AI in Testing Is Not a Tool Strategy: A Leadership Workshop to Build Vision, Governance, and Measurable Impact

AI is no longer a side experiment in testing; it is a leadership mandate. Yet many organizations remain stuck in tool demos, disconnected pilots, unclear ROI, and "automation theater." Quality and engineering leaders are being asked to “bring AI into testing,” but few have a practical blueprint for turning that ask into a scalable business strategy. In this high-impact session, we move beyond the AI buzzwords to deliver a strategic playbook for championing an AI testing strategy. Leaders will learn how to transition from reactive tools-first adoption to a 360-degree vision that connects business outcomes, quality risk, engineering productivity, and customer trust. We will explore real-world pitfalls—such as unmanaged AI risk, lack of human oversight, and KPI vanity metrics—and introduce a practical AI Testing Leadership Canvas that you can take back to your organization to instantly align your teams, design your roadmap, and secure executive buy-in.

During this workshop, attendees will learn how to:
• Benchmark Maturity: Quickly assess your organization's AI testing readiness across tools, processes, and people.
• Avoid "Automation Theater": Identify common AI testing anti-patterns and unmanaged risks before they impact delivery.
• Define the Framework: Learn the core pillars of an AI operating model, including human-in-the-loop governance and decision rights.
• Measure Real ROI: Shift from vanity metrics (like "number of AI test cases") to KPIs that tie directly to business value.