Artificial intelligence and machine learning technology is steadily becoming more prevalent in enterprises around the globe, but its adoption rate in 2020 varied widely between regions, according to a survey conducted by 451 Research, a unit of S&P Global Market Intelligence.
As businesses rushed to bolster their digital infrastructure to support remote workers and keep operations running efficiently during the COVID-19 pandemic, many began to see AI’s potential for producing large-scale data analytics, insights and automation.
More than 95% of enterprises surveyed for 451’s new “Voice of the Enterprise: AI & Machine Learning Use Cases 2021” report consider AI technology to be important to their digital transformation efforts. Further, 65% of enterprises with AI in production consider these initiatives “very important” to their digital transformation efforts.
“Digital transformation is a theme within enterprises now because of COVID,” said Nick Patience, lead analyst for AI and machine learning for 451 Research and an author on the survey report. The technology is beginning to take off now as a majority of companies are looking to tap AI for increasingly specific future projects, though AI remains in an experimental phase for many. The percentage of global enterprises that have machine learning initiatives either in production or at a proof-of-concept stage grew to 59% in 451’s 2021 survey, compared to 57% in 2020.
Adoption is more widespread in the U.S., however. While COVID-19 accelerated the progress of AI initiatives in the U.S., with adoption status climbing about 9 percentage points year over year. While some U.S. companies (28%) did slow the rollout of their AI initiatives in response to the pandemic, a larger amount of those outside the U.S. (40%) did so.
“The U.S. has always been an early adopter in every tech case, mostly due to the large economy and then large companies with large budgets,” Patience said. “The pandemic was more of an accelerant for some of these companies, which wasn’t necessarily the case overseas.”
Still, Patience noted some AI activity in western Europe, including Germany, where the manufacturing sector’s use of AI is above the levels of other countries. The U.K., meanwhile, boasts the highest venture capitalist-investment in AI, which may change gradually due to Brexit, Patience said.
Developing applications using cloud-based AI and machine learning services remains the top strategy for deploying the tech at most enterprises, with more than 45% indicating that they use cloud-based services to develop their machine learning applications, though other approaches are growing in popularity as well.
“The beauty of cloud-based AI platforms is that they allow enterprises to get their operations up and running very quickly and easily,” Patience said.
The top three benefits enterprises expect to realize from investing in AI, according to the survey, include lowering costs (32%), increasing sales (31%) and improving workforce productivity (31%). Improving business agility is another widely expected benefit, particularly in the financial services sector (37%).
Meanwhile, 27% of enterprises cited a shortage of cloud architects as a limiting factor in their machine-learning efforts. Machine-learning engineers (25%) and software engineers (25%) are the second- and third-most identified areas of skills shortages, respectively.
Data scientists also remain in short supply, but the fact that they are no longer the lead hindrance listed in the missing skills category of the survey speaks to growth in the AI industry, Patience said.
“This data point tells us that AI is not yet truly mainstream, but its certainly moving that way,” he added.