Who really needs Forward Deployed Engineers around AI?

Forward Deployed Engineers (FDEs) are increasingly being invested in by companies such as AWS, OpenAI, and Microsoft. These engineers are embedded with customers to work across multiple teams, identifying high-value workflows, understanding data and operational constraints, and building integrations to take the system from prototype into production.

In the case of AI deployment, this involves evaluating accuracy, reliability, confidence thresholds, guardrails, review and escalation processes, security, and observability. FDEs are needed because companies want to deploy probabilistic systems into deterministic operating environments, where enterprises want systems to respond within business processes that depend on predictable and uniform results.

However, FDEs should not just stop at successful projects but also convert what they learned into reusable capabilities, making the product better and reducing dependence on specific FDEs in future deployments. The growth of the FDE role indicates a market opportunity and shows that enterprises want AI solutions, but also serves as a warning sign of category immaturity.

Enterprises should focus on measures such as time to production, sustained adoption, measurable business value, customer self-sufficiency, and the creation of reusable product capabilities, rather than just the number of FDEs hired or proofs of concept completed.