Stream: Magny-Cours
Time: 11:15 - 12:00
As AI evolves from providing insights to agents that can take action, trust becomes critical. This session explores how mainframe organizations can establish governance and guardrails for AI agents without limiting their value. Learn how access controls, monitoring, evaluation, explainability, auditability, and human oversight can help organizations determine what agents can access, what actions they can take, and when people should remain involved in decisions across critical mainframe workflows. What You’ll Learn • What governance and guardrails are needed as AI agents move from recommendations to action. • How monitoring, evaluation, access controls, and auditability help establish trust in agent-driven workflows. • How to balance agent authority with risk, accountability, and human oversight in critical mainframe environments.
There is currently no attachment for Building Trust in AI: Governance, Guardrails, and Responsible Adoption for the Mainframe
Anthony DiStauro is a Distinguished Engineer and Chief AI Architect for BMC’s AMI portfolio, where he leads the technical vision, architecture, and strategic direction for the next generation of AI-powered mainframe solutions. Working across product, engineering, and executive leadership, he helps translate emerging AI technologies into scalable enterprise capabilities and differentiated solutions. A multi-patent recipient, Anthony is recognized for developing forward-looking technologies and for his ability to connect deep technical expertise with long-term business strategy. His work spans enterprise AI, agentic systems, platform architecture, and mainframe modernization, with a continued focus on responsible innovation, architectural excellence, and real-world adoption. Beyond his technical leadership, Anthony is a prominent advocate for enterprise AI and a trusted voice with customers, analysts, and industry leaders. Through webinars, podcasts, analyst briefings, executive discussions, and global customer engagements, he shares practical insights on AI adoption, the evolution of autonomous and agentic systems, and the expanding role of the mainframe in the AI-driven enterprise.
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