Tuesday, June 9, 2026: Main Day One

Agentic AI isn’t just transforming workflows, it’s reshaping how enterprises create value, compete, and organize for the future. As digital and human workers converge, leaders must rethink operating models, talent strategies, and business design to stay ahead of shifting market dynamics. Join executives to anticipate what’s next, align leadership around a shared vision, and build the foundations for a resilient, AI-ready enterprise.

• Brainstorm how to prepare your enterprise for evolving operating models and resourcing shifts
• Anticipate shifts in competitive positioning driven by agentic AI
• Align business, talent, and innovation strategies to capture new growth opportunities
• Balance governance, agility, and experimentation to navigate disruption
• Building leadership alignment and cultural readiness for an AI-powered organization 

Learn how to strategically prioritize Agentic AI initiatives that align with your enterprise growth goals and measure them appropriately. Dive into methods for measuring meaningful ROI to ensure your AI investments deliver lasting business impact.

Join this session to consider:

• Frameworks to prioritize AI projects aligned with strategic objectives
• Metrics that capture real value: cost reduction, compliance, CX, and user adoption
• Tools and techniques to quantify ROI and track success over time
• Data-driven decision-making approaches for sustainable AI investment
• Common pitfalls in ROI measurement and how to avoid them 

True success with agentic AI demands seamless collaboration across diverse enterprise functions. Explore how organizations are breaking down traditional silos between Finance, IT, Operations, HR, and more to create integrated AI ecosystems that drive transformative business outcomes.

Discover how to build strategic partnerships across functions by embedding AI teams as trusted collaborators to offer tailored points of view, co-creating use cases, and aligning AI initiatives with each function’s unique goals.

• How to foster strategic partnerships with business functions for AI adoption success
• Frameworks to identify overlapping AI opportunities and unlock synergy across departments
• Best practices for embedding AI expertise within functional teams as proactive partners
• Real-world examples of integrated AI workflows delivering measurable business impact
• Strategies to overcome cultural and organizational barriers to cross-functional collaboration 

Enterprises are eager to adopt agentic AI but many run into the same challenges: unclear frameworks, messy integrations, misconceptions about system capabilities, and confusion around design choices. This session will share real lessons learned to help you avoid common pitfalls and build agentic systems that actually perform at scale. We’ll break down the essential decisions, single vs. multi-agent design, choosing the right framework, whether to use MCP, and how to integrate agents into existing workflows. You’ll walk away with a clear understanding of the challenges, the tradeoffs, and the practical steps required to build reliable agentic AI in the enterprise.

• The top misconceptions that derail agentic AI projects and how to avoid them
• Guidance on selecting design patterns and frameworks (single agent, multi-agent, MCP, and more)
• How to integrate agents into existing workflows without adding complexity
• Field-tested strategies to overcome data, governance, and operational barrier
• A concise blueprint for building scalable, effective agentic AI systems 

Naresh Dulam

VP, Software Engineering
JP Morgan Chase & Co.

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Enterprises are eager to adopt agentic AI but many run into the same challenges: unclear frameworks, messy integrations, misconceptions about system capabilities, and confusion around design choices. This session will share real lessons learned to help you avoid common pitfalls and build agentic systems that actually perform at scale. We’ll break down the essential decisions, single vs. multi-agent design, choosing the right framework, whether to use MCP, and how to integrate agents into existing workflows. You’ll walk away with a clear understanding of the challenges, the tradeoffs, and the practical steps required to build reliable agentic AI in the enterprise.

• The top misconceptions that derail agentic AI projects and how to avoid them
• Guidance on selecting design patterns and frameworks (single agent, multi-agent, MCP, and more)
• How to integrate agents into existing workflows without adding complexity
• Field-tested strategies to overcome data, governance, and operational barrier
• A concise blueprint for building scalable, effective agentic AI systems 

Effective management of AI agents throughout their lifecycle is key to sustained performance and business value. This session offers a practical playbook for deploying, monitoring, retraining, and retiring agents. Learn how to set quality gates, detect data drift, and manage smooth handoffs between agents and humans.

• Best practices for deployment and risk management
• Continuous monitoring and performance tracking
• Detecting and addressing data drift with retraining
• Defining quality gates and human-agent handoffs
• Planning for agent retirement without disruption
• Aligning lifecycle management with compliance and governance 

Mayur Khare

Senior Director, AI and Data
Beazer Homes USA

See Bio