The central challenge, then, lies in considering how people interact with processes and technologies.
In industries as diverse as customer experience and agricultural equipment, the same pattern is emerging: traditional organizational structures—centralized decision-making, fragmented workflows, data spread across disparate systems—are proving too tough to support agentic AI. To unlock value, leaders must rethink how decisions are made, how work gets done, and what people should contribute as individuals.
“It’s critical that humans continue to verify this content. And that’s where you’re seeing more energy,” said Ryan Patterson, EVP and Chief Product Officer of Consex.
Much of the conversation has focused on what could be described as the next big unlock: making human AI collaboration a reality. Rather than positioning AI as a standalone tool or “virtual worker,” this approach posits AI as a system-level capability that augments human judgment, accelerates execution, and automates end-to-end tasks. This change requires organizations to map the value they want to create. Design workflows that combine human supervision with AI-driving automation. And build the data, governance and security foundations that make these systems trustworthy.
“My advice would be to expect some delays because you need to secure the data,” says Heidi Huff, VP of North American aftermarket at Valmont. “As you think about commercializing or operating any piece of AI use, if you start from ground zero and have governance at the forefront, I think that will help the results.”
Early adopters are already showing what this looks like in practice: starting with low-risk operational use cases, structuring data into tightly scoped enclaves, embedding governance into everyday decision-making, and empowering business leaders, not just technologists, to recognize that AI can create measurable impact. The result is a new blueprint for the maturity of AI in how modern enterprises operate.
“Improvement is really about doing existing things better, but reimagining is about discovering entirely new things that are worth doing,” Hung says.
This webcast is produced in partnership with Consex.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review. It was researched, designed and conducted by human writers, editors, analysts, and writers. This includes writing the survey and collecting data for the survey. The AI ​​tools that have been used were limited to secondary production processes that passed full human review.