15th October | 12pm ET
The Agentic Advantage:
How Enterprises Innovate Without Losing Control
Enterprises are facing a flood of AI Agent and Agentic AI use cases from business users and technology leaders.
But most organizations lack the capabilities to safely and effectively put them into production.
Agents can access proprietary data, act independently, and rapidly incur costs. Without clear visibility, risk assessments, or cost controls in place, Agentic AI doesn’t accelerate innovation—it amplifies exposure.
The risks are real and urgent: data leakage, uncontrolled access across your digital supply chain and vendor SaaS tools, and decision-making without oversight. AI leaders are under pressure to accelerate innovation, but without clear guidelines, visibility, and cost controls, these initiatives can spiral into security, financial, and regulatory liabilities.
Agentic AI is unlike anything your organization has introduced or scaled before, so preparing for it requires a fundamental shift: new architecture, new control models, and a new operating culture. Join us to learn how to stay in control—before these systems reach production.
In this digital summit, we’ll explore:
What CIOs, CDAOs, CAIOs, and Responsible AI leaders must do today to enable Agentic AI while mitigating its risks.
The emerging AI Control Tower model and how it enables visibility, control, and assurance across distributed AI systems.
New protocols like the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communications are shaping secure Agentic architectures.
This digital summit will identify Agentic AI lifecycle management and governance best practices and offer a forward-looking roadmap for technical and non-technical leaders alike.
Led by a dedicated team of experts and thought leaders from ModelOp, we’ll explore strategies to balance innovation with safety, quality, and financial due diligence as Agentic AI enters real-world workflows.
Key questions we’ll discuss:
What immediate steps should enterprise and AI leaders take to prepare for the oncoming wave of Agentic AI use cases?
What new enterprise architectures, protocols, and governance models are essential for controlling Agentic AI?
How can organizations detect and prevent agent misuse, data leaks, or malicious activity across complex ecosystems?
How do you measure ROI while reducing risk in autonomous systems that act independently?
What role will AI governance play in monitoring usage and cost controls?
Discussion Points
What new governance tools will be required to support the demands of Agentic AI, supporting visibility and control at scale.
What leaders can be doing now to prepare for Agentic AI including stakeholder alignment, processes to corral the wild west of Agentic AI, and usage guidelines like risk assessments and cost controls.
Real-world risks, examples, and mitigation strategies for security, privacy, and responsible AI teams.
How do you demystify technical frameworks and understand MCP, A2A and the secure protocols powering autonomous workflows.
How leading enterprises are structuring metrics around business value, risk and reduction to support Agentic AI ROI.
Agenda
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(by GDS Moderator)
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Speaker:
Daniel Zikovitz, Director of Digital Innovation & AI, GE Healthcare -
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Speakers:
Jim Olsen, CTO, ModelOp
Sam Talbott, Senior Manager, Global Risk, John Deere
Sangame Krishnamani, Capital One
Title:Agentic AI risks, value, and safeguards in the enterprise: How to manage the flood of Agentic AI use cases, control the risks, and avoid the hype.
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Moderated by GDS Moderator
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Speaker:
Jay Combs, VP Marketing, ModelOp