NEI engineers presented this paper at the 2026 IEEE Rural Electric Power Conference (REPC), introducing a framework for evaluating where AI can effectively support engineering knowledge work.
The paper received a 2nd Place Paper Award, recognizing it as one of the top papers at the conference.
Authors
Jasmine Badiee Konrad, PhD
Jake Wiggins, PE
Abstract
Power systems engineering firms are facing pressure to meet accelerated timelines without compromising technical quality. At the same time, the rapid emergence of large language models (LLMs) has prompted a surge of AI-based solutions aimed at relieving these operational demands. In engineering knowledge work, rapid adoption of such tools has occurred largely in the absence of structured frameworks for identifying appropriate use cases, resulting in inconsistent and sometimes ineffective deployment. This paper introduces a methodology for determining contexts in which AI tools can genuinely enhance engineering knowledge work, offering a practice-oriented solution tailored to the power systems engineering domain. The methodology serves as guidance for integrating AI tools in ways that complement engineering expertise to augment design processes, knowledge sharing, and technical workflows. The framework is expected to augment design reasoning, accelerate decision support, and standardize repetitive tasks.
Download the paper (accepted manuscript)
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Note: This is the accepted manuscript version. The final published version is available through IEEE.