Much of the conversation around AI (artificial intelligence) in manufacturing and mobility has focused on the technology itself—algorithms, models, and digital capabilities. But here at Connected World and The Peggy Smedley Show, we always talk about the technology, the people, and the process. In this era of agentic AI, where intelligent systems don’t just analyze data, but begin to act, orchestrate, and autonomously execute across the enterprise, we must keep people and process top of mind.
This is precisely the conversation I had recently with John Reed, global solutions leader, manufacturing and mobility industries, Microsoft, where he suggests we are moving from islands of operation to islands of successful AI implementation. He says roughly 70% of the scaling success of agentic AI will depend on people and process.
The bottomline is we are at a clear inflection point. Across industries and geographies, adoption is accelerating—not just in experimentation, but in core business functions, according to Reed.
“What we are seeing globally is that we are moving from pilots as a state of the industry to deep implementation, which involves business process reengineering and the orchestration of technology, process, and change across the enterprise,” he says.
This shift is significant. For years, companies have been testing AI in isolated use cases and small pilots delivering incremental value. Now, organizations are beginning to connect those efforts, embedding AI more deeply into operations and decision-making.
As Reed describes it, AI is evolving into something much bigger: an enterprise nervous system.
That “nervous system” analogy is powerful. It reflects a future where AI is not just a tool, but a connective layer, linking data, systems, and workflows across the entire business.
The next step now is to rethink how work gets done: How can processes be redesigned? How can intelligent agents be coordinated across departments? And how can decisions and actions flow seamlessly from one part of the organization to another?
Manufacturers are already moving in this direction, but creating this roadmap for business is easier said than done in a lot of cases.
“That aspiration needs to be achieved in clear and measurable steps—weeks and months, not months and years. It is having a strong strategic vision and being really practical about how that gets built out and have that build out happen in incremental steps around which you can measure progress, fail fast if necessary, and improve.”
Reed suggests a checklist for organizations looking to move forward:
- Establish a strong data foundation.
- Think deeply about culture and workforce skills.
- Build governance that ensures trust, consistency, and responsible use of AI across the enterprise.
- Plan for scale—not just in terms of technology, but also the people and processes required to sustain it.
- Invest in partnerships that can accelerate capability, fill gaps, and support long-term transformation.
Each of these elements reinforces the same idea: scaling AI is as much an organizational challenge as it is a technical one.
In the end, the companies that succeed in this next phase of AI won’t simply be the ones with the most advanced models. They will be the ones that rethink how their businesses operate, aligning technology with people, processes, and culture.
Agentic AI holds tremendous promise but realizing it requires a shift in mindset. The focus must move beyond pilots and point solutions to true enterprise transformation. And that transformation, as Reed makes clear, scales with people and process.
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