From Pilot to Scale: Putting Engineers at the Center of Industrial AI

Moving an AI pilot into everyday manufacturing requires both technology and workforce preparation. At Reimagining Tomorrow: AI, Innovation and Workforce Transformation, we explored how engineers can shape the systems they use. The event brought together business leaders, HR practitioners and technology innovators.

On Aug 21, 2026, Head of Solutions Mike Feng presented “From Pilot to Scale: Transforming Advanced Manufacturing with Industrial AI Agents”. He highlighted three linked priorities: building the right technology, developing the right talent and solving real industrial challenges. Engineers’ knowledge and involvement are central to that approach.

Our approach puts engineers in the role of teaching and scaling industrial agents. It aims to free time for learning and higher-value work while keeping production authority with people. Engineers contribute their understanding of the work and retain authority over production as the use of agents grows.

In a separate discussion in July 2026, CEO Xu Jinsong identified heterogeneous operating environments, fragmented data, deployment capability, workforce adoption and the need for reliable solutions as barriers to scaling industrial AI. Those challenges inform our approach to preparing a solution for use beyond its first application.

Each barrier requires attention. Data must be available to the solution, different operating environments must be understood, and deployment capability must be in place. Manufacturers also need to prepare the people who will work with the system. Technology and workforce readiness therefore need to advance together.

Our N–1–N pathway is designed to bring industry knowledge and proven use cases together into a repeatable deployment approach, then extend it across factories and applications. It connects data, agents and applications, and organizational knowledge, creating a foundation for scale informed by industrial experience.

For manufacturing and HR leaders, the practical questions are connected: which engineering knowledge should inform the system, how will people learn to work with it, who retains production authority, and what must be ready before the approach can be repeated elsewhere? Addressing them together makes workforce development part of the deployment plan.

We see talent development as part of preparing an AI deployment to grow. At the event, we connected engineers’ learning and higher-value work with the technical task of scaling agents. A plan for scale needs to explain both how the technology will operate and how the people responsible for production will shape its use.