Get to know the audience and participate in interactive benchmarking polls to kick the day off.

As the next wave of AI innovation moves beyond individual models to coordinated ecosystems of intelligent agents, multi-agent systems (MAS) are emerging as a strategic frontier. Understanding the opportunities, risks, and architectural implications of MAS is becoming increasingly critical. 

This executive-level panel brings together leaders and experts to discuss learnings from deploying AI agents across industries and unpack what organizations need to consider before leveling up to multi-agent systems. 

• Assessing learnings from deploying individual AI agents 
• Highlighting core principles and use cases of multi-agent systems 
• Choosing the right development frameworks and simulation environments 
• Understanding governance, control, and risk management in distributed AI systems 
• Determining organizational readiness: skills, infrastructure, and data strategy considerations 
• Communication, coordination, and conflict resolution strategies among agents 
• Key design trade-offs: centralized vs. decentralized control 
• Practical lessons from real-world implementations 

Katya Hall

Segment CIO
McKesson

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Hani Batla

CIO/CTO
Adorama 

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Making an organization work with agentic AI is not a simple task. It requires a change in technology, skills, workflows, getting on the same page with other tech leaders, and in-depth collaboration with your business owners. An AI-first architecture and mindset are the basis for delivering business impact at scale. Listen in as the Chief Data and Analytics Officer from Analog Devices dives into a recent infrastructure project to assess the blueprint of what AI-first architecture and mindset looks like and highlights agentic AI use cases that illustrate the real status quo of agentic AI vs the hype. 

• What agentic AI is—and isn’t: Clarifying the hype vs. practical capabilities 
• Assessing the blueprint for AI-first architecture in a recent infrastructure project 
• Positioning the human in the middle 
• Understanding the importance of a mindset shift beyond the technology 
• Highlighting successful agentic AI use cases that delivered business impact at scale 
• Lessons learned and practical considerations for your roadmap 

Ash Dhupar

Chief Data & Analytics Officer
Analog Devices

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In this fireside chat, we explore how agentic AI is being used today to unlock new levels of insight generation, customer satisfaction, productivity, and operational efficiency. Benchmark your AI roadmap against cutting-edge deployments—and understand where agentic AI is delivering meaningful, measurable value today. 

• Defining what business value means 
• Real-world examples across industries: from autonomous customer service agents to dynamic R&D copilots 
• How multi-agent coordination is enabling more adaptive and context-aware systems 
• What it takes to move from experimentation to production—including data, architecture, and change management 
• Best practices for optimizing inferences 
• Lessons learned from early adopters: ROI, risks, and what to watch out for 

This session provides a practical roadmap for organizations to navigate the integration of artificial intelligence into their core operations. Join us for a conversation that transcends the typical AI hype to deliver genuine insights into human- machine collaboration. Learn about the concept of Augmented General Intelligence (AuGI) which emphasizes technology that amplifies human capabilities rather than competing with them. This session is particularly valuable for leaders grappling with the real challenges of AI implementation - from prompt engineering and bias mitigation to the evolving nature of teamwork itself.  

• How to work with AI and human augmentation in the new workplace 
• Assessing scenarios of collaboration between humans and AI and the implications for leadership 
• Moving beyond AI as a mere tool to AI as a true teammate to unlock unprecedented innovation and productivity 
• Critical human skills in an AI world 
• Effective strategies to manage fear and uncertainty 

Ken Hubbell

AI Technology Expert, CEO/Co-Founder
The Pragmatic Futurist

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As AI systems evolve from passive tools to active, decision-making agents, traditional governance models are no longer sufficient. Agentic AI introduces new complexities—autonomy, emergent behavior, delegation of intent—that challenge how organizations manage risk, accountability, and control. 

In this fireside chat, we'll explore the frontiers of governing agentic systems. 

• What makes governance of agentic AI fundamentally different? 
• The importance of high-quality data 
• Assessing key risks and failure modes 
• Understanding emerging frameworks for oversight, guardrails, and real-time monitoring 
• Balancing innovation with control in distributed, goal-seeking systems 
• Exploring the evolving role of CIOs, CDOs, Chief AI Officers, and boards in stewarding agentic intelligence responsibly 

As organizations race to integrate language models into products and workflows, a critical question remains: Should you build a large, general-purpose model—or a smaller, domain-specific one? Each approach brings distinct strengths—and significant trade-offs. 

This session compares the performance, cost, governance, and usability of Large Language Models (LLMs) and Small Language Models (SLMs) in an enterprise deployment scenario and assesses the importance of context for different use cases. Gain practical insights into selecting the right model size and architecture based on your organization's goals, constraints, and regulatory context. 

• When does size matter—and when does it not? 
• Assessing contextual understanding and domain fit: How LLMs generalize vs. how SLMs specialize 
• Understanding latency, cost, and infrastructure requirements 
• Evaluating governance and risk trade-offs: Controllability, explainability, and hallucination risks 
• Highlighting data privacy, fine-tuning, and lifecycle considerations 

While agentic AI is transforming industries, its potential for social impact is only beginning to be realized. In this case study session, we spotlight how nonprofits are harnessing autonomous agents to amplify their missions — from optimizing resource allocation to automating outreach, improving accessibility, and scaling operations with limited budgets. 

Hear from the founder and president of "Code for Good" how the nonprofit world can benefit from the agentic AI revolution and amplify the work for good. We’ll explore how nonprofit organization "Code for Good" successfully implemented agentic AI to overcome capacity constraints and drive measurable impact in the communities they serve. The session will highlight key design choices, lessons learned, and the unique challenges of applying AI in mission-driven contexts where trust, transparency, and accountability are paramount. 

Attendees will leave with practical insights into how nonprofits can responsibly integrate agentic systems to do more good, with less overhead. 

• Low-cost, high-impact AI use cases for nonprofits 
• Leveraging no-code and low-code 
• Designing agent workflows for mission alignment 
• Building trust with stakeholders and communities 
• Ethical considerations and data stewardship 
• Partnering with technologists and funders for sustainable AI adoption 

Saritha Ivaturi

Founder/President
Code For Good  

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Join an interactive boardroom* on a preselected topic and discuss with a small group of your peers your biggest initiatives, challenges, and most effective strategies and tools.  

1.ROUNDTABLE: Tackling Common Challenges When Starting Out With Agentic AI 

Shakeel, Hye, Director of Data Engineering, TracFone Wireless 

Gartner predicts that 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls. How do you ensure it’s not yours? Join this roundtable to discuss with your peers how to find the right use case that will give you the head start to show value. Learn how others navigate challenges with data quality, governance, ethics, skillsets and resources, and discuss how to account for computing and storage cost from day one and know when to cap. Walk away with best practices for change management, to help get buy-in, navigate fear, and drive a mindset shift towards openness and experimentation. 

2.ROUNDTABLE: Using Agentic AI to Advance and Accelerate Innovation 

Dr. Melvin, Greer, Intel Fellow and Chief Data Scientist, Intel Corporation 

Agentic AI is not just a tool for efficiency — it's a catalyst for reimagining what’s possible. This roundtable invites participants to explore how autonomous agents are helping organizations push boundaries, unlock new capabilities, and accelerate innovation across industries. In this highly interactive session, we’ll assess the bold, experimental, and transformative use cases attendees are developing — from automating complex workflows to enabling new forms of creativity, decision-making, and problem-solving. Together, we’ll explore how agentic AI is reshaping the innovation process itself, turning moonshots into roadmaps. Whether you're testing the edges of what AI can do or just beginning to think beyond incremental gains, this conversation is designed to spark new ideas, surface shared challenges, and connect innovators who are rethinking the future with agents at the center. 

Other topics may include 

3.ROUNDTABLE: How to Safely Use AI: Protecting Consumer and Company Data in an Agentic Era 

As AI systems become more embedded in day-to-day operations, ensuring their safe and responsible use is no longer optional — it’s essential. This roundtable explores practical strategies and guardrails for using AI securely, with a focus on protecting both consumer data and your own proprietary information in an era of increasingly autonomous agents. 

Join us for a candid discussion on how to evaluate risks, set boundaries, and maintain trust while leveraging agentic AI. We’ll cover real-world cases, common pitfalls, and emerging best practices that can help your organization use AI with confidence and care.  

4.ROUNDTABLE: Understanding the Need For Manual Interventions: The A to Z of Training and Retraining Agents 

As autonomous agents become increasingly capable, the myth of “set it and forget it” continues to be challenged by the practical realities of training and retraining these systems. Building AI agents is only half the battle. This roundtable dives deep into the lifecycle of agentic AI, focusing on the critical — and often underestimated — role of human oversight and manual intervention. From the early stages of dataset curation and objective definition, to mid-lifecycle adjustments and post-deployment retraining, we will explore how, when, and why humans must step in. We’ll discuss real-world examples where intervention saved agents from drift or misalignment, and unpack best practices for building feedback loops that combine scalability with accountability. Join the discussion to move from taking risks to taking calculated risks. 

5.ROUNDTABLE: Do’s and Dont’s For Using Open Source 

Open source has become a cornerstone of rapid innovation in agentic AI — enabling faster development, broader collaboration, and more accessible experimentation. But with this power comes a complex set of responsibilities and risks. This roundtable will unpack the critical do’s and don’ts of leveraging open-source tools, models, and datasets when building autonomous agents. Join a candid conversation with AI practitioners as we explore how to evaluate open-source licenses, ensure responsible integration, avoid hidden liabilities, and contribute back ethically. We’ll cover real-world lessons from teams that have built on open-source foundations — and the mistakes they learned the hard way. This session will help you navigate the open-source landscape confidently and responsibly. 

6.ROUNDTABLE: Agentic AI’s Impact on Jobs from Job Cutting to Job Augmentation 

As agentic AI reshapes the workplace, one question looms large: What happens to the jobs? While headlines often focus on job cuts, the deeper story is more complex — and more important. This roundtable focuses on the evolving relationship between agentic AI and employment. We'll explore how jobs are changing not only due to automation, but also because the cost of effectively utilizing AI is rising — creating a shift in which roles are needed, what skills are in demand, and how teams must be trained to adopt AI agents and agentic AI. Some roles are being phased out, others are being transformed, and entirely new categories of work are emerging around AI oversight, orchestration, and human-agent collaboration. 

Join us for a forward-looking conversation on what’s going away, what’s coming up, and how organizations can prepare their people to not just survive — but thrive — in the age of agentic AI. 

*practitioners only

Dr. Melvin Greer

Chief Data Scientist and Intel Fellow
Intel Corporation  

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Shakeel Hye

Director of Data Engineering
TracFone Wireless

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Saritha Ivaturi

Founder/President
Code For Good  

See Bio