Data Engineers Drive AI Success in Core Operations

As organizations increasingly integrate AI into their core operations, data engineers are emerging as crucial enablers of AI success. Their role in managing large, reliable, and high-quality data is essential for effective AI implementation. A recent report by MIT Technology Review Insights highlights the growing influence of data engineers, who are now spending a significant portion of their time on AI-specific activities.

The report, based on a survey of 400 senior data and technology executives, reveals that 72% of respondents view data engineers as integral to the business. This sentiment is even stronger in AI-mature organizations, where 86% recognize their importance. Data engineers are particularly valued in financial services and manufacturing, where AI adoption is accelerating.

Evolving Roles of Data Engineers

Traditionally, data engineers focused on managing data pipelines. However, the rise of AI is reshaping their roles. Over the past two years, the time data engineers spend on AI projects has nearly doubled, from 19% in 2023 to 37% in 2025. This trend is expected to continue, with respondents predicting that AI-related work will account for 61% of their time within the next two years.

This shift is driven by the increasing complexity of AI models, which require managing unstructured data and real-time pipelines. As a result, data engineers are grappling with expanding workloads and growing demands on their expertise.

Challenges and Opportunities

While data engineers are becoming more influential, they face significant challenges. The complexity of AI models and the need to manage unstructured data add to their workload. Additionally, the demand for their skills is outpacing the supply, leading to potential talent shortages.

Despite these challenges, data engineers have the opportunity to drive AI innovation. By leveraging their expertise in data management and adapting to AI-specific activities, they can help organizations unlock the full potential of AI.

Conclusion

Data engineers are key to AI success, managing the data that powers AI initiatives and adapting to the evolving demands of AI integration. As AI continues to reshape industries, the role of data engineers will become even more critical, shaping the future of AI in business.