Who’s in Control? Scaling AI Agents Without Losing Accountability

Organizations are rapidly introducing AI agents across their application landscape, but with that acceleration comes a new wave of complexity. Shadow AI is emerging at scale, agents and data are becoming increasingly siloed, and teams are struggling to keep pace with evolving protocols and architectures. At the same time, many organizations remain stuck in pilot mode, unable to scale AI into production, while deeper questions around accountability, governance, and ownership remain unresolved as agents begin making more autonomous decisions.
Leading organizations are reframing this challenge by focusing on building an “AI-ready” enterprise from the ground up. This means transforming rigid systems into interoperable, API-driven environments that agents can seamlessly access and act upon, while implementing governance frameworks that define accountability, manage risk, and address ethical considerations. It also requires breaking down silos across data and agents, operationalizing AI across core initiatives like cloud and ERP transformation and rethinking how humans and agents work together to drive outcomes at scale.
Join Salesforce MuleSoft and a select group of your peers to explore what it takes to move from experimentation to an agentic enterprise. Together, we’ll uncover how to get ahead of shadow AI, establish clear governance and accountability models, and redesign your organization for a future where humans and AI agents operate in tandem to deliver measurable business impact.