The growing impact of AI in manufacturing

Most methods used to measure productivity were designed for the era of the industrial economy. In factories, the use of human intellect was limited, and most work depended on manual labour. At that time, if a company wanted to produce more goods, it had to hire more people, install more machines, or make employees work longer hours.

AI does not fit this model. It supports thinking and decision-making without requiring more employees or more time. As a result, many of its benefits do not clearly show up in statistics, even though companies do gain from them.

A closer look shows that its impact is greater at the individual level. Because of AI, work speed increases by an average of up to 14 per cent. At the same time, errors reduce, tasks are completed faster, and coordination improves.

These benefits are significant, but they mostly do not appear as higher output in productivity data. Companies use them to complete work faster, bring consistency in responses, and simplify internal operations.

From the outside, it may appear that there has been no change in output, but internally the way work is done changes substantially. The gains from faster execution are largely absorbed in fixed-price contracts, protection of margins, and quality control, rather than showing up as higher productivity.

AI mainly saves time rather than labour. It speeds up drafting, searching, error correction, summarisation, and decision-making.

In production, it can be utilized effectively—primarily to identify defects during the manufacturing process and to accurately compile data on raw material and finished product inventories.

However, productivity metrics are designed to measure changes in output per hour worked, not how quickly uncertainty is reduced or how much coordination improves.

There is another overlooked aspect as well. Productivity analysis focuses entirely on “averages,” whereas AI’s most consistent impact is on “variability.” The greatest improvement is seen among employees, with fewer errors and more reliable outcomes.

For companies, reliability and consistency are just as important as higher average output.

Today, AI is transforming the way work is done at a much faster pace. For India, this is especially significant. AI will very quietly, through small incremental changes, accumulate over time and create a far-reaching impact.