As a wide range of manufacturers begin to incorporate AI into their daily operations, companies developing artificial intelligence products and support appear poised to benefit.
Joint research with Microsoft (NASDAQ:MSFT) and MIT Technology Review Insights found the following 35%. Manufacturers surveyed have already commercialized AI use cases. Meanwhile, the majority (64%) are currently researching or experimenting with AI.
“Many executives surveyed indicated their intention to significantly increase spending on AI over the next two years,” the study said. “Companies that have not yet implemented AI in production are gradually doing so.”
The study sample consisted of 300 senior executives from around the world working in organizations with annual revenue of $100 million or more.
Approximately 60% of executives surveyed expect spending on AI in engineering and design to increase by 10% or more. A further 43% plan to spend the same amount on factory operations.
Large enterprises are moving faster to integrate AI
Most major manufacturers plan to integrate AI into their operations at some point, but the largest manufacturers are making the most progress.
Aerospace, automotive, and electronics manufacturers are most likely to already have use cases in production.
Almost 80% of surveyed companies with annual revenue of $10 billion or more have already implemented AI use cases. For companies with revenues of $1 billion to $10 billion, this number drops to 38%. It has since largely disappeared, with 2% to 4% of companies with revenues between $100 million and $999 million implementing use cases.
However, even the majority of small and medium-sized enterprises surveyed are still conducting some form of AI research and experimentation.
“Everyone in manufacturing is excited about AI,” said Philippe Lambach, chief AI officer at Schneider Electric. “However, relatively few companies are leveraging AI at scale to transform the way they work.”
Small businesses say a lack of talent and skills is holding back progress in AI. The cost of maintaining and improving AI models is also an issue for manufacturers on tight budgets.
Ben Armstrong, executive director of the Massachusetts Institute of Technology's Center for Industrial Performance, said: “While we are seeing limited-impact use of AI among some producers, there is little evidence of AI-driven transformation.” Stated. “Few manufacturers are extending the use of AI technology beyond the front office and into production operations.”
Product design tops AI use cases
So far, the main AI use cases by manufacturers are product design, content creation, and chatbots.
“Design is increasingly being done in simulated environments, which can significantly reduce cycle times,” said Indranil Sircar, chief technology officer of manufacturing solutions at Microsoft. Ta. “Design engineering is becoming more data-centric, and AI is enabling that through simulation.”
Manufacturers have also devoted resources to developing AI technology to improve productivity and efficiency.
How to handle huge amounts of data?
The study found that data is the most difficult challenge in scaling AI for most manufacturers, as this industry generates more data than any other industry. And much of that data is currently not suitable for AI models.
To address this, 57% of respondents said they are making their machines more connected. Additionally, the same percentage of respondents said data quality is the most difficult challenge when integrating AI into operations.
“AI requires a certain level of data maturity,” the study states. “Before bringing an AI use case into production, determine how well your organization is collecting, storing, and processing data and take concrete steps to remediate weaknesses.”