Manufacturing companies are increasingly investing in artificial intelligence to modernise IT operations, but many remain unprepared to deploy the technology at scale, according to a global survey by Riverbed.
The study, titled The Future of IT Operations in the AI Era, found that 87% of manufacturing leaders and technical specialists say their investments in AIOps – artificial intelligence for IT operations – have delivered returns that meet or exceed expectations. However, only 37% believe their organisations are fully ready to operationalise AI across the enterprise.
The findings highlight strong industry interest in using AI to streamline operations, reduce costs and manage complex global supply chains. Yet significant barriers remain. According to the survey, 62% of AI initiatives in manufacturing are still in pilot or development stages, suggesting many companies are still experimenting rather than deploying large-scale AI systems.
Data quality emerged as one of the most significant challenges. Around 90% of respondents agreed that improving the quality of organisational data is essential for AI success. However, nearly half of those surveyed reported concerns about the accuracy and completeness of their data.
In fact, 47% said they lack confidence in whether their current data can support effective AI outcomes, while only 34% rated their data as excellent in terms of relevance and usability.
Richard Tworek, chief technology officer at Riverbed, said the results illustrate both strong progress and lingering challenges within the sector.
He noted that while manufacturers are achieving positive returns from AIOps investments, many organisations are still grappling with gaps in preparedness and data quality that could slow the wider adoption of AI technologies.
Another key trend identified in the research is the growing focus on consolidating IT tools. On average, manufacturing companies currently use around 13 observability platforms sourced from nine different vendors. As a result, 95% of organisations surveyed are now working to reduce the number of tools they use in order to lower costs, improve integration and streamline IT operations.
At the same time, companies continue to evaluate new solutions. The survey found that 91% of manufacturers are considering adopting new tools to support consolidation efforts and improve interoperability across systems.
The report also highlighted the rising importance of unified communications platforms in modern manufacturing workplaces. Around 42% of employees use these tools regularly, while 66% of respondents said they are essential to day-to-day operations.
Despite this growing reliance, satisfaction remains mixed. Only 45% of respondents said they were satisfied with the performance of their communication tools, while 42% reported experiencing issues such as dropped calls, limited visibility and integration challenges.
Looking ahead, many manufacturers are prioritising stronger data infrastructure to support AI strategies. Nearly three quarters of respondents plan to establish dedicated AI data repository strategies by 2028, while network performance, data movement costs and interoperability were identified as critical factors in scaling AI applications.
The research also found widespread adoption of OpenTelemetry, with 44% of manufacturers already fully implementing the technology and a further 42% in the process of adopting it.
As manufacturers continue their digital transformation efforts, the study suggests that improving data quality, infrastructure and integration will be key to unlocking the full potential of AI-driven IT operations.
