EY, a global professional services firm, has significantly increased coding productivity by four to five times through the strategic integration of AI agents with its engineering standards. This integration has revolutionized the efficiency of teams working on EY’s suite of audit, tax, and financial platforms.
The key challenge faced by coding agents was the inability to deploy generated code effectively. Stephen Newman, EY Global CTO Engineering Leader, emphasized the importance of generating code that is integratable, compliant, and does not create additional cleanup work in the long run.
The solution involved connecting coding agents to EY’s engineering standards, code repositories, and compliance frameworks. This integration led to substantial productivity gains, but it was not a simple plug-and-play process. EY invested 18 to 24 months in building the necessary cultural foundation and technical integrations to enable semi-autonomous coding at scale.
EY adopted a cultural shift approach by introducing GitHub Copilot-style tools to familiarize engineers with prompt engineering and AI assistance organically. This approach ensured that AI adoption was user-driven rather than imposed from the top.
The success of this initiative hinged on granting agents access to EY’s code repositories and engineering standards, allowing them to generate deployable code efficiently. By evaluating multiple agent platforms, EY selected Factory, which demonstrated tangible value to developers and significantly improved productivity.
Under Newman’s guidance, EY established a workload classification framework to delineate tasks suitable for autonomous agent handling and those requiring human oversight. This restructuring of developer roles to orchestrators directing agents resulted in efficiency gains ranging from 15% to 60% in the early adoption phase.
EY’s journey showcases the potential of integrating AI technologies with established engineering practices, paving the way for enhanced productivity and efficiency in software development.
Source: VentureBeat