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Redefining Data Engineering for the AI Era

by Rachel Kim – Technology Editor

Data ⁤Engineers at the⁣ Forefront of AI ‍Revolution, Workloads Surge: New Report

CAMBRIDGE, MA ⁤- A new report reveals data ​engineers are increasingly ⁢critical ‍to business success adn are dedicating a rapidly growing portion of their time to artificial intelligence⁢ projects, even as their‍ overall workloads intensify. The findings, released today, ‌underscore a fundamental shift in the role of data ​engineering as organizations lean further into AI-driven strategies.

According to ⁤the study,‌ 72% of technology leaders now view data engineers ⁤as ​integral to ⁣their businesses, a sentiment⁢ rising to 86% within the largest organizations-those with the highest levels of AI maturity. This importance is notably pronounced in the financial services and manufacturing sectors. The evolving landscape is driving a significant increase in time spent on​ AI initiatives, nearly ‌doubling⁤ from an average of 19% of a data ⁣engineer’s day in 2023 to 37% in 2025. Experts predict this trend will⁤ accelerate, reaching 61% within the next two years.

The‍ report highlights⁢ the growing complexity of data management, particularly with the rise of unstructured data and the demand for real-time data pipelines to ⁣support advanced AI models. Consequently, 77% of ⁣respondents anticipate⁤ continued growth in data engineer workloads.

The ⁤full report is available for download⁢ here.

This content was produced by insights, the custom content arm of ​MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, ‍designed, and written by human writers,⁢ editors, analysts, and illustrators. This includes the writing of surveys and‌ collection of data for surveys.AI tools that may have been⁣ used were limited⁢ to secondary production processes that passed thorough human review.

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