Why OpenText’s AI chief says the human element is the biggest lesson in agentic AI

Even the companies building the technology are discovering that the road to autonomous AI isn’t quite as straightforward as expected.

At OpenText World 2026, Shannon Bell, executive vice president and chief product and technology officer at OpenText, acknowledged that the company had expected to move toward fully autonomous AI workflows much faster than it has. The biggest surprise? The importance of the human element.

In this episode of In The Channel, Bell discusses what OpenText has learned from deploying agentic AI internally, including its global command centre, where human operators and AI agents work together. Those lessons have prompted a more deliberate approach to adoption, with greater emphasis on change management, employee readiness and incremental deployments.

For channel partners, the implications extend beyond the technology itself.

Bell argues that getting enterprise data ready for AI is an ongoing discipline, not a project with a defined finish line. As customers improve data quality and governance, deploy agents and identify new business processes to automate, partners have opportunities to deliver continuing value rather than one-time implementations.

We also discuss OpenText’s evolving AI portfolio, including Aviator and Aviator Studio, and the potential for partners to build repeatable, industry-specific solutions using the company’s technology. Bell acknowledges that partner adoption remains in its early stages, but sees considerable opportunity as customers mature in their AI journeys.

And looking ahead, Bell shares her enthusiasm for hybrid agentic AI, which would allow organizations to deploy AI workflows across cloud and on-premises environments while keeping sensitive data where it belongs.

It’s a candid look at the practical challenges behind the agentic AI vision — and what those challenges mean for the partners tasked with making it work.

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