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

Efficient and resilient operations that adapt and evolveFocus 2 AI turns operations into adaptive systems that sense, decide and improve continuously across networks. Operations sit at the core of value creation, spanning sourcing, manufacturing, supply chains, logistics, maintenance and field services. Historically, these functions were optimized for efficiency and stability through forecasts, standardized processes and human coordination to manage variability and exceptions.AI introduces a fundamentally different architecture across this value chain. By embedding real-time sensing and predictive intelligence into execution, it enables operations to shift from reactive, scheduled execution to adaptive, predictive and learning-based systems that respond dynamically to changing conditions. AI-enabled transformation of operations and supply chain TABLE 2 –Improve operational efficiency and performance by proactively reducing bottlenecks, downtime and defects. 20–50% reduction in defect rates; up to 10–30% reduction in scrap and rework, leading to over 10% earnings before interest and taxes (EBIT) impact111 From manual coordination to human-AI coordination and AI-orchestrated execution: AI and robots take on routine, heavy and hazardous work while humans focus on oversight and judgement within defined guardrails. –Increase operational flexibility, stability and resiliency for just-in-time execution by continuously adjusting production as conditions change. Up to 27% reduction in order lead time; up to 20–30% reduction in inventory; 5–8% improvements in fill rate through real-time demand/supply balancing122 From reactive fixes to pre-emptive resilience: Early warning systems detect deviations during execution and trigger predefined responses before disruptions escalate. –Turn operations into a source of innovation and growth by embedding automation, digital simulation and embodied AI directly into the workflow. Organizations with AI-enabled intelligent operations achieve 2.4 times greater productivity and 2.5 times higher revenue growth133 From forecast-driven planning to real-time sensing: Fixed schedules give way to continuous sensing of demand, supply and production signals to rebalance workflows dynamically. 4 From one-speed execution to outcome-driven, continuous network-wide improvement: AI learns from execution outcomes and local and tacit knowledge to continuously improve decisions across plants, assets and teams. –Improve sustainability and safety by optimizing energy use and early risk detection. Approximately 40–60% potential reductions in energy consumption and emissions14 At a glance Ambition: opportunities to capture Action: how organizations are changing Fulfilment Scheduling Planning Delivery Production Organizational Transformation in the Age of AI: How Organizations Maximize AI’s Potential 13