Enterprise AI in 2026: From Experimentation to Operational Value

Presented By

Tom DeBevoise, ACR
Denis Gagne, Trisotech

Description

By 2026, enterprise AI is no longer about experimentation or bold claims of full autonomy. The focus has shifted to building systems that work in production, under real constraints, and at enterprise scale. Organizations that succeed are those that treat AI as an architectural concern, grounded in processes, decisions, and governance, not as a collection of tools.

This webinar examines how to design enterprise AI solutions that reliably augment human work, improve decision quality, and increase productivity. We focus on the practical integration of Generative AI, Intelligent Autonomous Agents (IAI), and explicit process and decision models to create systems that are controllable, explainable, and operationally safe.

What we will cover:

A Top-Down Enterprise AI Strategy
How to anchor AI initiatives in business objectives, processes, and decisions, so they scale beyond pilots and deliver measurable value.
A Practical Architecture for Intelligent Agents
How to design bounded, observable agents that use thinking models responsibly, leverage expertise at scale, and operate within enterprise governance.
Process and Decision Models as Control Structures
Why explicit models are essential when combining symbolic and sub-symbolic AI, and how they provide the stability AI systems need in production.
Context as a First-Class Concern
How to build and manage situational context so conversational systems and thinking models behave predictably and produce usable results.

Who should attend

This session is for enterprise architects, process and decision modelers, AI leaders, and executives who are moving beyond pilots and looking to operationalize AI responsibly and at scale.

What you will gain

A clear, practical view of what enterprise AI should look like in 2026, the architectural patterns that matter, and the design choices that separate durable solutions from short-lived experiments.