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    Redefining data engineering in the age of AI

    ProfitlyAIBy ProfitlyAIOctober 23, 2025No Comments2 Mins Read
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    As their affect grows, so do the challenges knowledge engineers face. A significant one is coping with better complexity, as extra superior AI fashions elevate the significance of managing unstructured knowledge and real-time pipelines. One other problem is managing increasing workloads; knowledge engineers are being requested to do extra at the moment than ever earlier than, and that’s not more likely to change.

    Key findings from the report embody the next:

    • Knowledge engineers are integral to the enterprise. That is the view of 72% of the surveyed know-how leaders—and 86% of these within the survey’s largest organizations, the place AI maturity is best. It’s a view held particularly strongly amongst executives in monetary providers and manufacturing firms.
    • AI is altering every thing knowledge engineers do. The share of time knowledge engineers spend every day on AI initiatives has practically doubled up to now two years, from a median of 19% in 2023 to 37% in 2025, in response to our survey. Respondents anticipate this determine to proceed rising to a median of 61% in two years’ time. That is additionally contributing to greater knowledge 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 Expertise Assessment. It was not written by MIT Expertise Assessment’s editorial employees.

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



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