dbt Labs: speed outpacing trust
dbt Labs released a report saying AI-driven acceleration in analytics engineering is outpacing trust and governance, with 72% of data leaders worried about data quality. The report highlights a gap between rapid production of transformations and the slower work of establishing reliable lineage, tests and ownership for critical fields (prnewswire.com).
dbt Labs says analytics teams are using artificial intelligence to ship code faster than they can make the data trustworthy. (prnewswire.com) The company released its fourth annual State of Analytics Engineering Report on April 14, 2026, and said 72% of respondents now prioritize artificial intelligence-assisted coding in development workflows. Only 24% said they prioritize artificial intelligence-assisted pipeline management, including testing and observability. (prnewswire.com) Analytics engineering is the work of turning raw warehouse data into cleaned, documented tables that business teams can query. dbt Labs, founded in 2016, sells software for those transformations and says its platform is aimed at “AI-ready structured data.” (getdbt.com, prnewswire.com) The report says trust in data and data teams jumped to 83% as an organizational priority in 2026, up from 66% a year earlier. Speed also rose, to 71% from 50%, suggesting companies are trying to push both goals at once. (prnewswire.com) That tension shows up in the failure cases. dbt Labs said 71% of data professionals named incorrect or hallucinated outputs reaching stakeholders as a top concern as autonomous agents start operating on company data at larger scale. (prnewswire.com) The plumbing behind trust is slower work: tests that catch bad records, lineage maps that show where a metric came from, and ownership rules that assign a person or team to a critical field. dbt’s own materials pitch metadata, cataloging, and lineage as the way to strengthen governance and trusted data. (getdbt.com, metaplane.dev) The cost side is moving too. dbt Labs said 57% of respondents reported higher warehouse and compute spending, while only 36% reported increased team budgets. (prnewswire.com) This is the second straight year dbt Labs has framed data quality as the bottleneck for artificial intelligence work. In its 2025 State of Analytics Engineering report, the company said poor data quality was still the challenge reported most often and that artificial intelligence tooling was the biggest recent investment area for data teams. (getdbt.com, getdbt.com) dbt Labs is turning this year’s report into a product and marketing push. The company has scheduled a 2026 State of Analytics Engineering virtual event for April 29 and April 30, with speakers from dbt Labs, Hex, and Ramp. (getdbt.com, uktechnews.co.uk) The report’s core message is narrow and practical: companies can use artificial intelligence to write more transformations, but they still need tests, lineage, and named owners before executives can trust the numbers. (prnewswire.com, getdbt.com)