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    Redefining data engineering in the age of AI

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    Redefining data engineering in the age of AI
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    As their affect grows, so do the challenges data engineers face. A serious one is coping with larger complexity, as extra superior AI fashions elevate the significance of managing unstructured data and real-time pipelines. Another problem is managing increasing workloads; data engineers are being requested to do extra immediately than ever earlier than, and that’s not prone to change.

    Key findings from the report embrace the following:

    • Data engineers are integral to the enterprise. This is the view of 72% of the surveyed know-how leaders—and 86% of these in the survey’s greatest organizations, the place AI maturity is biggest. It is a view held particularly strongly amongst executives in monetary providers and manufacturing corporations.
    • AI is altering the whole lot data engineers do. The share of time data engineers spend every day on AI initiatives has almost doubled in the previous two years, from a median of 19% in 2023 to 37% in 2025, in line with our survey. Respondents count on this determine to proceed rising to a median of 61% in two years’ time. This can be contributing to greater data engineer workloads; most respondents (77%) see these rising more and more heavy.

    Download the report.

    This content material was produced by Insights, the customized content material arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial employees.

    This content material was researched, designed, and written by human writers, editors, analysts, and illustrators. This consists of the writing of surveys and assortment of data for surveys. AI instruments which will have been used had been restricted to secondary manufacturing processes that handed thorough human evaluation.

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