Data quality worries are holding back manufacturers from implementing AI, with less than one-third ready to implement AI despite AI growth optimism
While manufacturers are enthusiastic about AI, they’re holding back because of concerns about poor data quality.
Research from Riverbed found more than nine-in-ten (92%) manufacturing leaders agree that AI will provide a competitive advantage and 65% expect it to be a driver of growth by 2027.
However, far fewer say they feel fully prepared to adopt and deploy the technology today, with under one third (32%) fully prepared to implement AI. Riverbed noted this is 5% lower than the average across industries.
One of the major factors holding manufacturers back is data quality, the report found. While 87% of manufacturing leaders agree that great data is critical for AI success, over two-thirds (69%) question how effective their firm currently is at using data for AI.
Under half of those surveyed (42%) classed their organization’s data as ‘excellent’, across measures such as accuracy and completeness, with the same figure identifying their low data quality as a barrier to further AI investment. This is in line with other recent reports that chief data officers (CDOs) are blaming poor data quality on slow AI adoption.
Meanwhile, with the manufacturing industry particularly reliant on legacy systems, 92% manufacturing leaders express fear that AI could expose proprietary data to the public domain.
“AI is transforming the manufacturing industry, offering significant benefits in terms of operational efficiencies, reducing costs, and the ability to innovate at a faster pace to maintain a competitive edge,” said Jim Gargan, CMO at Riverbed.
“However, for manufacturers to deliver substantial performance improvements and improve their AI Ops initiatives, they must focus on the quality of their data.”
A majority manufacturers have at least moved beyond the stages of assessing and experimenting with AI, according to Riverbed. The study found that more than half (56%) are accelerating their AI strategies by investing in infrastructure and talent, while 29% are approaching the final stage of full AI integration within daily operations.
Riverbed’s data comes from the newly-released, manufacturing sector specific results of its wider Riverbed Global AI & Digital Experience Survey. The larger survey took in responses from 1,200 IT, business, and public sector decision makers across the US, UK, Australia, France, Germany, Spain, and Saudi Arabia in June 2024.
Interest and concerns over AI transformation
Manufacturers can benefit from AI in terms of increased efficiency and productivity, improvements in product quality, optimizing inventory levels and production processes, and applying proactive data-driven decision making.
Riverbed found that over the next three years, 80% expect to introduce workflow automation, with 69% moving to automated remediation and 63% implementing 24/7 support availability such as chatbots.
To get in gear for AI, more than half (57%) of manufacturers have formed dedicated AI teams, and 42% have created observability and/or user experience teams.
While manufacturers are wary of potential security risks, many are working to address these issues, the Riverbed study noted. More than eight-in-ten respondents agreed that observability across all elements of IT will be critical to ensuring AI Ops success.
A similar number noted they are working to tackle network blindspots, including public cloud, enterprise mobile devices, and remote work environments. To counter this, many are focusing on zero trust architecture projects.
However, the report found, there’s something of a reality gap amongst manufacturers, with three-quarters claiming to be ahead of their peers, including 25% who say they are significantly ahead. Only 7% say they are behind.
“This gap between perception and reality indicates many leaders are overconfident about where their IT function is on their AI journey in relation to their industry peers,” Riverbed wrote.
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