operations, higher quality, faster cycle times and lower maintenance costs. Agentic AI becomes powerful when leaders clearly define intent and constraints, and the system executes with speed and consistency. Robotics and autonomous driving technologies follow the same pattern. When AI is integrated into scheduling, maintenance, logistics and mobility operations, it shifts from an interesting technology to a performance driver. The mindset shift is from exploring possibilities to executing against clear business objectives. What are the most promising and practical AI applications in manufacturing today? The strongest use cases link digital intelligence directly to physical systems. For example, computer vision can guide robotic systems and detect defects instantly, while agentic AI optimises production schedules across multiple facilities. Autonomous driving technologies enhance safety and efficiency in industrial yards and fleet operations, and AI systems capture the expertise of experienced technicians, scaling knowledge across the workforce. Because I have led IIoT and cybersecurity portfolios, I understand the complexity of legacy infrastructure and fragmented data environments. At Microsoft, we bring together cloud, AI and security to unify those systems and enable co-ordinated decision-making across plants and fleets. That integration reduces cost, increases resilience and creates new service opportunities. The opportunity is to convert top AI use cases into ROI efficiently and effectively. How would you describe the partner community in industrials and manufacturing, and where is it adding the most value? Industrial transformation depends on collaboration. From my experience, the strongest results come from co-ordinated ecosystems of original equipment manufacturers, system integrators and technology innovators. The future favours Rodriguez (centre) with Bosch’s Tanya Rueckert (left) and Paul Thomas at CES 2026, announcing their joint work on agentic AI for production 35 EXECUTIVE INTERVIEW
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