From an AI and data governance perspective, the Festival offers a uniquely practical and globally grounded conversation about how countries can shape digital and AI futures that work for them. Rather than treating AI as a standalone technology, the programme connects it to the broader systems that make equitable innovation possible: strong public data systems, governance, interoperability, institutions, partnerships, and public trust. It brings together policymakers, statistical leaders, technologists, and practitioners to explore the opportunities and governance challenges of emerging technologies, with a strong emphasis on implementation, inclusion, and Global South leadership.
Sessions not to miss
AI and Emerging Technologies: Opportunities, Risks and Realities (June 4, 9:30 a.m.) I'm biased because I helped shape this one, but I genuinely think it's one of the few sessions trying to situate AI within actual governance, infrastructure, and power realities instead of treating it as inevitable magic technology.
Connecting AI Governance to AI in Practice (June 3, 8 a.m.) Also biased. We created this session in response to a gap: too many sessions were discussing the big picture without linking it to practical realities. The global AI governance conversation is still too abstract and disconnected from implementation, especially in lower- and middle-income countries.
Getting Public Sector Data Infrastructure Ready for AI: A New Joint Initiative (June 3, 11 am) A closed session, but honestly one of the most important in the whole AI track. "AI readiness" is mostly a data systems, interoperability, governance, procurement, and institutional capacity question — and this one treats it that way.
Building Culturally-Grounded AI Content Safety Systems for African Languages (June 3, 4 pm) Exciting because it pushes against the deeply Western-centric assumptions embedded in most AI systems and raises real questions about language, context, culture, and representation.
The Disability Data Desert: Who Is Missing from Africa's AI Systems? (June 3, 8 am) This gets at a fundamental issue: AI systems reproduce exclusion when entire populations are invisible or poorly represented in the underlying data.
Decoding Bias at Scale and Rewriting Equity: An AI Lab for Inclusive Statistical Classifications (June 3, 2 pm) Worth attending because it moves beyond generic "bias in AI" discussions into the actual mechanics of how classification systems shape visibility, policy, and power.
Inclusive Digital Financial Services: Building Trust through Responsible AI and Data Governance (June 3, 4pm) Financial inclusion AI conversations often ignore governance, safeguards, and asymmetric risks for vulnerable populations. This one doesn't.
Scaling AI and Telehealth in Public Health: What Works, What Doesn't, and What's Next (June 4, 8 am) The framing alone sets it apart — implementation-oriented rather than hype-oriented. We need more honest conversations about what actually works.
AI Opportunities for Enhanced Climate Change Data: A Global South Perspective (June 3, 11 am) Valuable because climate AI conversations are often dominated by institutions from the Global North, despite the fact that climate impacts are deeply unequal.
Moving Targets: How Do We Measure AI Impact When the Tool Keeps Changing? (June 4, 4 am) One of the smartest framing questions in the programme. Governance, accountability, and evidence all become extremely difficult when technologies evolve faster than institutions can respond.
Collaborative Data Ecosystems: Building AI-Ready Data for Better Decisions (June 5, 8 am) Foundational. AI conversations tend to skip over the fact that usable, trusted, interoperable data ecosystems are the prerequisite for almost everything else.
Advancing AI and Data Science through Inclusive Collaboration for Equitable Official Statistics (June 5, 8 am) Exciting because NSOs and official statistics communities are finally being recognised as central actors in trustworthy AI ecosystems, rather than peripheral technical stakeholders.
Explore the full program here.
One thing to watch for
A key theme emerging across many of these sessions is the gap between AI ambition and the governance, data systems, and institutional capacity needed to back it up. The programme reflects an important shift from viewing AI solely as a technology conversation toward understanding it as a broader question of inclusion, infrastructure, stewardship, and public trust. One particularly important question running through the Festival is how countries and institutions can shape AI systems in ways that reflect their own priorities, contexts, and development goals while navigating rapidly evolving global technological ecosystems.