Businesses are hiring AI specialists instead of data engineers - and its a big problem (www.techradar.com)

Recent data indicates a troubling hiring trend in the U.S. tech industry, where businesses are increasingly prioritizing AI specialists over data engineers. This shift, driven by the hype surrounding AI, raises significant concerns as over 80% of AI projects fail due to issues rooted in data quality rather than the AI models themselves. Research shows that many organizations—63%—lack confidence in their data management capabilities, which is critical for successful AI implementation. The disparity is stark, with 111,296 AI/ML job postings compared to only 76,271 for data infrastructure roles, leading to a 46% imbalance that risks project success. This focus on hiring AI talent without a solid foundation in data governance could spell disaster for many companies. For instance, firms in less tech-mature areas are especially at risk, as they appear to chase AI opportunities without considering the necessary data infrastructure needed to support them. With AI specialists earning an average of $15,000 more than data engineers, organizations are incentivizing the wrong roles, potentially leading to the abandonment of AI projects as early as 2026 without appropriate data management practices in place. Successful AI adoption will require a shift in understanding that prioritizing data quality and governance is as critical as hiring AI talent.