On open and candid discussion with respected NGO leaders on the realities of AI in their organizations today. We look forward to a free-ranging discussion
The session promises to be rich with real-world learnings and insights, and we’ll reserve time for questions and discussion.
The development sector is facing unprecedented pressures to demonstrate impact, strengthen resilience, and do more with fewer resources. Mergers and strategic combinations, once seen as last-resort measures, are increasingly powerful tools for mission advancement and business model transformation.
This conversation brings leaders together to explore when and how mergers, alliances, and shared services can accelerate impact, reduce risk, and position organizations for long-term success. Through practical insights and real-world examples, participants will gain clarity on the opportunities, challenges, and requirements to pursue strategic combinations thoughtfully and effectively.
Paul is a leading expert in AI and digital transformation for the global development sector. He has held senior roles at Save the Children US and advises INGOs worldwide on AI strategy, governance, and ethical adoption. He holds the Artificial Intelligence Governance Professional (AIGP) certification and is known for his ability to make complex AI issues clear and actionable for leadership teams. Paul’s approach is practical, intuitive, and steeped in real-world experience, making him a trusted partner to executives navigating digital change.
In 2026, leading nonprofits are shifting from AI experiments to AI fully integrated into strategic planning. This will widen the divide between AI-enabled organizations and those standing still. Leaders who don’t set an AI plan now risk falling behind on efficiency, fundraising, and impact.
AI Readiness Checklist
A simple framework for helping you understand the key elements needed for AI success in your organization.
A 2026 AI Roadmap Outline
An approach to identify opportunities for using AI, set priorities and align your team.
A Risk-Reduction Framework
Practical ways to identify and manage AI risks so you can move forward confidently.
