Lubrizol leverages AI and cloud computing to accelerate specialty chemical innovation, enabling faster testing, better decisions, and sustainable material development without sacrificing performance.
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As companies look to accelerate innovation with artificial intelligence, cloud computing, and advanced modeling, the primary challenge is connecting new technologies to reliable data, scientific expertise, and the practical realities of bringing products to market. For specialty chemicals manufacturer Lubrizol, digital transformation is all about giving researchers the tools to test ideas faster, make better-informed decisions, and develop more sustainable materials without compromising performance. Girish Rao, vice president of information technology at Lubrizol, says the company is building a digital foundation that connects business processes, modern data platforms, and cloud infrastructure to support its research and development (R&D) teams. Their goal is to combine decades of accumulated technical data with the deep expertise of chemists and engineers who understand customer needs as well as the physical constraints of their work. Data scientists can help identify patterns, test new hypotheses, and model possibilities before researchers conduct physical experiments. But, Rao emphasizes, “it’s not about replacing scientific judgment; it is about giving our scientists better tools.” Scientists, data scientists, and IT teams approach problems from different perspectives, prioritizing experimental validity, model performance, and platform security and scalability, respectively. By bringing these groups together in “fusion teams,” Lubrizol aligns them around shared objectives, starting with small pilots to build trust. “Once the trust is built between the team members and they know what value they’re about to create,” Rao says, “things go a lot better.” Cloud infrastructure also gives the company flexibility to access computing resources and modern tools without making the substantial investments required to build and maintain its own data centers. These capabilities could prove especially valuable in advancing sustainability. Digital modeling can help researche
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