Women in AI by FemTechConf
AI Governance Conference: Responsible AI, Regulation and Enterprise Risk
AI governance has moved from a specialist policy topic to an operating requirement for organisations deploying artificial intelligence. The challenge is no longer only writing principles. Companies need ownership, documentation, evaluation, human oversight, security controls and clear decisions about which systems can be deployed under which conditions.
7,500 expected in person · 75,000 virtual · 50+ speakers · 11–12 November 2027, London
Why AI governance belongs in the main AI conversation
Governance is often treated as a constraint applied after a technical system has been built. In practice, good governance changes architecture, data decisions, evaluation, procurement, monitoring and accountability from the beginning. That makes it relevant to engineers and product teams as much as legal or compliance functions.
The strongest organisations are therefore building cross-functional governance models. Technical teams need to explain what a system can and cannot do. Business owners need to define acceptable outcomes. Risk teams need evidence. Leaders need escalation routes. Boards need enough literacy to ask the right questions without pretending to run model evaluations themselves.
Governance topics at Women in AI Global Summit
The 2027 Summit is developing governance as a core programme theme rather than a side discussion. Coverage connects policy with enterprise implementation and technical practice.
- Responsible AI frameworks and operating models
- EU AI Act implementation
- AI sovereignty and national capability
- Human oversight and accountability
- Model evaluation and monitoring
- Enterprise AI risk management
- Transparency and documentation
- Public-sector AI and public value
- Board and executive oversight
Learn from people working across policy and implementation
The announced speaker group already includes leaders whose work touches AI governance, technology transformation and public value. Andrea Marshall Webb of Credera works at the intersection of AI, leadership, sovereign AI and governance. Dia Nag brings senior UK public-sector transformation experience from Capgemini Invent. Senior leaders from KPMG, Hitachi and other organisations add enterprise perspectives on adoption and transformation.
That mixture is important. AI governance becomes useful when policy, engineering and operating reality meet in the same discussion.
Build governance capability before regulation forces the issue
Organisations that wait for a compliance deadline often discover that the evidence they need was never collected. Governance maturity is easier to build while AI systems are still being designed and procurement processes can still be changed.
Our Responsible AI editorial hub covers frameworks, the EU AI Act, ISO 42001, NIST AI RMF, model risk, human oversight and documentation in depth. The Summit provides the live counterpart: the chance to hear how leaders are applying these ideas and discuss the trade-offs with peers.
Related resources
Frequently asked questions
Does Women in AI Global Summit cover AI governance?
Yes. AI governance, responsible AI, sovereignty, regulation, enterprise risk and public-sector adoption are core areas of the Summit programme and year-round editorial coverage.
Is the governance content only for lawyers and compliance teams?
No. Effective AI governance also involves engineering, product, data, security, procurement, executive leadership and boards.
Can companies sponsor governance content or experiences?
Yes. Companies interested in thought leadership, responsible AI positioning, executive engagement or enterprise visibility can discuss partnership opportunities with the Women in AI team.