Manufacturing Sector Faces AI Challenges, but Rapid Adoption Expected by 2027

Riverbed has released the findings of its Riverbed Global AI & Digital Experience Survey, focusing on the manufacturing sector. The survey reveals that while 92% of manufacturers view AI as a top priority for the C-suite and agree it provides a competitive advantage, only 32% are fully prepared to implement AI projects, 5% lower than the overall industry average. The study highlights several challenges that manufacturers face, including issues with data quality and scalability, which hinder their ability to maximize AI’s potential. However, AI offers numerous benefits, including increased efficiency, productivity, improved product quality, optimized inventory management, and enhanced data-driven decision-making, all of which contribute to a better customer experience.

Looking ahead, manufacturers are expected to experience rapid AI adoption over the next three years. By 2027, 83% of manufacturing leaders anticipate their organizations will be fully prepared to implement AI strategies and projects. This shift marks a significant change, with AI moving from being seen primarily as a tool for operational efficiency to becoming a major driver of growth. Currently, 58% of manufacturing leaders focus on AI for operational efficiencies, while by 2027, 65% expect AI to primarily fuel growth, making this one of the most notable shifts across industries.

The survey also found that Millennials and Gen Z are seen as the most comfortable with AI in the workplace, with 45% of manufacturing leaders viewing each generation as proficient in AI technology. The strong support for AI across all generations reflects a widespread enthusiasm for AI adoption within the sector. In fact, 97% of manufacturers believe AI will help them deliver a better digital experience for their end users, and 62% report a positive sentiment toward AI in their organization.

As AI adoption accelerates, 56% of manufacturers are investing in AI infrastructure and talent to drive their AI strategies forward, while 29% have already fully integrated AI into their operations. AI automation is particularly seen as a critical tool for improving IT efficiency and enhancing the digital employee experience. The most common AI use cases expected to improve IT operations include workflow automation (80%), automated remediation (69%), 24/7 support (63%), data-driven insights (60%), and anomaly detection (59%).

Despite the optimism surrounding AI, the survey identifies key barriers to broader adoption in the manufacturing sector. These include the reality gap, readiness gap, and data gap. While 77% of manufacturers claim to be ahead of their peers in AI adoption, this perception does not always align with reality. Only 32% of manufacturers feel fully prepared to implement AI projects, with 67% citing challenges in scaling AI solutions. Additionally, 87% of manufacturing leaders acknowledge that quality data is essential for successful AI implementation, yet 69% express concerns about their data’s effectiveness, with 42% rating their data quality as a barrier to further AI investment.

Cybersecurity also remains a significant concern, with 92% of manufacturers worried that AI could expose proprietary data to the public domain, especially given the sector’s reliance on legacy systems. Addressing these concerns and overcoming data challenges will be critical for manufacturers to fully realize the potential of AI.

Salman Ali, Senior Manager – Solution Engineering at Riverbed, commented, “To achieve substantial performance improvements and unlock the full benefits of AI, manufacturers must focus on enhancing data quality. Riverbed’s open, AI-powered observability platform helps overcome these data challenges by enabling organizations to scale and automate their AI initiatives, driving efficiencies across IT operations and delivering measurable ROI.”

Manufacturers are taking proactive steps to overcome AI challenges, with 57% forming dedicated AI teams and 42% focusing on observability or user experience teams. Additionally, 84% of manufacturing leaders agree that using real data, rather than synthetic data, is essential for improving the digital experience, and 83% emphasize the importance of observability across all IT elements in an AIOps strategy.

As AI continues to transform manufacturing operations, the sector is poised for significant growth, with organizations focusing on overcoming key barriers and harnessing AI’s full potential to drive innovation and improve business outcomes.