Manufacturing Industry "AI Leaders" Focus on Production, Quality and Maintenance
BIRMINGHAM, Mich. — Manufacturers generating the strongest returns from artificial intelligence are concentrating investments on production planning, quality, maintenance and supply chain operations, according to a new report from NTT DATA.
The report, based on responses from 574 manufacturing and automotive executives worldwide, found that AI leaders distinguish themselves less by the amount of AI they deploy and more by how deeply they embed it into operational workflows that directly affect factory performance. The report classified AI leaders as manufacturers with mature AI deployments and measurable business results, while laggards were defined as organizations with limited adoption and little or no financial return from AI investments.
According to the study, leading manufacturers are increasingly redesigning production, quality and maintenance processes around AI rather than treating the technology as a standalone tool or pilot project. The report found that 93.2% of AI leaders use AI to support operational functions such as planning, engineering and operations management, compared with 68.8% of laggards.
The report also found that 38.6% of manufacturing and automotive AI leaders are rebuilding core operational systems with embedded AI capabilities, compared with just 12% of laggards. Organizations trailing in AI adoption were more likely to rely on AI add-ons layered onto existing software platforms.
NTT DATA said manufacturers are increasingly moving AI beyond experimentation and into day-to-day decision-making across production, quality inspection, predictive maintenance and supply chain execution.
"In manufacturing and automotive environments, leaders increasingly recognize a hard truth: Ambitious AI goals cannot be realized if underlying production, planning and operational systems are fragmented, underpowered or difficult to govern," the report states. "Disconnected tools drive duplicated costs, inconsistent controls and failures under the demands of real-world, high-stakes operations. Manufacturing and automotive AI leaders address this challenge by embedding AI directly into core systems rather than bolting it onto existing applications. This approach enables scalability, reliability and consistency across plants and value chains."
The study also discussed the relationship between AI and employees.
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"Manufacturing and automotive AI leaders use AI to augment experienced employees rather than replace them. 26.7% of manufacturing and automotive AI leaders empower experienced employees with AI tools, allowing them to focus on higher-value strategic work while junior staff handle AI-augmented tasks, compared with 20.0% of manufacturing and automotive AI laggards."
The full report is now available.
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