Security News > 2021 > April > Trends in the evaluation and implementation of enterprise AI adoption

While in last year's survey respondents cited company culture as the major bottleneck to enterprise AI adoption, lack of skilled people and difficulty hiring topped the list this year, noted by 19% of respondents.

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.

Key findings of enterprise AI adoption The second-most significant barrier to AI adoption is quality data.

The percentage of respondents reporting mature practices-that is, the ones that had revenue-bearing AI products in production-has stayed roughly the same over the last few years.

Among respondents with mature practices, scikit-learn and TensorFlow were the most used AI tools.

Education has the lowest percentage but the highest number of respondents who are considering AI. "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, VP of content strategy at O'Reilly and the report's author.

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