How Santosh Singh is bringing manufacturing discipline to AI work design

For Santosh, choosing an AI tool comes after understanding what needs to change.

His manufacturing experience taught him to examine work where it happens. The people performing it bring knowledge that a process description alone may miss: where things slow down, why exceptions occur, and what it takes to produce the right outcome.

He brings the same discipline to decisions about AI.

That starting point keeps the business problem visible while the team considers possible improvements, including where technology could help.

Working with Reejig, DENSO developed a view of work broken down into tasks and subtasks.

That detail provided a foundation for understanding what people actually did before deciding how their work should change. Connecting tasks with skills also helped make the relationship between work and employee development more concrete.

For Santosh, the usefulness of that picture depended on whether the business recognized it. Work data needed to reflect the organization’s experience closely enough to support decisions.

DENSO brought leaders and people doing the work into validating the picture.

Their involvement helped establish where the data matched reality and where it needed refinement. It also gave the business a role in shaping the understanding that would inform redesign.

This reflected Santosh’s wider approach to change: practitioners’ knowledge belongs alongside the data. People need to trust the description of their work before using it to consider new responsibilities, different workflows, or AI support.

Validation therefore helped create a shared foundation for those conversations across the organization.

With a more detailed picture of work, Santosh’s focus extended beyond individual tasks to how work moved across the business.

His manufacturing perspective drew attention to the entire flow: the handoffs between teams, the bottlenecks that delayed progress, and the responsibilities needed to keep work moving.

Improving one task has limited value if the wider process still struggles. Understanding those connections creates opportunities to reconsider how the work should operate across functions.

Human judgment remains central to that thinking. Santosh considers where people should lead, where AI could assist, and where people need to supervise or evaluate its contribution. The aim is to design those relationships deliberately, with clear responsibility for the outcome.

Santosh’s longer-term ambition is to connect this understanding of work with employee development, career pathways, and workforce planning.

Knowing which tasks people perform helps make conversations about skills more specific. It gives leaders a basis for considering how responsibilities might change and what expertise people will need.

As DENSO develops its approach, keeping that understanding current will matter. Changes in technology, workflows, and business needs will create new questions about how work should be organized.

Santosh’s contribution is a disciplined way to answer them: examine the problem, involve the people who understand it, and assess improvements in the context of the whole flow of work.