Innovating with AI in the special chemicals industry

Lubrizol, a specialty chemicals manufacturer, is laying down a digital foundation that ties together business processes, modern data platforms, and cloud infrastructure for its research teams, according to its vice president of IT, Girish Rao. The idea is to use decades of technical data and modeling to narrow down formulations before chemists run physical experiments.

The piece is partner content, produced by MIT Technology Review's custom content arm in partnership with Infosys, not by its newsroom. It is useful as a window into how an industrial R&D organization talks about AI, but it offers no measured results.

I like the posture here more than the evidence. Rao's line is that this is about giving scientists better tools, not replacing their judgment, and that is the right way to bring AI into a field where a wrong formulation can fail in a customer's product or a regulator's review. Starting with small pilots to build trust across chemists, data scientists, and IT is also how this tends to work in practice.

The sustainability pitch is where I'd push. Modeling more formulations and exploring options such as starch and corn-based materials sounds promising, and the piece is honest that scaling a lab result into production while meeting performance, regulatory, and cost limits is the hard part. But there are no numbers: no cycle-time reduction, no hit rate, no example of a product that got to market faster.

The downside to name is the gap between modeling and reality. If teams start trusting simulated trade-offs over physical testing, or if leadership uses AI to shrink lab headcount rather than expand what scientists explore, the gains could turn into quality and safety problems later. We'll give credit when a company like this shows the outcomes, not just the architecture.

This is sponsored content: a webcast summary produced by MIT Technology Review Insights in partnership with Infosys. Rao also describes 'fusion teams' that pair scientists, data scientists, and IT staff, and cites cloud computing as a way to avoid building and running its own data centers.