28th May 2026
How can education and training play a key role in unlocking AI literacy and opportunities for local humanitarian leaders in Cameroon?
“We need to avoid a new digital inequality where only large international organisations benefit from AI transformation, while local actors remain behind due to lack of access, fractional training, or funding.“ – Ulrich Assouah
In this interview, we hear from Ulrich Assouah, Managing Director of IFP Humanitarian Studies, based in Douala, Cameroon. With a background in humanitarian leadership development, organisational governance, and capacity building for local NGOs and young professionals across Africa and fragile contexts, Ulrich brings a practitioner’s lens to the question of AI’s role in locally led humanitarian action.
Cameroon was the 8th highest respondent country in the HLA/Data Friendly Space Humanitarian AI January 2026 pulse survey (and 7th in the 2025 baseline study), with 43 respondents. The survey gathered responses from 1,729 individuals across 120+ countries and territories.
Key stats: respondents from Cameroon
- 72% of respondents from Cameroon told us that they’re using AI daily or weekly
- 21% rated their AI skill level as advanced, and 5% considered themselves to be expert (-1% and +2% compared to overall respondents respectively)
- 61% are using commercial AI tools like ChatGPT, and 26% are using custom-built AI agents
- 14% said that their organisation has a formal AI policy (-9% compared to overall respondents)
- 72% believe that AI has improved operational efficiency (+7% compared to overall respondents) and 63% believe that AI has led to better decision-making (+9% compared to overall respondents)
In his own words, drawn from an interview conducted by HLA research co-lead Ka Man Parkinson, Ulrich shares how he is currently using AI, what he is hearing from the more than 100 local NGOs his organisation works with, and what he believes must change.
Introducing Ulrich and his approach to AI
My work focuses on strengthening humanitarian leadership, professional development, organisational governance, and capacity building for students, young professional NGOs, and local humanitarian actors, particularly in Africa and a fragile context.
Over the years, I have worked closely with vulnerable communities, refugees, education initiatives, local organisations, and humanitarian training programmes. Through these experiences, I have seen both the opportunities and the limitations faced by local actors in accessing quality knowledge, innovation, and global networks.
My approach to AI in humanitarian work is a human-centred and locally driven one. I believe AI should not replace humanitarian value – that is really important – nor human judgement or community engagement. Instead, AI should serve as a tool to strengthen decision-making, improve efficiency, democratise access to knowledge, and empower local organisations that often operate with limited resources.
For me, the future of humanitarian AI must be ethical, inclusive, context sensitive, and accessible to local actors, especially those in low resource settings who are often excluded from technological and transformation discussions.
AI as a tool for education and training, mentoring and coaching
Currently we are using AI in several practical ways within our work and training ecosystem. First, AI supports content development for humanitarian education and professional training.
We use AI-assisted tools to help structure training materials, develop strategic documents, improve communication, and simplify complex humanitarian concepts for learners.
Secondly, AI is helping to strengthen organisational productivity. It supports proposal drafting, reporting, strategy planning, communication workflow, research, and multilingual content adaptation – especially between English and French.
And AI is becoming a tool for capacity building and digital literacy. We are increasingly introducing humanitarian students and local NGOs to responsible AI use, including ethical considerations, AI-assisted learning, and practical application in humanitarian coordination and management. My one major direction is to integrate humanitarian AI into our training programmes through workshops, certifications, webinars, and practical learning spaces focused on ethical AI adoption, humanitarian governance, digital transformation, and operational readiness.
I also see significant potential in using AI to strengthen local organisation systems, including in knowledge management, proposal development, project monitoring, communication and visibility, multilingual learning, and why not strategy and decision-making.
When I use it as a mentor or a coach, I’m using AI as a sounding board to test ideas, to get different perspectives, based on the context and the need of those local organisations.
Demand from local NGOs for AI capacity strengthening
Last week, we did a webinar on how AI can help leaders in local NGOs. We got more than 50 attending participants. And at the end, they told us that the webinar was not enough – they need training now, because they would like to know more about how they can use those tools, how those tools can help them in their daily activities. Based on that, they can easily have to write, even writing a proposal, and all the rest.
From our own point of view, the demand is enormous. We have more than 100 local NGOs that have engaged with us in terms of providing capacity building and structuring. So we did a survey based on the context where we are, and based on the reality that they encounter daily. What has come out from the survey is that they have difficulty in terms of funding, in terms of resource mobilisation, as everywhere nowadays. But the point is that they find it difficult to even identify the tools for AI that can be suitable to them.
For instance, they are looking for funding. With AI, they can easily know and identify the donors or funders who can provide them funding according to their area of expertise or area of intervention on the field. In terms of writing proposals, how can their proposal be suitable to the donors so that they can be selected to receive the grant? How can they do proper reporting – financial reporting, activity reporting that is suitable for donors? And even how can they collect data on the field? They can still use AI for that.
But what also comes through strongly is visibility. They need to use tools that can easily give them the opportunity to communicate, to be well known as a local NGO that is specialised in a specific area. Many of them have a positive impact with low financial resources – but they have a real, good positive impact on the field with those vulnerable people that they encounter daily. We have to do things differently, based on the fact that the context is totally different. We need to guide them according to their area of expertise, according to their need, such a way that they can easily approach the challenges that they will face on the field.
AI tools: language, context, and the question of access
In Cameroon, we use French and English – because we have two different aspects: the French-speaking and the English-speaking communities. But we also have more than 250 dialects. In the Anglophone area, we have what they call Pidgin. Pidgin is a language that is more common among youth, teenagers, students. So Pidgin is more frequent, and that could be an opportunity for AI – it’s something that most of Cameroon can relate to.
The point is that AI should not be something that is already reserved for certain levels of people, categorised for some levels of people. No. It should be like: everyone can – once you have a phone, a mobile phone, you can easily have AI. We can make sure that those who speak French or English can see their sayings in it. And as the Pidgin language is well known in Cameroon, it can be an opportunity.
When we put in Pidgin, easily they can understand. That’s something that ChatGPT handles. Most of the people we work with are using ChatGPT. Some are using Gamma for PowerPoint. Some are trying to use Claude, but Claude requires payment, so not everyone can do that. And some are using other tools to do video.
The access question extends further too. I discussed with the leader of a local NGO who works daily with disabled people, and he raised the idea of using AI to support them – using the voice function, for instance, so that someone who is blind or who cannot easily read can use their voice and ChatGPT can easily respond. How can we adapt these tools for disabled people? That is the point.
AI for improved targeting and assistance
In terms of gathering data, for instance, we can go into the community, gather information, and based on that information, we can easily ask AI to tell us exactly the need of the community based on what we have gathered on the ground, on the field. AI can easily tell us exactly those who are interested in a specific area, and how we can prioritise those who are really in need. That is where AI can easily help us.
Having that basic information that we have collected on the ground – by using tools like KoboCollect, for instance – when we come out with it, it will be easier for us to use AI to prioritise the needs of the beneficiary, the needs of the community. Based on that, we should easily identify where they need support, how we can support those who are really in need rather than prioritise a specific area and leave those who are truly needed. We need to have the database. Once we have it, AI can do the work.
Education for AI preparedness and readiness
The real risk is that technological progress moves faster than ethical preparedness and organisational readiness, especially in vulnerable contexts where we are. We are not always aware of what is really going on elsewhere, because the time it takes for things to reach here in Africa means the capacity, the frame, the rapidity – it is totally different. That is the reason why AI literacy, governance frameworks, local leadership and inclusive participation are extremely important.
We also need to avoid a new digital inequality where only large international organisations benefit from AI transformation, while local actors remain behind due to lack of access, fractional training, or funding. Humanitarian AI should ultimately strengthen humanity, accountability, and local ownership, not weaken them.
Shared progress will require collaboration between humanitarian practitioners, researchers, educators, technologists, donors, and communities themselves. Responsible innovation must be collective, practical, and grounded in real humanitarian reality.
Education is the base. How can we educate people how to use AI? All the different types – Gemini, Copilot, ChatGPT, Claude, and all the rest. We have to give them training by telling them: ChatGPT can generate a flyer, Gemini can generate video – but what is really essential? What is your need? First, go and do the research online to have a proper and a good understanding of what you really want to do. Based on that, now you can ask AI to give you a little support.
Ulrich’s message for the sector – and his vision for local AI
I believe that AI is interesting, but AI needs to be structured. As we are in a different type of context, we need to engage and take into consideration our own proper context. That is why I usually say: we need to have our own proper AI and contextualise it in the fact that we are here in Africa. When we have it at that level, a policy can come out. When the policy comes out, it will have a proper strengthening and a proper understanding in terms of how we can use it with more dignity, with more humanity – and how local ownership can easily see their own interests and their own opportunity by using AI.
We in Cameroon are really open for that. I was planning, if we have the funding, to organise a big conference – maybe a forum concerning AI in the humanitarian field. That is something we are discussing. It seems like people still have that fear about AI. Some of them are interested, but they don’t know how to use it. They don’t know the output of these tools. So there is a great opportunity to raise that. And specifically here in Cameroon, the demand is really enormous.
Humanitarian AI should ultimately strengthen humanity, accountability, and local ownership, not weaken them.
This interview was conducted as part of the Humanitarian Leadership Academy and Data Friendly Space’s ongoing Humanitarian AI research initiative, which builds on the 2025 foundational study and the January 2026 pulse survey. Supporting resources – including reports, podcasts, webinars and microlearning guides – are available on the research landing page.
Disclaimer
The views and opinions expressed in this interview are those of the featured individual and do not necessarily reflect those of their affiliated organisations. This resource has been produced as a contribution to ongoing discussions on the use of AI in the humanitarian sector. Publication does not constitute endorsement of any specific technology, individual, organisation or approach.
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