61% Predicting to Achieve AI Goals in Just 11 months, Fluke Reliability Survey Finds
Everyone is in the survey business these days. Fluke Reliability conducted this one and of course capitalized on the Artificial Intelligence (AI) meme. The focus was on our traditional understanding of AI in manufacturing, not on Generative AI that is capturing headlines but not use cases.
Why are business leaders (over 600 senior decision-makers and maintenance professionals in this survey) considering AI? Business growth, addressing the skills gap and need for greater efficiency are driving plans for AI, machine learning, cloud computing and other digital technology adoption.
Censuswide conducted the research, which surveyed over 600 senior decision-makers and maintenance professionals in the U.S., the UK, and Germany. The findings confirm that manufacturers are at the forefront of implementing AI technologies into day-to-day operations.
AI will be a high business priority for companies over the next 12 months according to 93% of survey respondents. This sentiment is echoed at an organizational level, with 9 in 10 senior decision makers agreeing AI is the priority and over 4 in 5 maintenance managers saying the same.
Regarding the role of AI in predictive maintenance, only 8% of those surveyed are currently operating a predictive maintenance strategy. However, a massive 76.5% want to shift to predictive/proactive maintenance in the future, and AI implementation is viewed as a tool to achieve that goal.
Manufacturers are already turning their intentions into action, on average respondents said they intend to invest 44% of their technology budgets on AI in 2024 alone. In fact, (30%) of those surveyed plan to invest 51-75% of their technology budget on AI this year.
While only 9% of manufacturers agree that they have completed their Industry 5.0 goals to date, the majority (61%) expect to achieve their AI goals in just 11 months.
Anticipated benefits include:
- the ability to develop new products and services (35%)
- provide a new way to address data processing and analysis requirements (35%)
- a means to address the call for improvements to customer service (35%)
- the demand for improved efficiency and productivity (34%)
- ways to compensate for the skilled labor shortage (31%).
