Now
Even if an NGO does not currently have a project that fits the WHO opportunity, there are steps it can take to prepare for the future.
Organizations can start by improving staff understanding of AI, identifying practical problems where technology could help, creating basic guidelines for responsible AI use, and strengthening data protection practices.
They can also begin documenting small technology projects.
A pilot project that saves health workers time, improves communication, or helps organize community health information could provide valuable lessons for future work.
Most importantly, NGOs should involve people in the process.
AI should be introduced to communities and healthcare workers—not simply for them.
The Bigger Opportunity for NGOs
The WHO initiative represents a wider change in the way the world is thinking about AI and healthcare.
The conversation is gradually moving from
“What can AI do?”
to:
“What can AI do safely, responsibly, and meaningfully for people?”
That shift creates an important role for NGOs.
Technology companies may develop the tools, but NGOs understand what happens when those tools reach real communities.
They can identify barriers, gather feedback, measure results, and explain what works—and what doesn’t.
This real-world experience can help shape better AI solutions in the future.
Looking Ahead
AI is likely to become a bigger part of healthcare in the coming years. But successful adoption will not depend only on better technology.
It will also depend on trust, privacy, evidence, human oversight, and community involvement.
For NGOs, this means there is an opportunity to become more than users of AI. They can become contributors to the conversation about how AI should be used in healthcare.
The organizations that understand both technology and people may have the strongest role to play.
Final Thoughts
The WHO Global AI for Health Challenge is an important opportunity for organizations already using AI in healthcare to share their experiences and contribute to a wider global conversation.
For NGOs, the message is simple:
You do not need to build the next big AI model to contribute to the future of AI in healthcare.
If your organization is using technology to solve a real healthcare problem, your experience could provide valuable lessons for others.
AI may be changing healthcare, but technology alone will not create better health outcomes.
The real impact will come from combining technology with human knowledge, community trust, responsible decision-making, and a clear understanding of the people healthcare is meant to serve.
