While there is high enthusiasm for AI — with 92% of those surveyed in the manufacturing industry confirming AI is a top C-Suite priority and 92% agree it provides a competitive advantage — only 32% of manufacturers are fully prepared to implement AI projects now, 5% lower than the overall industry average, according to Manufacturing sector results of the Riverbed Global AI & Digital Experience Survey.
Source: Kaizen
They recognize there are a number of challenges ranging from data quality to scalability which are impacting their ability to realize the full potential of AI technology. As AI continues to advance, manufacturers can achieve significant benefits including increased efficiency and productivity, improvements in product quality, optimizing inventory levels and production processes, and applying proactive data-driven decision making, all to collectively enhance and deliver a superior customer experience.
The next three years are anticipated to be a period of rapid expansion as enterprises seek practical AI approaches and solutions. By 2027, 83% of manufacturing leaders expect their organization to be fully prepared to implement their AI strategy and projects. During the same time period, AI is expected to mature and become a growth driver. Whereas today, 58% of leaders across manufacturing say the primary reason for using AI is to drive operational efficiencies over growth (42%), those numbers flip in 2027, with 65% of organizations saying AI will primarily be a growth driver versus driving efficiencies (35%). This sizable shift is one of the largest across all the industry sectors participating in the study.
Manufacturing leaders surveyed also said they expect to see many benefits through the use of AIOps, as 89% of manufacturers agree that AI automation is important to improve IT efficiency and deliver a superior digital experience for end users. Manufacturing leaders were asked to rank how they expect to use AI in their IT operations to improve Digital Employee Experience (DEX) within the next three years and the results revealed:
- Workflow automation (80%)
- Automated remediation (69%)
- 24/7 support availability such as chatbots (63%)
- Data-driven insights (60%)
- Anomaly detection (59%)
While there is widespread enthusiasm for AI, the research identified three major gaps that organizations must overcome to realize the desired benefits and achieve business success. As with other industries, manufacturers must overcome the reality gap, the readiness gap, and the data gap in order to maximize the value of their AI investments.
Reality Gap: Manufacturers are confident about their AI adoption for IT services and digital experience, with 77% 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.
Readiness Gap: As stated earlier, there's a readiness gap as only 32% of manufacturing leaders say their organization is fully prepared to implement AI projects today. This group is behind all other sectors (except the public sector) in terms of AI preparation. Additionally, 67% say with AI still maturing, it's challenging to implement AI that works and scales.
Data Gap: Nearly all leaders in the manufacturing sector (87%) acknowledge that great data is critical for great AI. However, 69% are concerned about the effectiveness of their organization's data for AI usage, and only 42% rated their data as excellent for completeness and accuracy. It's notable too that 42% say their data quality is a barrier to further AI investment.
There are also growing concerns in the sector about data confidentiality and security risks, with 92% concerned that AI will access their organization's proprietary data in the public domain due to use of AI. The manufacturing industry is especially vulnerable to data breaches due to its widespread reliance on legacy systems, so cybersecurity is a concern for this sector.
Manufacturing organizations are implementing strategies to overcome AI challenges and achieve tangible results. To address AI preparedness, 57% of manufacturers have formed dedicated AI teams, and 42% observability and/or user experience teams.
Manufacturers are exploring other initiatives to drive successful AI integration. When it comes to data, the vast majority of manufacturing leaders (84%) say using real data, rather than synthetic data, is crucial in AI efforts to improve the digital experience.
Additionally, 83% of respondents agree that observability across all elements of IT is important in an AIOps strategy, and at least 81% say observability to overcome network blind spots—including public cloud, remote work environments, Zero Trust architectures, and enterprise-owned mobile devices—is either extremely or moderately important.
Methodology: The Riverbed Global AI & Digital Experience Survey polled 1,200 IT, business, and public sector decision-makers across seven countries, all with over $250 million in annual revenue (over $500 million in the US, UK, and France). Industries included manufacturing, financial services, retail, government/public sector, healthcare providers, energy and utilities, and transport and airlines. A total of 200 decision makers were surveyed in the Manufacturing industry. The survey was conducted by Coleman Parkes Research in June 2024.
