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January 25-27, 2027 | Hilton Orlando Lake Buena Vista

Moving AI beyond productivity 

The Agentic AI conversation is shifting rapidly. Leaders are no longer asking what they can do with Agentic AI. The real opportunity now is scaling it, governing it, and turning it into measurable business value.
 
The Agentic AI Transformation Summit brings together both AI and transformation leaders, creating the cross-functional conversations required to scale agentic AI successfully. Success will depend on more than the technology itself; leaders must work together to drive adoption, reinventing operating models, transforming workforces, strengthening governance, and driving enterprise-wide adoption at scale.
 
The pilots are over. It's time to reinvent.

Why Should You Attend The Agentic AI Summit?

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Scale Agentic AI  

Learn how leading organizations are moving beyond experimentation to embed agentic AI into core business operations

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Deliver Measurable Value 

Explore real-world case studies demonstrating how enterprises are generating ROI from agentic AI initiatives

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Accelerate Adoption  

Gain practical strategies for driving workforce readiness, stakeholder buy-in and sustainable AI transformation 

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Transform the Operating Model  

Discover how organizations are redesigning teams, governance and business processes to thrive in an AI-enabled future

Meet the Voices Driving Enterprise Transformation   

MOVING BEYOND PILOT PARALYSIS AND TOWARDS REAL ENTERPRISE VALUE 

As economic pressures intensify, organisations are under growing pressure to prove that AI investments deliver measurable business value. Yet many remain stuck in “pilot paralysis”, running isolated experiments that never scale. Success requires more than great technology; it demands the right operating model, governance, data foundations, and ROI framework. In this panel discussion, we’ll explore why AI initiatives stall and how organizations can build the capabilities needed to move from proof of concept to enterprise-wide impact.

  • Achieve measurable AI ROI by aligning use cases with strategic business outcomes 
  • Move successful pilots into production by building the right governance and operating model 
  • Reduce the risk of fragmented AI adoption through stronger data and technology foundations 

    SCALING ENTERPRISE AI, SYSTEMS, TEAMS, AND OPERATING MODELS 

    Enterprise AI leaders face a pivotal challenge: transitioning from isolated use cases to resilient, production-ready AI systems—without disrupting core operations. This panel explores how to architect the right technical foundations, team structures, and cultural shifts needed to operationalize AI at scale. Reimagine business processes with LLMs, agentic workflows, process mining, and automation to enable seamless, end-to-end execution

    • Establish clear roles, structures, and ways of working across AI, data, engineering, and business teams to accelerate delivery 
    • Drive sustained adoption through capability building, effective governance, and cultural change that supports enterprise-wide impact 


      An Easy Guide to the Agentic Transformation Case Studies

      From governance and workforce transformation to enterprise-wide adoption, discover how organizations including Pfizer, CME Group, William Jessup University and Cencora are turning agentic AI into measurable business outcomes.

      Download the guide and start planning the case studies you don't want to miss.

      Be at the forefront of innovation

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      Scaling from pilot to production

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      Enabling agentic AI adoption

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      Building trust and governance for agentic systems

      What our Community Has to Say 

      Report | Agentic AI Governance Made Practical: What Leaders Need to Do Now to Balance Risk, Innovation, and Accountability

      As Agentic AI becomes embedded across enterprise workflows, the challenge for leaders has fundamentally shifted. It's no longer about if you use AI; it's about how you stay in control of systems that can act on your behalf.

      But here's the real challenge: Most governance models were built for static systems, not autonomous agents that learn, adapt, and make decisions in real time.

      This report gives you clear and actionable insights for governing Agentic AI in the real world, helping you shift from reactive compliance to confident, scalable control.