What the rise of the forward deployed engineer tells us about how organizations are building capability

The growing demand for forward deployed engineers isn’t about the emergence of a new job title, but a signal that organizations are entering a new phase of AI adoption.

Spend on AI hasn’t yet delivered the benefit that was promised. Forward deployed engineers (FDEs) might be part of the solution.

FDEs are emerging as one of the fastest-growing roles in tech, sitting between business needs, human knowledge, and technical delivery, and helping organizations solve the right problems instead of simply deploying more technology.

The market signal is clear: you can’t hire your way to success; you have to train your way to capability.

Principal Solution Consultant Luke Radford argues that this reflects a broader shift away from technology-first thinking. In an age of abundant tools, competitive advantage doesn’t come from building more, but from solving better.

Hyperscalers agree. Organizations including AWS, Microsoft, OpenAI, Anthropic, CGI and Capgemini are all investing in forward deployed engineering capabilities. That's a strong signal that the challenge facing businesses isn’t just access to AI but translating those tools into measurable business value.

So, what are forward deployed engineers?

A forward deployed engineer (FDE) is an emerging role with many definitions, but their common aim is to identify where technology can create business value. They’re part engineer, part consultant, and part translator. FDEs are trained to ask deeper questions, challenge assumptions, and bridge the gap between human and technical systems.

At first glance, the title "forward deployed engineer" suggests a highly technical role. In reality, some of the most valuable skills associated with the role aren't technical at all.

They include:

• Discovery and problem definition
• Stakeholder engagement
• Systems thinking
• Business understanding
• Translating between technical and non-technical audiences
• Challenging assumptions

FDEs operating across both human and technical systems. Their job isn’t simply to understand the technology but to understand the people, processes, and organizational realities that determine whether a solution succeeds.

They help organizations move from asking:

"What can this technology do?"

to:

"What problem are we actually trying to solve?"

Fighting the urge to build first and ask questions later

Business leaders want better outcomes. Technical teams know what the technology can do. Yet there’s often a gap between the two. This results in projects that are technically impressive but commercially underwhelming – or solutions that patch the problem without addressing the underlying need.

As Luke argues, the value of a forward deployed engineer isn't measured by how much technology they build, but by how effectively they help organizations solve the right problem. The discipline is less about delivery for delivery's sake and more about achieving meaningful outcomes.

While human nature is to add more, FDEs are counter cultural – they seek to take away and stop before they initiate something new. Fighting the default position isn’t about technical wizardry but developing epistemic humility, the recognition of the limits of your own knowledge. This comes by being deeply curious about the problem at hand and asking questions before potentially wasting time building something that wasn’t necessary in the first place.

Human judgment is becoming more valuable, not less

The emergence of FDEs supports the idea that human knowledge is the antidote to time-wasting tools and processes, directly challenging the narrative that AI will replace the need for human intelligence.

The best FDEs aren't simply engineers. They're translators, investigators, and problem-solvers. They understand that successful deployment depends as much on people and processes as it does on technology. Most importantly, they are excellent at operating in ambiguity, something that’s much harder for AI.

Ambiguity used to be a failure state for leaders to correct. FDEs recognize that ambiguity is its own operating model and learn to navigate within it.

Businesses can skill their way to capability

The rise of the FDE challenges the assumption that organizations must look externally to build AI capability.

In many cases, the foundations already exist within the business.

Technology can be learned but business knowledge and the ability to drive change within an organization is the hard-to-build skill that can take years to build.

Software engineers have deep knowledge of systems, customers, and organizational processes. They're already accustomed to solving problems and working across functions. With the right development pathways, many are well-positioned to evolve their skills into roles that bridge technical delivery and business value.

Organizations that can combine existing institutional knowledge with emerging AI skills are better placed than those that focus solely on external recruitment.

The next competitive advantage

The organizations that thrive in this environment won't be the ones that build the most agents, launch the most pilots, or adopt the latest technology first.

They'll be the ones that develop the capability to translate between business needs, human knowledge, and technical possibility.

As Alvin Toffler said: “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”

Ready to build AI capability across your organization? Explore our AI training courses and develop the skills needed to turn AI investment into measurable business value.