Photo Courtesy of Nimit Patel
In the past couple of years, no topic or technology has gained as much focus on a global stage as Artificial Intelligence (AI). A lot of these recent advancements have emerged in the United States where both the past and current President of the United States have made AI a national priority, along with many other global leaders.
AI is reshaping all sectors and industries at an unprecedented pace, and one such area is the world of heavy industrial processing. This change is visible across mines, power generation, chemical manufacturing and even agriculture, with AI unlocking efficiencies by reducing fuel usage, material wastage and optimizing processes to levels never seen before.
Leading this transformation is Nimit Patel, an AI and machine learning expert at QuantumBlack, the AI division of McKinsey & Company. With a rare blend of deep AI expertise and a solid foundation in industrial engineering, Nimit has delivered measurable impact across heavy industries worldwide, from copper mines in South America to power plants across North America and Asia.
Bringing together AI and Industrial process expertise
A recent McKinsey study highlighted that AI has the potential to generate an additional $1 trillion in value just for the industrial sector, and this is just the beginning. But despite these remarkable advancements, adoption across the industrial sector remains low as building AI systems for these processes requires a deep understanding of both AI & the process, leaving a massive untapped opportunity for those with the expertise to bridge this gap.
Nimit’s work fills this gap. He is implementing AI solutions and redefining the very fabric of industrial operations through cutting-edge innovation. Leading the use of AI across these industries, his work has become the gold standard and emulated by other AI professionals, which gained him the prestigious 2025 Global Recognition Award.
At an early stage of his career, he recognized the transformative potential of machine learning. He honed his expertise in AI-driven optimization, deep learning and building digital twins for complex systems, bridging the gap between traditional industrial processes and cutting-edge AI methodologies.
What attracted Nimit the most about this work is the multi-dimensional impact it could drive: optimizing industrial processes not only led to operational efficiencies and cost savings, but it also helped in reducing fuel usage and emissions – thereby also pushing towards sustainability, which was a constant motivator for him.
This expertise is what paved the way for his career growth at McKinsey & Company, where he currently leads globally impactful data science projects and deployments for optimizing heavy industrial processes.
Optimizing mines, power plants and heavy industries globally
During his career, Nimit’s impact spans multiple industries, with some of his most groundbreaking work taking place in mining, energy and chemicals. One of his most notable achievements occurred in the mining sector for one of South America’s largest copper producers. Faced with the challenge of helping the concentrator extract more copper from the ore in an efficient manner, he and his team developed a cutting-edge AI recommendation engine that combined neural network-based predictive models with meta-heuristic optimizers.
The result was a remarkable 10 percent increase in copper production, resulting in a $350 million boost in EBITDA and an additional 200 million pounds of copper produced annually.
Another landmark success came in the energy sector, where Nimit and his team developed a novel AI solution that optimized thermal efficiency and reduced emissions across a large fleet of fossil-fueled power plants. Through deploying over 400 AI models to enhance plant efficiency and predict equipment failures, his team achieved a significant reduction in CO2 emissions—equivalent to removing 300,000 cars from the road, while also generating over $60 million in savings within the first year. This initiative solidified his position as an industry leader in AI-driven energy efficiency.
Inspired to take this work and scale it globally, Nimit also led the development of a first-of-its-kind proprietary internal QuantumBlack solution OptimusAI. The solution worked as an AI co-pilot for engineers and plant operators to improve productivity and efficiency of their heavy industrial processes. With over 100 use-case deployments globally, and impact of more than $4B created, his work has set the industry standard for optimizing heavy industrial processes globally.
Unlocking sustainability and materials discovery with AI
Nimit also believes in constantly evolving with the technology landscape, so with the recent advent of Generative AI, he has also been at the forefront of bringing that to industrial R&D. In the chemicals sector, he spearheaded the development of a revolutionary AI-powered molecular discovery engine, leveraging generative AI to speed up the identification of new coating polymers. This molecular & materials discovery approach enabled to cut R&D timelines by a remarkable threefold, accelerating time-to-market by a couple of years and is poised to revolutionize how industry approaches research for novel molecules & chemicals.
As the society calls for cleaner energy, optimized resource utilization and next-generation manufacturing, Nimit’s work serves as a beacon of what is possible when AI meets industrial engineering at scale. In the words of those who have witnessed his work firsthand, Nimit Patel is not just an AI expert, but a pioneer who is redefining the future of heavy industry.
