CASE STUDY 6 Improving predictive maintenance with AI and robots Nestlé Purina uses AI-powered robots and fleet management software to automate routine equipment inspections and enable predictive maintenance. Robots equipped with thermal and acoustic sensors regularly scan motors and gearboxes for anomalies; AI analyses the data to flag issues early. This approach detects problems before failures, reducing unplanned downtime and allowing operators to focus on higher-value work.15 –Embodied AI systems, including inspection drones and mobile robots, detect physical anomalies and trigger response protocols with only human oversight. –Digital twins simulate changes to equipment settings and operational conditions, allowing adjustments to be tested virtually before physical deployment. Organizational changes observed: –Issue detection is embedded in shared dashboards, agent alerts and inline quality systems accessible to frontline teams. –Risk detection and intervention planning occur earlier, with predefined intervention roles across operations, logistics and procurement. –Resilience is increasingly incorporated into design, supported by playbooks validated through simulation. –Performance is measured by disruption contained and impact avoided, not just recovery speed. –Development and oversight of AI-driven resilience systems becomes a shared responsibility across operations, engineering, data science, information technology (IT) and risk functions. Early vs advanced adopters: –Early: Predictive analytics flag risks and alert human teams. –Advanced: Multi-agent systems simulate risks and reconfigure operations automatically within defined tolerances. CASE STUDY 7 Accelerated problem detection and resolutions At Siemens, generative AI enables frontline workers to flag design and quality issues through natural language, automatically summarizing and routing insights to the right teams. Automation engineers use AI co-pilots to generate and debug programmable logic controller (PLC) code, reducing errors and cycle time, while real-time computer vision detects defects in the factories. These capabilities accelerate problem resolution, improve quality and enhance operational resilience.16 Organizational Transformation in the Age of AI: How Organizations Maximize AI’s Potential 16

Organizational Transformation in the Age of AI How Organizations Maximize AI%27s Potential 2026