The central challenge, then, lies in rethinking how people, processes and technology work together.
In industries as diverse as customer experience and agricultural equipment, the same pattern is emerging: Traditional organizational structures—centralized decision making, fragmented workflows, data dispersed across incompatible systems—are proving too rigid to support agent AI. To unlock value, leaders must rethink how decisions are made, how work is executed, and what humans uniquely have to contribute.
Ryan Peterson, EVP and chief product officer at Concentrix, said, “It’s very important that humans continue to verify content. And that’s where you’ll see more energy being put into it.”
Much of the conversation focused on what could be described as the next major unlock: operationalizing human-AI collaboration. Rather than positioning AI as a standalone tool or “virtual worker,” this approach reimagines AI as a system-level capability that augments human judgment, accelerates execution, and reimagines work from end to end. That change requires organizations to map the value they want to create; Design workflows that blend human oversight with AI-powered automation; And build the data, governance, and security foundations that make these systems trustworthy.
“My advice is to expect some delays because you need to make sure you keep data secure,” says Heidi Huff, vice president of North America aftermarket at Valmont. “As you think about commercializing or operationalizing any part of the use of AI, if you start from ground zero and keep governance at the forefront, I think that will help outcomes.”
Early adopters are already showing what this looks like in practice: starting with low-risk operational use cases, shaping data into tightly scoped enclaves, incorporating governance into everyday decision making, and empowering not just technologists, but also business leaders, to identify where AI can create measurable impact. The result is a new blueprint for AI maturity that is based on reengineering the operations of modern enterprises.
“Adaptation is really about doing existing things better, but reimagining is about discovering entirely new things that are worth doing,” says Hung.
This webcast is produced in partnership with Concentrix.
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 written by human writers, editors, analysts, and illustrators. This includes writing surveys and collecting data for the surveys. The AI tools that may have been used were limited to secondary production processes that underwent thorough human review.
