How Civil Society Adapts — and Leads — Through Tech and Turbulence. Civil society is navigating two disruptions at once: rapid advances in AI that are reshaping how organizations operate—and sweeping shifts in policy, funding, law, and public trust that are redefining the space in which they operate at all. This opening plenary sets the stage for the Summit with a grounded look at both realities. Leaders from law, philanthropy, and global nonprofits explore how organizations can adapt their strategies, governance, and use of technology while the rules of the game are changing around them

This fast-paced showcase highlights practitioners who are already applying AI and data to deliver tangible outcomes across issue areas. Multiple concise lightning talks spotlight what’s working, what’s been learned, and what others can adapt — grounded in implementation rather than theory. Together, these talks provide concrete examples of how innovation is unfolding across the ecosystem today, and what it takes to move from idea to impact at scale.

Demand for AI-enabled solutions across the social sector is rising rapidly — but the pathways to capital remain fragmented, unclear, and often misaligned with how technology is actually built, governed, and sustained. This session brings funders, investors, leaders from technology companies serving the social sector and nonprofit technology leaders together to examine how to connect “shovel-ready” solutions to appropriate forms of funding so capital can better support real solutions — not just pilots.

Operational AI & Data in Crisis and Conflict -- Humanitarian organizations operate in environments defined by urgency, uncertainty, and ethical risk. This session explores how AI and advanced data systems are being deployed today to improve situational awareness, logistics, targeting, and coordination — without compromising trust or safety. Highlighted solutions will examine real use cases from humanitarian response, lessons learned from deployment at scale, and the infrastructure and governance required to responsibly use AI when stakes are highest.

AI systems increasingly shape access to opportunity, justice, and public services — often without meaningful accountability. This workshop grounds AI and AI governance in civil rights and constitutional principles. Featured solutions will explore frameworks for embedding equity, due process, and transparency into AI systems, and the role legal institutions, regulators, and civil society must play in setting enforceable guardrails.

AI & Data Solutions Driving Measurable Climate Impact. This fast-paced showcase features practitioners applying AI and data to accelerate real-world climate solutions—from emissions reduction and energy optimization to resilience, adaptation, and climate justice. A series of concise lightning talks highlights what’s working, what’s been learned, and what others can replicate—grounded in deployment, not theory. Speakers share practical tools, implementation lessons, and measurable outcomes that move climate action from pilots to scale.

In this session co-presented by Digital Promise and DrivenData, we will talk about what it means to build AI infrastructure in a particular social sector. It will be a case study for the theory behind a program we have just launched that will fund AI infrastructure for K-12 education. It is focused on how to build infrastructure that improves AI for a particular domain, through investments in data, models, and benchmarks. It will cover how this is different from investments in AI capacity (ability to use existing AI tools) and AI progress (such as compute infrastructure). We will talk about how and why education is a good domain for this initiative and what other domains should consider for their own education infrastructure.

Safety, Development, and Design Choices Matter -- Children are increasingly exposed to AI-driven platforms shaping learning, relationships, play, mental health, and even their ability to think. This session examines how AI and data tools intersect with child development, online safety, education, and more. The session will explore emerging risks, design principles and policy gaps for child-centered AI — along with the responsibilities of platforms, governments, nonprofits, educators, and parents in safeguarding young people.

What does it actually take for a nonprofit to move from promising pilot to scalable, AI-enabled impact? This session spotlights the efforts successful accelerators -- including Fast Forward and Google.org -- to back mission-driven organizations building and deploying data and AI solutions—and puts the focus where it belongs: on the nonprofits themselves. Through a fast-paced lightning round, participating organizations share the real work behind their solutions—what they built, what they learned, and what it took to implement in the field. Along the way, Fast Forward and Google.org reflect on how accelerators, funders, and technology partners can better align capital, capability, and community to help solutions scale.

This is a hands-on session about building AI products that balance empowerment and impact with governance and risk. We'll start with a real use case from your own work, then walk through how to think about what AI is really doing. In plain language, without requiring technology expertise, we'll walk through making simple maps of where AI can help, and where it creates risk. From there we'll get into the practical product design: how to connect AI to verified information so it doesn't make things up, when to escalate to a human, and how to limit what AI can and can't do. This workshop builds on real world experiences building governed AI tools for nonprofit, government and global enterprises. You'll walk away with a one-page product blueprint and a way of thinking about AI decisions you can use in your real work.

AI adoption fails more often due to people and process than technology. This workshop focuses on the organizational realities of AI change inside nonprofits: leadership alignment, staff readiness, fear and resistance, governance, and ethical use. Participants will learn practical strategies for leading AI transformation in mission-driven organizations—grounded in transparency, inclusion, and long-term capacity building.

Most AI adoption starts with tools: pick a platform, deploy a model, hope impact follows. The result is usually incremental efficiency—not meaningful change. This session makes a different case: transformation begins with use cases, not technology. Instead of asking “Where can we apply AI?”, organizations should ask “What decisions or outcomes must improve—and what work needs to change to get there?" Panelists will share how leading organizations redesign workflows, governance, and incentives alongside AI—so gains translate into real mission impact, not just faster versions of the same work.

While AI is already helping to advance impact it is also starting to reshape labor markets, energy systems, information integrity, and public trust. Both are happening at a speed often faster than institutions can respond. This session provides a grounded, practitioner-oriented examination of AI’s second-order effects and seeks to be an on-ramp for how practitioner experience can inform smarter AI policy development. We want more AI policy conversations to have more meaningful input from practitioners who actually deploy technology in communities.

Digital Public Infrastructure (DPI) is recognized as a critical foundation for delivering inclusive, scalable public services. Drawing on DataKind’s experience building and stewarding digital public goods, this session shares lessons from efforts to address one of DPI’s most persistent challenges: fragmented and closed data standards. As AI-enabled systems are introduced into public services, the absence of shared, interoperable standards—particularly those that support continuity of personal context—has emerged as a barrier to effectiveness, safety, and equity. Without common standards, systems remain siloed, vendor lock-in persists, and communities are excluded from shaping the infrastructure that serves them. "Good Tech" cannot meaningfully exist without technology underpinnings that center and serve the communities the technology purportedly exists for.

This session will explore how data standardization can function as a public good when paired with intentional codesign. Participants will examine why shared, open standards are a foundational layer of DPI, how persistent, user-controlled context
improves AI-supported services, and why community participation is essential to ensuring standards are trusted. During the session, we will share cross-sector, globally-representative examples and learnings from DataKind’s work in education, healthcare, and humanitarian response, and will highlight how participatory, open source codesign strengthens the adoption and long-term impact of these "good" technologies.

Participants will leave with an understanding of how shared data standards enable interoperability, reduce duplication, and unlock innovation across public-interest sectors. Discussion will foreground funding and long-term stewardship as critical objectives for DPI and conclude with a call to action to collaborate on shaping, adopting, and sustaining emerging data standards as digital public infrastructure.

Host: Beeck Center for Social Impact + Innovation, Georgetown University

Across government and civil society, the question isn’t whether to adopt data and AI — it’s how to use them to deliver better services, strengthen trust, and improve outcomes for the people who rely on public systems every day.

This workshop spotlights practical civic tech applications already making a difference — from benefits delivery and digital identity to procurement, case management, and frontline service design. Grounded in implementation, not theory, the session explores what it takes to deploy responsible AI inside real institutions with legacy systems, policy constraints, and limited capacity.

AI has the potential to help transform impact measurement — moving beyond static reports to dynamic, decision-grade intelligence -- and with it how the sector is organized. This session explores how AI is starting to support outcome measurement, learning loops, and aligning various actors in the impact ecosystem in new ways around systems that funders and practitioners can actually trust.