Webinar Description
Key Takeaways
- Focuses on securing AI agent workflows across gateways, tools, and operational paths
- Addresses governance challenges specific to autonomous AI systems in enterprise environments
- Covers Model Context Protocol (MCP) usage controls and tool access management
- Designed for CISOs and security leaders responsible for AI adoption strategies
- Explores audit-ready evidence capture for AI agent actions
Securing AI Agents Without Compromising Innovation
As organisations accelerate their adoption of AI agents, security teams face a fundamental challenge: these autonomous systems operate across gateways, tools, and execution paths that traditional security controls were never designed to monitor. This webinar brings together security practitioners and product leaders to examine practical approaches for governing AI agent workflows while maintaining the pace of innovation that business units demand.
The session features Lee L’Archevesque, CISO of Digital Currency Group, alongside Moinul Khan, CEO and Co-Founder, and Vairavan Subramanian, VP of Product Management. Their combined perspectives from financial services security leadership and product development offer attendees insight into both the strategic and operational dimensions of AI agent governance.
The Visibility Gap in Agent Security
AI agents differ fundamentally from conventional software in how they interact with enterprise systems. Rather than following predetermined execution paths, agents make autonomous decisions about which tools to invoke, which data sources to query, and how to chain multiple actions together to accomplish objectives. This autonomy creates security blind spots that network-level monitoring and traditional access controls cannot adequately address.
The webinar examines how security teams can extend governance across the full agent workflow rather than focusing solely on network traffic or endpoint behaviour. This includes controlling how agents access external tools and managing their use of the Model Context Protocol, an emerging standard that enables AI systems to interact with external data sources and services in a structured manner.
Audit Requirements and Operational Risk
Regulatory expectations around AI systems continue to evolve, and organisations deploying agents must demonstrate accountability for the actions these systems take. The discussion addresses how security teams can capture audit-ready evidence for every agent action, creating the documentation trail that compliance and legal functions increasingly require.
Balancing risk reduction with operational enablement remains central to the conversation. Security programmes that impose excessive friction on AI adoption risk pushing usage into shadow IT channels, where visibility and control disappear entirely. The speakers explore frameworks that allow organisations to enable AI adoption while maintaining appropriate risk boundaries.
Who Should Attend
This session is structured for CISOs and security leaders who have moved beyond initial awareness of AI risks and are now focused on building executable governance strategies. Attendees should expect a practical discussion oriented toward implementation rather than conceptual overview, with emphasis on creating durable security frameworks that can adapt as AI agent capabilities continue to expand across enterprise environments.