About the summit
Now in its third year, the AI + Data Security World Summit is America’s only event built specifically around AI security, data security and data protection, with events in New York and San Francisco. AI has collapsed the wall between data protection and security. Every AI deployment is a data governance decision, every model creates a new attack surface, and the teams responsible for protecting enterprise data are now being handed AI security as well. In 2027, the summit expands into two streams. One covers AI security, including models, agents, AI pipelines and the data feeding them. The other covers data security and protection, including governance, privacy, data loss and resilience. Until this summit, AI security, data security and privacy sat as streams inside broader cybersecurity conferences, never the room itself. The AI + Data Security World Summit is that room. Across New York and San Francisco, CISOs, Chief Privacy Officers, Heads of Data Security, AI governance leaders and the teams responsible for protecting enterprise data come together to compare programs directly with their peers. Make sure you are part of the discussion at America’s only event built specifically around AI security, data security and data protection.
Who attends
- CISO
- Chief Privacy Officer
- Head of Data Protection
- Head of AI Governance
- Head of Security
- Data Protection Officer
What the programme covers
- AI Application and Agent SecuritySecuring models, copilots, RAG applications and autonomous agents from development through to production.
- Shadow AI and AI Asset DiscoveryFinding the models, agents and AI tools already in use and bringing unapproved adoption under control.
- AI Data SecurityStopping sensitive data flowing into prompts, models, vector databases and third-party AI services.
- AI Governance, Testing and AssuranceModel inventories, approval gates, security testing and the evidence required by regulators and boards.
- Data Discovery and DSPMFinding, classifying and reducing the exposure of sensitive data across cloud, SaaS, AI and legacy systems.
- Data Access and Privacy GovernanceControlling who can access sensitive data, how it can be used and whether it meets privacy and regulatory obligations.
- Data Loss Prevention and Insider RiskControlling data movement and risky user behaviour without blocking the business.
- Ransomware and Data ResilienceProtecting critical data, recovering quickly and proving resilience across regulated environments.