How to get stuck AI initiatives back on track with forward deployed engineering

Forward deployed engineers (FDE) are having a moment. Search interest is up 9x year over year, and tech companies are rolling out new FDE offers left and right. Why now? We unpack what it is, how it works, and why AI complexity is turning it into a go-to approach for getting CX initiatives across the finish line.

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What is forward deployed engineering (FDE) anyway?

Besides being a mouthful, FDE is one of the fastest-growing roles in tech. Part platform expert, part business consultant, and part execution lead, FDEs embed alongside internal teams to bridge the gap between powerful technology and the operational realities that get in the way of results. They align to internal priorities, scope the work to be done, and tap into the right professional services resources when needs exceed internal capacity and capabilities.

The model dates back about a decade to Palantir, which began embedding engineers alongside client teams to put new platform investments into practice. It represents a fundamentally different approach to: "Here's your software, call us if you need help."

Now, it’s going mainstream, largely for its unique ability to help solve one foundational problem AI has created.

The problem: AI has turned innovation into a full-time job

For the last few years, CX leaders have been told to adopt AI.

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To their credit, many have. Despite everything else on their plate, CX teams are making real progress with AI. The proof? According to our upcoming research report with CX Dive, 75% are already using AI to support self-service. Another 54% are strengthening agent assist tools, and 53% have integrated AI into their knowledge strategy.

But here's what nobody warned them about: AI doesn't work like the big CX projects that came before it. Platform migrations had a finish line. You planned, you migrated, you went back to business as usual. AI is a never-ending cycle of sprints, each one building on the last and demanding your constant attention.

That's a fundamentally different kind of drain on CX teams. It requires technical, strategic, and project management skills that are constantly evolving. Most organizations don't have all of those pieces in place. And as a result, they eventually get stuck.

How FDE gets your AI initiatives unstuck

An embedded FDE gains context and understanding of your operations and technical environment in a way that traditional external support teams don’t, allowing them to scope work, quickly tag in the right specialized resources, and scale up or down as needs change.

A couple of examples...

• Need a technical resource to integrate a new AI solution with your broader CX stack? Your FDE defines the approach and pulls in the right engineers to execute.
• Need a rollout strategy to drive adoption across the contact center? Your FDE builds the plan and brings in change management to bridge the gap between investment and actual adoption.

The result: AI projects move faster and deliver stronger ROI because someone is dedicated to ensuring their success.

FDE in action: 3 ways to get your AI roadmap back on track

So where do you begin? Here are three smart starting points:

1. Get one AI use case into production fast. Pick something you know you need help executing, like building an AI agent. Use it to uncover constraints and see how FDE helps implement AI on a smaller scale.
2. De-risk your next AI project rollout. Have an AI solution in mind, but not sure it solves your problem? FDE can validate your deployment approach from end-to-end, so you get it right the first time.
3. Sequence an AI roadmap that compounds value. The fastest way to stall AI progress is to build the wrong thing first. FDE helps you prioritize and sequence your roadmap so each phase builds on the last.

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