Transform Complexity into Opportunity with Digital Engineering
IEEE Spectrum - AI
Jun 30, 2025 12:00
Mike Spector
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airesearchieeetechnology
Summary
Digital engineering has evolved from simply digitizing physical designs to leveraging vast, complex data from across enterprises—including AI datasets and digital twins—to drive actionable insights and innovation. This shift enables organizations to transform data complexity into strategic opportunities, highlighting the growing importance of AI in synthesizing information and guiding real-world engineering solutions.
In a literal sense, digital engineering is as old as the first back-of-the-napkin sketch that was shoved in a pocket before being modeled in a computer-aided design program. Those pencil marks became data points, and they were soon joined by millions more as product complexity exploded. We’re now awash in engineering data coming from all corners of the enterprise, as well as from partners, suppliers, and vendors. Product geometries, multiphysics simulations, materials intelligence, market research, digital twins, artificial intelligence datasets, and cyber-physical systems of all kinds contribute to the data deluge. Digital engineering is no longer just about making the physical digital and all the benefits that entails. Today, digital engineering is about making the digital physical — in other words, being able to gather useful insights from all those data points, bring those insights together into a strategy, and turn that strategy into reality. Download this free whitepaper now!