Can AI truly revolutionise manufacturing efficiency?

Riverbed, a leader in AIOps for Observability, has unveiled the Manufacturing sector findings from its Global AI & Digital Experience Survey

The study highlights strong enthusiasm for AI, with 92% of surveyed manufacturing executives identifying AI as a top C-Suite priority and agreeing it offers a competitive edge. However, only 32% of manufacturers are currently fully prepared to implement AI projects—5% below the overall industry average. Challenges such as data quality and scalability are key hurdles preventing manufacturers from unlocking AI’s full potential. As AI evolves, the industry is poised to benefit from improved efficiency, enhanced product quality, optimised inventory management, and more data-driven decision-making, all of which contribute to a superior customer experience.

The next three years are expected to bring rapid AI expansion as businesses seek practical AI solutions. By 2027, 83% of manufacturing leaders anticipate being fully prepared for AI implementation. AI’s role is also expected to shift significantly, from primarily driving operational efficiencies (58% today) to becoming a key growth driver (65%) by 2027. This shift represents one of the most notable transformations across all industries in the study.

Millennials and Gen Z viewed as AI leaders

As AI reshapes the manufacturing sector, enthusiasm spans the C-Suite, younger employees, and organizations as a whole:

• 97% agree AI will enhance digital experiences for end users.
• 62% say their company’s sentiment toward AI is positive, with 32% neutral and only 6% skeptical.
• While Gen Z is often seen as the AI-savvy generation, manufacturing leaders view Millennials (45%) as equally adept, followed by Gen X (10%).

Most manufacturers have moved beyond the experimental phase, with 56% accelerating AI initiatives by investing in infrastructure and talent. Meanwhile, 29% have reached the transformative stage, where AI is fully integrated into operations.

AI driving workflow automation in manufacturing

Manufacturing leaders foresee AI delivering significant benefits, with 89% recognising AI automation as key to improving IT efficiency and digital experiences. Over the next three years, AI will be used in IT operations for:

• Workflow automation (80%)
• Automated remediation (69%)
• 24/7 support availability via chatbots (63%)
• Data-driven insights (60%)
• Anomaly detection (59%)

Gaps hindering AI adoption in manufacturing

Despite strong AI adoption momentum, the study identified three critical challenges preventing manufacturers from maximising AI’s benefits:

• Reality Gap: While 77% of manufacturers believe they are ahead of peers in AI adoption (including 25% who say they are significantly ahead), only 7% admit to lagging behind. This discrepancy suggests an overestimation of progress.
• Readiness Gap: Only 32% of manufacturing leaders say their company is fully prepared for AI adoption, ranking them behind most other sectors. Additionally, 67% cite AI’s immaturity as a barrier to scalable implementation.
• Data Gap: Although 87% recognize high-quality data as crucial for AI success, 69% are concerned about their data’s effectiveness, and only 42% rate their data as excellent in terms of completeness and accuracy. Furthermore, 42% see poor data quality as a hindrance to further AI investments. 

Addressing AI-related security and confidentiality risks

With 92% of manufacturing leaders concerned that AI could expose proprietary data in the public domain, data security remains a significant issue. The industry’s reliance on legacy systems makes it particularly vulnerable to breaches, reinforcing the need for robust cybersecurity strategies.

Overcoming AI challenges in manufacturing

Salman Ali, senior manager – Solution Engineering, GCC, at Riverbed, explained, “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. However, for manufacturers to deliver substantial performance improvements and improve their AIOps initiatives, they must focus on the quality of their data. Our recent study reveals that 42% of manufacturing leaders are concerned about the effectiveness of their organization’s data for AI purposes. At Riverbed, we’re helping customers in this industry overcome this data challenge with our open, AI-powered observability platform, which provides practical AI that works and scales, enabling organizations to automate and drive efficiencies across their IT operations and achieve significant ROI from their IT investments and AIOps efforts.”