To gauge the overall maturity of AI, the survey sought to uncover challenges respondents faced when evaluating solutions. While in last year’s survey respondents cited company culture (22%) as the major bottleneck to AI adoption, lack of skilled people and difficulty hiring topped the list this year, noted by 19% of respondents. This shift is significant, as it implies a greater overall acceptance of AI, but it also reveals the very real and persistent AI talent gap O’Reilly has predicted.
While it’s not surprising that demand for AI expertise has exceeded supply, it’s important to understand which specific skills and professional titles are most critical to AI adoption. Companies feel the skills shortage most acutely in the areas of ML modeling and data science (52%), understanding business use cases (49%), and data engineering (42%). The survey also found that the percentage of companies with AI products in production over the last year (25%) is flat when compared with 2020 (26%) and 2019 (27%), which may be reflective of the AI skills gap.
Other key findings include:
“Enterprise AI has grown; the sheer number of survey respondents will tell you that, but deployment of AI applications into production has remained roughly constant, and with it, overall maturity in the field,” said Mike Loukides, vice president of content strategy at O’Reilly and the report’s author. "It’s no surprise that the demand for AI expertise has exceeded the supply—that's been predicted for years—but it’s important to realise that it’s now become the biggest bar to wider adoption."