Business Transformation World Summit 2026

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Building the AI-Ready Enterprise: Why Process Intelligence Comes First

Moving into the new Agentic AI era requires a foundation most enterprises lack today. Featuring Cardinal Health, this session outlines a practical framework to deploy agents that actually deliver massive business outcomes. 

You'll Learn: 

  • How to train agents on proven patterns, not theory, so they handle real complexity 
  • How to identify which tasks suit agents and which decisions require human judgment in operations 
  • The method to capture context switching, exceptions and workarounds that documentation misses completely 
  • How to measure agent impact against your business goals before you commit budget to scale 
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Train Your Agents on Reality

Generic AI breaks because it learns from SOP documents that miss how work actually happens, the hidden steps, exceptions, and nuances. Your agents break in production when they encounter real workflows with context switching and manual workarounds.

Skan AI's Observation-to-Agent platform captures how your team works across every application to build training data from reality. Deploy AI agents that understand your processes, not generic best practices, and continuously measure their impact.

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Executive Panel Discussion

The Self-Optimizing Enterprise: How Are We Getting There?

The AI debate is over. What matters now is how far you push its advances and how you transform your people from users into architects of intelligent systems.

In a candid executive panel moderated by Skan AI, transformation leaders explored how to redeploy talent as a competitive advantage and scale AI excellence that lasts.

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FAQs

What does Skan AI do for enterprise transformation?

Skan AI captures work across every application to reveal how teams actually operate. It builds foundational data that trains effective, context-aware AI agents. It helps leaders control outcomes with real operational truth.

What makes process context essential before I deploy AI agents?

Real work differs from the “happy path” in SOPs and system logs. Complete operational context reveals decisions, pauses, rework, and fixes that shape outcomes. AI agents need this detail to act safely at enterprise scale.

How does Skan AI support operational excellence goals?

It exposes bottlenecks and errors across end-to-end workflows. It reveals effective paths and the activities that slow teams down. It equips leaders to standardize, optimize, and control outcomes.

What problems does Skan AI solve that legacy tools cannot?

Legacy tools miss context switching, manual fixes, and off-system work. They rely on logs that ignore real user behavior and decisions. Skan AI captures the full trace of work for precise root-cause insight. 

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