Build a High-Performance Data & AI Team (2nd Edition)
▼ Summary
– MIT Technology Review Insights surveyed 800 senior data executives and interviewed 15 leaders to assess organizational data performance improvements with generative AI.
– Few data teams are keeping pace with AI, with only 12% rated as “high achievers” in 2025 compared to 13% in 2021, showing little progress.
– Data teams face constraints including talent shortages, difficulties accessing fresh data, tracing lineage, and managing security complexity for AI success.
– AI performance is limited, with just 2% of organizations rating themselves as high achievers in delivering measurable business results through AI.
– Most organizations struggle to scale generative AI, as only 7% have deployed it widely despite two-thirds having some deployment.
A recent global survey of 800 senior data and technology executives, conducted by MIT Technology Review Insights, reveals that organizations are struggling to translate advancements in generative AI into tangible data performance improvements. Despite the rapid evolution of artificial intelligence, most companies find themselves no more effective at executing their data strategies today than they were before generative AI became mainstream.
The study highlights a significant gap between technological potential and organizational reality. A mere 12% of surveyed executives in 2025 classify their organizations as data “high achievers,” showing virtually no progress from the 13% reported back in 2021. This stagnation persists despite growing investments in AI infrastructure. Critical barriers include severe shortages of skilled AI talent, compounded by systemic challenges in accessing current data, maintaining clear data lineage, and managing increasingly complex security protocols, all fundamental requirements for successful AI implementation.
These foundational data struggles directly impact AI performance across the board. The research identifies an even more pronounced capability gap when focusing specifically on artificial intelligence outcomes. Only 2% of respondents give their organizations high marks for delivering measurable business results through AI initiatives. While approximately two-thirds of organizations have begun deploying generative AI in some capacity, a mere 7% have achieved widespread implementation. This indicates that most companies remain stuck in experimental phases, unable to scale their generative AI projects beyond limited pilot programs.
The comprehensive report, available for download, provides detailed analysis and recommendations for building data and AI teams capable of overcoming these challenges. Through additional in-depth interviews with fifteen technology and business leaders, the research identifies patterns among organizations that successfully bridge the gap between AI ambition and operational reality.
(Source: Technology Review)
