Manufacturers to Experience Operational Gains from Early AI Adoption: Study

The average number of AI models in production among manufacturers has declined from 242 today to a projected 189 next year.

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While only 31% of manufacturers describe themselves as "Transformational" in their AI adoption – the lowest share among sectors surveyed – they consistently report lower barriers to reaching that maturity, according to new benchmark data from S&P Global Market Intelligence, in collaboration with Vultr.

“The data shows what that discipline produces: Lower perceived barriers to maturity. Platform engineering that unifies governance before chasing scale. Model consolidation that prioritizes proven value over portfolio breadth,” the report says. “This isn't the fastest path to Transformational AI, but it may be the most durable. As simulation-driven production, robotics coordination, and real-time analytics become table stakes, manufacturers building AI on integrated platforms will have the foundation to scale sustainably.”

Key takeaways:

·        The benchmark study categorizes AI maturity in three stages: Operational (early functional gains), Accelerated (AI across multiple functions), and Transformational (AI embedded into core operations).

·        Currently, 25% of manufacturing respondents remain Operational compared to 19% across all industries, and only 31% have reached Transformational maturity.

·        But across nearly every organizational barrier – skills shortages, data quality, security, cultural alignment, and more – manufacturers report materially lower severity. The skills shortage register stands at 46% for manufacturers, compared to 62% for all other respondents. Data quality: 50% vs. 60%. Security: 49% vs. 60%. Even leadership alignment and company culture come in 13 points lower.

·        35% of manufacturers have built or are in the process of creating internal PaaS infrastructure. Within two years, the figure is projected to reach 45%, while reliance on hyperscaler-managed PaaS is expected to decline from 56% to 42%.

·        Manufacturers still run 30% of their training workloads and 28% of their inference on major public clouds, both figures well above the industry averages.

·        The average number of AI models in production among manufacturers has declined from 242 today to a projected 189 next year.

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