3M and Microsoft Team Up to Accelerate AI Infrastructure and Enterprise Transformation
he collaboration combines Microsoft's hyperscale cloud and AI capabilities with 3M's materials science and precision manufacturing expertise to strengthen the physical infrastructure supporting the growing demand for cloud and AI workloads.
3M and Microsoft have announced a strategic partnership aimed at advancing AI data centre infrastructure and accelerating enterprise AI transformation. The collaboration combines Microsoft’s hyperscale cloud and AI capabilities with 3M’s materials science and precision manufacturing expertise to strengthen the physical infrastructure supporting the growing demand for cloud and AI workloads.
As part of the agreement, Microsoft Azure will become the first announced hyperscale cloud provider to deploy 3M’s Expanded Beam Optical (EBO) technology in its data centres. At the same time, 3M will leverage Microsoft’s AI and digital platforms to drive enterprise transformation across key business functions, including customer service, finance, sales and marketing.
The deployment of 3M’s proprietary EBO technology is designed to improve the speed, reliability and efficiency of fibre optic connections within AI data centres. Unlike traditional fibre connectors that require direct contact, the expanded beam optical interface allows for faster installation, greater tolerance to contamination and easier maintenance. According to the companies, Microsoft’s early use of the technology has demonstrated the potential to reduce network deployment timelines in certain environments while maintaining strong signal performance under typical data centre operating conditions. To meet increasing demand from hyperscale cloud providers and data centre operators, 3M is scaling production of the technology and continues to support broader industry adoption through the Expanded Beam Optical Multi-Source Agreement (MSA).
“At Microsoft, we’re redefining the foundation of cloud and AI infrastructure — combining our own innovations with advances from partners like 3M to build datacenters that are faster to deploy, more resilient and ready for the scale of AI. 3M’s EBO solution will help unlock new levels of performance, reliability and efficiency to ensure customers can run their cloud and AI workloads on a trusted, sustainable and advanced environment.”
– Cliff Henson, Corporate Vice President, Cloud Supply Chain and Engineering, Microsoft
Beyond infrastructure, the partnership also supports 3M’s enterprise AI transformation. The company will deploy Microsoft’s AI capabilities to simplify business processes, improve decision-making, enhance customer experiences and increase employee productivity. One of the first initiatives will see Microsoft’s newly launched Frontier Company engineers collaborate with 3M’s Global Business Services team to automate customer order management using AI-driven workflows. The solution will assist with credit checks, delinquency assessments and system updates while incorporating human oversight through monitoring dashboards and approval controls. The companies expect the initiative to reduce manual effort, improve operational consistency, accelerate cash flow and enable more scalable operations.
“At 3M, we view AI as a powerful tool that can accelerate growth, improve customer experiences and help our teams work more effectively. Our collaboration with Microsoft supports that vision through targeted optimization opportunities for our enterprise while advancing the infrastructure needed to power the future of AI. We are excited to deepen our partnership and develop practical solutions that can create mutual value.”
– Jon Van Wyck, Executive Vice President and Chief Strategy officer, 3M
Looking ahead, Microsoft and 3M plan to expand their collaboration through continued technical engagement between engineering and commercial teams and by exploring additional innovation opportunities across Microsoft’s data centre and device ecosystem. The companies said the partnership will focus on addressing evolving requirements for AI infrastructure, including reliability, deployment speed, density and long-term scalability.

