Date & Time: Tuesday, July 28, 2026 | 11:00 AM British Summer Time
Duration: 1 hour | 1 CPE | Webinar in english
Model Context Protocol (MCP) 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 webinar explores how organisations can move from fragmented governance ecosystems - where risk, compliance, internal audit, legal, quality, and security operate in silos-towards 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.
Participants 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.
By attending this webinar, participants will learn how to:
Head of Group Management Systems, LAB14 GmbH
Salla Lutz is a governance professional specialising in governance, risk, compliance, quality management, and organisational transformation within a multinational high-tech environment. Her work focuses on integrating governance structures, management systems, and decision-making processes across complex organisations.
She holds a PhD in Business Transformation under Uncertainty and is currently pursuing a Master's degree in Risk & Compliance Management. Her research explores governance competence, responsible leadership, and the organisational factors that enable or hinder-effective governance in increasingly complex and digital environments.
Combining academic research with extensive practical experience in governance integration, internal auditing, risk management, management systems, and organisational change, Salla provides practical insights into the governance challenges organisations face when implementing AI-enabled governance structures.
Her particular interest lies in helping organisations move beyond fragmented governance models towards a shared organisational context, where technology enhances transparency, accountability, and informed decision-making while preserving human judgement and leadership responsibility.
