Why AI governance is the foundation of secure MCP adoption
July 28 @ 6:00 am – 7:00 am EDT
Description:
MCP (model context protocol) is rapidly emerging as the standard for connecting AI systems with enterprise data and business processes. However, many organisations focus on technology before addressing a more fundamental challenge: governance readiness.
Successful MCP adoption depends on more than secure architecture and technical controls. It requires clear ownership, cross-functional accountability, trusted data sources, auditability, and governance structures capable of supporting AI-enabled decision-making across the enterprise.
This session explores how organisations can move from fragmented governance ecosystems (where risk, compliance, audit, legal, quality, and security operate in silos) toward a shared organisational context that enables responsible and scalable AI adoption.
Drawing on practical governance experience and research into governance under uncertainty, the session highlights common governance pitfalls that can undermine AI initiatives, including accountability gaps, siloed decision-making, and symbolic governance practices.
Attendees will leave with a practical framework for assessing governance readiness, aligning key stakeholders, and establishing the governance foundations that transform MCP from a technical implementation into a strategic business capability.
Learning objectives:
- Assess your organisation’s MCP-readiness across ownership, accountability, auditability, and policy frameworks.
- Identify governance fragmentation risks that can undermine AI-enabled decision-making and MCP initiatives.
- Build a practical roadmap for creating shared organisational context and cross-functional governance alignment.
CPE credit(s): 1 CPE upon live viewing and participation. CPEs not offered on-demand.
Field of study: Management Services
Instructional delivery method: Group Internet Based
Level: Basic
Prerequisite: None
Advanced preparation: None
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