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2026 Global AI Report: A Playbook for AI Leaders
Why AI strategy is your business strategy: The acceleration toward an AI-native state. Explore executive insights from AI leaders.
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Liantis
Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
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CLIENT STORIES
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Liantis
Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
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Randstad
We ensured that Randstad’s migration to Genesys Cloud CX had no impact on availability, ensuring an exceptional user experience for clients and talent.
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2026 Global AI Report: A Playbook for AI Leaders
Why AI strategy is your business strategy: The acceleration toward an AI-native state. Explore executive insights from AI leaders.
Access the playbook -
- Careers
Overview
Where AI strategy drives manufacturing performance
The 2026 Global AI Report for manufacturing reveals how leading manufacturers convert AI strategy into measurable operational and financial impact. Based on global executive research, the findings show that disciplined governance, core system reinvention and workflow integration separate AI leaders from laggards. Manufacturers that embed AI across production, planning and enterprise systems are widening the execution gap at scale.
Highlights
FAQ
AI leaders in manufacturing have a well-defined AI strategy, mature or evolved AI adoption and measurable financial and operational impact. They move beyond pilots, embedding AI into production, planning and enterprise systems at scale.
83.8% of AI leaders in manufacturing are increasing AI investment, reflecting confidence built through early operational wins. Leaders convert proof points into disciplined reinvestment that compounds performance gains.
Leaders rebuild core systems with embedded AI, centralize governance and redesign workflows end to end. Laggards rely on fragmented pilots and bolt-on solutions that limit scale and resilience.
67.6% of AI leaders in manufacturing follow centralized governance models. In asset-intensive, safety-critical environments, structured oversight enables faster scaling without increasing risk.
93.2% of AI leaders embed AI into operational workflows such as production, planning and engineering. Concentrating on high-impact domains allows leaders to drive measurable improvements in throughput, reliability and cost discipline.
Key findings
- Leading manufacturers pair decisive execution with disciplined AI governance.
- Centralized oversight enables AI to scale safely across plants and value chains.
- AI leaders embed intelligence into core production and planning systems.
- Operational workflows are redesigned end to end to turn pilots into plant-wide performance.
- 83.8% of AI leaders in manufacturing are increasing AI investment.
- 38.6% are rebuilding core systems with embedded AI.
- 67.6% follow centralized AI governance to scale with control.
- 93.2% embed AI directly into operational workflows.
AI is becoming the operating backbone of the enterprise. The manufacturers pulling ahead are the ones embedding AI into production, planning and engineering, governing it with discipline and scaling it across plants with confidence. That’s where real performance gains in throughput, resilience and margin are being unlocked."
Global Manufacturing Leader, NTT DATA
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