Building Digital Capacity: Two Days That Transformed How Uganda's CSOs Think About AI

Forty participants. Two days. One mission: demystifying artificial intelligence for the organizations doing grassroots development work.

Standing in the registration area at Igongo Cultural Centre in Mbarara on the morning of November 21st, 2024, I watched as civil society leaders from across Central and Southwestern Uganda filed in. Some came with excitement, others with skepticism, and many with simple curiosity about whether AI was actually relevant to their work.

As project lead for this Tech Talk workshop - part of the broader Localizing Artificial Intelligence for Grassroot Impact initiative - I'd designed the two-day program to answer that question definitively. But I knew that my answer wouldn't matter. What mattered was whether these CSO leaders would leave with practical skills, real confidence, and a fundamentally different understanding of what's possible.

Two days later, watching participants practice building data dashboards and creating chatbots for community engagement, I had my answer.

The Context: What We Learned Before We Taught

This workshop didn't emerge from theory. It emerged from research.

Between September 27 and October 10, 2024, Kampala Analytica and GIZ conducted a baseline survey engaging over 40 respondents from 20 CSOs across Central and Southwestern Uganda. We used key informant interviews and focus group discussions to understand how AI was being localized for sustainable development.

The findings challenged assumptions.

Contrary to the perception that grassroots areas are isolated from AI advancements, we found CSOs already beginning to adopt AI tools to improve operational efficiency, resource mobilization, and outreach. More importantly, we found strong interest in gaining AI skills - indicating high demand for exactly the kind of capacity-building we were about to deliver.

But we also found barriers: limited infrastructure, digital literacy gaps, and genuine concerns about ethics and data privacy.

This baseline shaped everything about how I structured the workshop. We weren't going to lecture about AI in the abstract. We were going to show CSO leaders exactly how AI could solve their specific problems, using tools they could actually access and afford.

Day One: Foundations, Context, and Honest Conversations

Setting the Stage

After opening remarks from GIZ's Advisor on Digitalization, emphasizing GIZ's commitment to advancing digital solutions for grassroots impact, I provided an overview of the day's roadmap. The goal wasn't just knowledge transfer - it was creating the foundation for sustained engagement with AI.

Dr. Viola Nyakato delivered a keynote that reframed the conversation entirely. She traced AI's evolution from theoretical models to practical applications in social impact, highlighting Uganda-specific opportunities like AI for agricultural forecasting and education. But more importantly, she addressed the elephant in the room: ethical challenges, emphasizing transparency and inclusivity.

This set the tone. We weren't selling AI as a silver bullet. We were presenting it as a powerful tool that requires thoughtful, ethical implementation.

The Baseline Findings

When Christopher Okidi, CEO of Kampala Analytica, presented our baseline survey findings, the room came alive. Participants recognized their own experiences in the data - the growing interest in AI, the infrastructure limitations, the ethical concerns, and the examples of AI tools already improving operational efficiency.

This wasn't abstract anymore. This was their reality, validated by research.

Digital Literacy as Foundation

In my session on digital and AI literacy, I introduced the Digital Literacy Handbook we'd developed specifically for this initiative. But rather than lecture, I facilitated an interactive exploration.

The conversation revealed what the survey had suggested: CSO leaders weren't starting from zero, but they needed structured frameworks to understand how AI tools fit into their existing workflows. We discussed foundational digital skills for navigating AI tools - not as prerequisites that excluded people, but as building blocks that empowered them.

The Interactive Session: Learning from Experience

The day's most valuable session might have been the simplest: an interactive discussion where participants shared their experiences with digital tools.

Facilitated by AI and civil society experts, this session surfaced common themes: the need for localized AI solutions that work with limited infrastructure, the importance of capacity building that's sustained rather than one-off, and the reality that CSOs need practical tools, not just theoretical knowledge.

One participant from a youth-focused organization described how they'd tried using a sophisticated donor management system but abandoned it because it required constant internet connectivity - which they simply didn't have in their rural office. This prompted a conversation about designing AI solutions for the contexts they'll actually be used in, not the contexts we wish existed.

That kind of honest exchange shaped how I approached Day Two.

Day Two: From Theory to Practice

Day Two was about getting hands dirty. I facilitated the opening session on content creation and communications, demonstrating tools like Canva for graphic design and Metricool for social media management.

But demonstration wasn't enough. Participants created infographics in real-time, automated social media posts, and collaborated on visual content. The energy in the room shifted - this was no longer about whether AI was relevant to CSO work. This was about how quickly they could integrate these tools into their operations.

Fundraising and Resource Mobilization

Morine Amutorine led a session that addressed one of CSOs' most pressing challenges: securing sustainable funding. She presented AI tools for prospecting, chatbot integration for donor engagement, and predictive analytics for campaign optimization.

Participants practiced creating campaign strategies using AI models. I watched one organization leader - initially skeptical about "machines handling fundraising"—build a donor prospecting workflow that could save her team hours of manual research weekly.

Research and Proposal Writing

Christopher Okidi's session on generative AI for research and proposal writing tackled another pain point. CSOs spend enormous time drafting proposals and research briefs. Christopher explored natural language processing tools for summarizing data and drafting proposals, and participants created sample research briefs during the session.

The reaction was telling. People weren't thinking "this will replace our work." They were thinking "this will free us to focus on the work only humans can do - building relationships, understanding community needs, making strategic decisions."

Social Accountability and Data

Alban Manishimwe introduced AI-driven data tools for social accountability - dashboards and geospatial tools for citizen reporting. Participants practiced building data dashboards tailored to community needs.

One participant from a governance organization realized she could create a dashboard visualizing budget expenditure data that would make accountability reporting far more accessible to the communities she served. She sketched it out on paper during the session, planning how to implement it within weeks.

Global Perspectives

We livestreamed sessions from an AI Global Event, featuring Prof. Dr. Davit Sahakyan discussing global AI trends and their implications for grassroots impact, and Ms. Rokaiya Purna sharing insights on empowering creative industries through technology.

This global perspective mattered. It showed participants that they weren't isolated - that civil society organizations worldwide were grappling with similar questions about how to harness AI ethically and effectively.

The Civic Hackathon Introduction

I introduced the upcoming Civic Hackathon (which would later take place in January 2025), encouraging participants to consider proposals for AI-driven solutions. Several teams in the room would eventually participate and win grants - but that's a story for another article.

What Actually Changed: Measuring Impact Beyond Skills

The formal outcomes were significant:

But the real transformation was subtler and more profound.

In the reflections session, participants shared stories of improved confidence and deeper understanding of AI applications. One leader said something that stuck with me: "I came here thinking AI was for tech companies. I'm leaving knowing it's for anyone committed to solving problems."

Another participant noted: "The hands-on practice was crucial. I've attended workshops where we just talked about tools. Here, we actually used them. Now I know I can go back and implement this."

The Challenges We Didn't Solve (And Why That's Okay)

The workshop surfaced challenges we couldn't solve in two days:

Infrastructure deficits, especially in rural areas, remain a real barrier. You can't use cloud-based AI tools without reliable internet.

Limited technical expertise within many CSOs means that even with training, sustained implementation requires ongoing support.

The high cost of some AI tools creates accessibility issues for organizations operating on shoestring budgets.

But acknowledging these challenges openly was itself valuable. It prevented the false promise that AI would magically solve all problems. Instead, it focused our attention on practical solutions: prioritizing AI tools that work offline or with limited connectivity, building peer support networks for troubleshooting, and identifying free or low-cost alternatives to expensive platforms.

What This Means for CSOs: Lessons for Digital Transformation

Having now managed both this Tech Talk workshop and the subsequent Civic Hackathon, I see clear patterns about what works for CSO digital transformation:

Start with the actual conditions CSOs operate in - the infrastructure they have, the skills they possess, the budgets they manage - then identify AI solutions that fit. Don't start with impressive technology and force-fit it to contexts where it won't work.

Participants didn't just need to know that Canva exists or that chatbots can engage donors. They needed to actually create a graphic, actually build a simple chatbot, actually experience the workflow. That's what built confidence and capability.

The interactive sessions where participants shared experiences and challenges were as valuable as the facilitated training. CSO leaders learn powerfully from each other's successes and failures.

From Dr. Nyakato's keynote through every subsequent session, we emphasized that AI implementation must prioritize data privacy, inclusivity, and transparency. This isn't just good practice - it's essential for maintaining community trust.

This is why we committed to monthly Tech Talks and ongoing resource access. Digital transformation isn't an event; it's a process. CSOs need sustained support, not just initial training.

The Digital Literacy Handbook, the AI resource repository on Kampala Analytica's website, the specific tools demonstrated - these tangible resources mattered more than abstract frameworks.

The Ripple Effect: From Workshop to Ecosystem

Looking back now, having also managed the Civic Hackathon that emerged from this workshop, I see how this two-day Tech Talk was a catalyst.

Several participants from Igongo would go on to participate in the January hackathon. The networks formed in Mbarara would facilitate collaborations that extended well beyond both events. The confidence built in those hands-on sessions would translate into actual AI implementation in CSO operations.

This is what successful capacity-building looks like: not just a one-time knowledge transfer, but the initiation of ongoing learning, experimentation, and mutual support.

Moving Forward: Building on the Foundation

The partnership between Kampala Analytica and GIZ, with support from the European Union, represents a commitment to sustained engagement with CSO digital transformation. The monthly Tech Talks we committed to aren't just follow-up - they're recognition that this work is never truly "done."

AI will continue evolving. CSO needs will continue changing. Infrastructure in Uganda will (hopefully) continue improving. The ethical challenges will become more complex, not simpler.

But what we established at Igongo Cultural Centre those two days in November was something foundational: a community of CSO leaders who understand that AI isn't something that happens to them, but something they can actively shape and deploy for grassroots impact.

As I reflect on my role as both project lead and facilitator, what I'm proudest of isn't the specific tools we taught or the number of participants we trained. It's the shift I saw in how people approached the intersection of technology and social impact.

They came with questions about whether AI was relevant. They left with questions about which AI applications to implement first - and that's precisely the transformation we were working toward.

For CSOs Considering AI Adoption

If you're leading a civil society organization and wondering whether AI is relevant to your work, here's what I learned from those two days in Mbarara:

AI isn't relevant because it's trendy or because donors are talking about it. AI is relevant when it solves a specific problem you're actually facing.

Does your team spend hours manually compiling data for reports? AI can help.

Are you struggling to reach donors who align with your mission? AI can help.

Do you need to make complex data accessible to the communities you serve? AI can help.

But start with the problem, not the technology. And start with tools that work in your actual context - not the context you wish you had.

The future of civil society isn't about organizations becoming tech companies. It's about organizations thoughtfully deploying technology to amplify their mission, reach more people, and create more impact.

That's the future we're building toward—one workshop, one hackathon, one practical AI tool at a time.

Marshal Owach was the Project Lead for the Localizing Artificial Intelligence Solutions for Civil Society Organizations initiative at Kampala Analytica. He specializes in helping CSOs across East Africa navigate digital transformation through capacity building, partnership development, and practical technology implementation. His approach centers on localized solutions that work in actual African contexts, not idealized Western assumptions. Connect to explore how your organization can thoughtfully harness AI for grassroots impact.