Shingai Manjengwa Speaking Topics

• AI for All: What Every Leader Needs to Know

  AI is moving from an emerging technology to core organizational infrastructure. The question for leaders is no longer whether AI will affect their organization, but how to adopt it well.

  In this practical and engaging keynote, Shingai Manjengwa demystifies today's AI landscape and gives leaders a clear framework for making better decisions about adoption, investment, talent, and risk. Drawing on her work with executives, policymakers, and organizations around the world, including board-level engagements with sovereign investment funds and national governments, she separates hype from genuine opportunity and shows where AI can create measurable value.

  Audiences leave with a clearer understanding of what AI can and cannot do, where to start, and the leadership decisions required to move from experimentation to meaningful adoption.

  Attendee Results: Artificial Intelligence, Strategy, and Leadership

  • Understand the current AI landscape without the hype or the fear
  • Learn a practical framework for evaluating adoption, investment, and risk decisions
  • See real examples of organizations moving from pilot to meaningful adoption
  • Leave with a clear sense of where to start

• Operationalizing Responsible AI: From Principles to Practice

  Responsible AI cannot live only in principles, policies, and boardroom checklists. Once AI becomes part of an organization's operating infrastructure, governance must become operational.

  In this keynote, Shingai Manjengwa reframes responsible AI as a people, operations, and safety problem. Drawing lessons from safety-critical industries such as aviation and healthcare, alongside real enterprise cases including a well-documented breach that exposed 500,000 monthly user queries in under two hours, she explores how organizations can build practical systems for testing, monitoring, accountability, incident response, and human oversight.

  Audiences leave with a practical understanding of how to move responsible AI from abstract values into everyday operations, and how leaders can create the culture, processes, and accountability required to deploy AI safely at scale.

  Attendee Results: Responsible AI, Governance, Operations, and Risk

  • Understand why responsible AI requires operational systems, not just policy documents
  • Learn from safety-critical industries how incidents get investigated and shared
  • See a real case study of enterprise AI governance failure and recovery
  • Take away a concrete starting point for building AI incident response

• The AI Advantage: Redesigning Work for an AI-Enabled Organization

  The biggest productivity gains from AI will not come from giving everyone a chatbot. They will come from redesigning how work gets done.

  Shingai Manjengwa explores how AI is changing workflows, job design, skills, and organizational structure, from individual productivity to AI agents capable of taking action across software systems. She shows leaders how to identify high-value use cases, distinguish automation from augmentation, and avoid simply adding AI to inefficient processes.

  This keynote gives audiences a practical way to think about AI transformation: process first, technology second. Participants leave better equipped to identify where AI can save time, improve decisions, and create new capabilities, while understanding what remains fundamentally human.

  Attendee Results: AI Productivity, Future of Work, and Organizational Transformation

  • Learn to distinguish genuine automation opportunities from cosmetic AI addition
  • Understand the difference between individual productivity gains and structural transformation
  • See how to evaluate a workflow before deciding whether AI belongs in it
  • Leave with a process first, technology second approach to transformation

• Learning in the Age of AI: What Should Humans Know?

  When AI can write, calculate, code, summarize, and explain, what does it mean to be educated?

  Drawing on her work designing AI education for learners ranging from students to executives and policymakers, including programs that have reached over 500,000 learners worldwide, Shingai Manjengwa examines how artificial intelligence is changing teaching, learning, and the skills people need to thrive.

  This keynote goes beyond the debate over whether using AI is cheating to address deeper questions. What knowledge should remain foundational? How do we preserve critical thinking? What does AI literacy actually require? And how should schools, universities, and workplaces prepare people for a world in which intelligent systems are everywhere?

  Audiences leave with a practical framework for developing human capability alongside AI rather than outsourcing it.

  Attendee Results: AI, Education, and the Future of Learning

  • Move past the cheating debate to the deeper questions AI raises for education
  • Understand what AI literacy actually requires at different ages and levels
  • Learn a framework for building human capability alongside AI, not instead of it
  • Gain language to bring back to a school, university, or workplace setting

• A Nudge or a Kick: Moving Toward AI Safety

  AI systems are becoming more capable, autonomous, and deeply embedded in society. The challenge is no longer simply encouraging responsible behaviour. Leaders must decide where education is sufficient, where safeguards are necessary, and where accountability must have real consequences.

  In this provocative keynote, Shingai Manjengwa examines AI safety through five questions: education, selection, responsible use, testing and verification, and action and consequence. She connects technical risk with governance, institutional capacity, and AI sovereignty, showing why organizations and governments need both informed users and robust systems.

  Audiences leave with a clearer understanding of where responsibility lies as AI becomes more powerful, and what practical action leaders can take now.

  Attendee Results: AI Safety, Sovereignty, and Responsible AI Policy

  • Learn a five question framework for AI safety usable at any level of an organization
  • Understand the connection between AI sovereignty and institutional capacity
  • See how to decide where education ends and accountability must begin
  • Leave with practical next steps rather than abstract principles

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