Legal Services

As part of its digital transformation initiative, a client in the oil and gas industry aimed to enhance clarity and efficiency in its engineering processes. The client faced significant challenges due to a library of over 750 documents, each containing more than 100 requirements and extensive cross-references. Traditional methods for managing these documents were labor-intensive and prone to errors, leading to inefficiencies in project execution. The client sought to streamline its processes, improve predictability, and enhance the accuracy of its engineering requirements catalog, with a vision to process this large volume of content in less than a month. To address these issues, the client engaged Ernst & Young LLP to explore potential solutions. The EY team proposed an AI-based solution to automate the rewriting and tagging of engineering requirements, which would allow the client to leverage industry standards and improve access for engineering, procurement, and construction teams. The initial phase involved rationalizing the engineering requirements against industry standards and rewriting them based on technical standards from the International Council on Systems Engineering (INCOSE) and the Easy Approach to Requirements Syntax (EARS). This effort aimed to create a more cohesive and user-friendly digitalized requirements library. The EY team developed a proof-of-concept (POC) application within the secure EY Fabric environment, utilizing Generative AI technology to create rewrite and metadata application agents. This POC demonstrated the model's ability to accurately tag and rewrite documents, which helped build the client's confidence in the AI solution. The implementation of the AI-based solution yielded significant outcomes, with throughput increasing from processing four to five documents monthly to handling 750 engineering documents within just three weeks. This transformation resulted in expected savings of over 90% compared to previous manual efforts. The project not only improved the client's document management process but also unlocked the ability to preprocess content for subject-matter experts, increasing team throughput by 20%, which translated to productivity savings of up to US$5 million. The client is now leveraging these savings for other value-added tasks in engineering transformation. Additionally, the development of a technical capability for document ingestion and metadata tag generation can be applied to other critical areas, such as contracting and safety practices, positioning the client for future innovations.

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