Creative paper boat
Companies developing products and support for AI look set to benefit as a wide range of manufacturers begin to incorporate AI into their day-to-day operations.
A joint study by Microsoft (NASDAQ:MSFT) and MIT Technology Review Insights found 35%. manufacturers interviewed have already put AI use cases into production. While the majority, 64%, are currently researching or experimenting with artificial intelligence.
“Many executives responding to the survey indicate that they plan to significantly increase spending on AI over the next two years,” the study reads. “Those who haven’t started AI in manufacturing are moving in gradually.”
The survey sample consisted of 300 senior executives from around the world working in organizations with annual revenues of $100 million or more.
Nearly 60% of executives surveyed plan to increase AI spending by 10% or more in engineering and design. Another 43% plan to spend the same amount on factory operations.
Larger companies are moving faster to integrate AI
While most major manufacturers plan to integrate AI into their operations at some point, the largest have made the most progress.
It is more likely that aerospace, automotive and electronics manufacturers are already implementing use cases in production.
Nearly 80% of companies surveyed that earn $10 billion or more per year are already implementing AI use cases. This figure drops to 38% for companies with revenues between $1 billion and $10 billion. It then nearly disappears, with 2% to 4% of companies earning $100 million to $999 million implementing use cases.
However, even the majority of smaller companies surveyed are still researching or experimenting with AI in some way.
“Everyone in manufacturing is excited about artificial intelligence,” said Philippe Rambach, chief AI officer at Schneider Electric. “But relatively few are using AI at scale to transform the way they work.”
Smaller companies point to talent and skills shortages that hinder progress with AI. The costs of maintaining and improving AI models also become problematic for manufacturers with tighter budgets.
“While we see low-impact uses of AI among some manufacturers, there is little evidence of an AI-driven transformation,” said Ben Armstrong, executive director of MIT’s Industrial Performance Center. “We have seen few manufacturers extend the use of AI techniques beyond the front office to manufacturing operations.”
Product design comes first in AI use cases
So far, manufacturers’ predominant AI use cases involve product design, content creation, and chatbots.
“Design increasingly occurs in simulated environments, which can significantly reduce cycle times,” said Indranil Sircar, technology lead for manufacturing solutions at Microsoft. “Design engineering is becoming more data-centric, and artificial intelligence is enabling this through simulation.”
Manufacturers have also invested resources in developing artificial intelligence techniques to improve productivity and efficiency.
How to manage colossal data?
The study finds that the toughest challenge for most manufacturers in scaling AI is data, as the industry creates larger quantities than other industries. And much of this data is not currently suitable for AI models.
To solve this problem, 57% of respondents said they are increasing machine connectivity. The same percentage of respondents also said that data quality is the most difficult challenge related to integrating AI into operations.
“AI requires a level of data maturity,” the study reads. “Determine how well the organization collects, stores, and processes data and take concrete steps to fix weaknesses before putting AI use cases into production.”