For manufacturers, the research identifies two related challenges.
Manufacturers may know where their data is, but many are still struggling to govern it, unify it and put it to work in AI applications, according to new research from data and AI platform company Cloudera.
Manufacturing findings from its Data Readiness Index 2026 on Sept. 8, show gaps in data access, governance and infrastructure are creating barriers to scaling AI across manufacturing organizations.
The findings are based on Cloudera’s broader research into data readiness. In manufacturing, the company reports that 82% of respondents have visibility into where their data resides. But only 58% say all or nearly all of their data is fully governed.
Cloudera said manufacturers are managing growing volumes of operational, production, supply chain, customer and IoT data across distributed environments. The company identifies the ability to integrate, govern, unify and operationalize that data as a continuing challenge.
The difficulty extends beyond the data itself.
According to the research, 20% of manufacturing organizations identify weak integration of AI and analytics into operational workflows as the leading reason their initiatives fail to deliver expected return on investment.
From data to action
The report says the challenge becomes particularly apparent when manufacturers attempt to translate AI-generated insights into operational decisions.
Manufacturing data and processes can be distributed across factories, supply chains, enterprise applications and edge environments. That makes it more difficult to use data consistently across the organization.
Cloudera said manufacturers need to be able to operationalize AI across those distributed environments so that trusted data can support decisions and measurable business outcomes.
“Realizing those opportunities requires more than access to data,” says Morgan Bowling, Cloudera’s director of global industry AI solutions for industrial and manufacturing. “It requires confidence in the quality, governance, and availability of that data across the business.”
Cloudera’s findings also place manufacturing somewhat ahead of other industries surveyed in data visibility and readiness, while still identifying significant governance gaps.
Manufacturers are pursuing AI for applications including production-process optimization, quality control, predictive maintenance and supply-chain resilience. But the research indicates that having access to data does not necessarily mean organizations can use it effectively across those applications.
Governance remains a gap
The 58% figure for organizations reporting that all or nearly all of their data is fully governed points to a gap between knowing where data exists and having confidence in how it is managed.
The report also highlighted infrastructure performance as one of the barriers manufacturers face as they attempt to scale AI across increasingly distributed environments.
For manufacturers, the research identifies two related challenges: making data trustworthy and making AI useful within the processes where manufacturing decisions are actually made.
“Manufacturers that invest in data readiness today will be in a stronger position to scale AI initiatives tomorrow,” Bowling said.
The findings are part of Cloudera’s Data Readiness Index 2026, which examines data-readiness issues across industries.
