KPMG FDE Uses AI to Accelerate Client Project Delivery

KPMG is redefining enterprise software delivery through its forward-deployed engineer model, leveraging artificial intelligence to accelerate client outcomes and transfer technical expertise directly into business operations. Justin Johnsen, lead technical architect and a forward-deployed engineer at KPMG, has been instrumental in executing this shift. After six years with the firm as a traditional software engineer and architect, Johnsen now operates alongside client teams to navigate complex business requirements and implement AI-driven solutions. The forward-deployed model departs from conventional systems integration by embedding engineers directly into the client workflow. Rather than executing a linear requirements-to-delivery handoff, engineers co-develop applications, provide real-time training, and ensure teams can independently maintain and scale solutions. AI has fundamentally altered the development bottleneck. While coding speed is no longer the primary constraint, gathering precise context and refining project intent before implementation remains critical. This shift allows engineers to concentrate on high-level problem definition and strategic decision-making rather than repetitive coding tasks. In practice, this approach has dramatically compressed delivery timelines. Johnsen recently integrated a suite of client applications that required months of traditional requirement gathering, yet AI enabled full deployment within a single month. The accelerated pace and transparent methodology prompted the client to request formal training on AI prompting and workflow integration, highlighting the dual role of the model in both solution delivery and capability building. Similarly, for a risk assessment platform, his team aggregated disparate data signals from legacy and cloud environments, deployed AI to reason across the datasets, and generated actionable scoring metrics for independent review. Industry observations from these deployments indicate a broader trajectory: enterprise software development is increasingly focused on data aggregation, system integration, and AI-driven reasoning rather than front-end development. The primary challenge for modern enterprises lies in unifying fragmented data and enabling AI to derive visibility and value across hybrid infrastructure. On-site collaboration remains a strategic advantage, fostering organic communication and enabling engineers to capture contextual cues that are often lost in remote meetings. By merging technical execution with continuous coaching, KPMG ensures clients receive not only functional software but also the documentation and AI proficiency required for long-term operational resilience. As artificial intelligence handles increasingly complex data synthesis, the forward-deployed engineer is evolving into a strategic partner who bridges technological capability with enterprise decision-making.