Forward Deployed Engineers Face a Reality Check as Enterprise AI Adoption Stumbles

Enterprise adoption of artificial intelligence remains a thorny challenge, hampered by concerns around data protection, escalating expenses and a scarcity of skilled personnel. In response, technology vendors and professional services firms have mobilized teams of forward deployed engineers—specialists embedded with customers to provide direct technical support. The market's enthusiasm for this approach, however, may be premature.

Gartner's analysis suggests the current push for forward deployed engineer (FDE) interventions will underperform. The research firm forecasts that about 70% of vendor-led AI engineering initiatives will be discontinued by 2028, drawing on data from IT services companies, client work and internal modeling.

Many providers now use 'forward deployed' as a label for implementation, professional services, solution engineering or AI consulting; some thoughtfully, others because it sounds more strategic. Some charge premium fees without the delivery depth, program management, or change management maturity to justify them.

Mukul Saha, Gartner senior director analyst

The financial burden of FDE engagements can be substantial. Gartner estimates that consulting fees for forward deployed engineers alone could reach $200,000 per quarter for each use case. Enterprises that achieve early wins but neglect to build their own internal engineering capabilities risk becoming locked into expensive arrangements that conventional service providers or partner models might deliver more efficiently and with greater predictability.

The supply-demand imbalance underscores the challenge. Approximately 2,000 forward deployed engineers are currently active in the market, according to Saha, yet demand is roughly four times that figure. This gap means the engineering talent required to meet customer needs simply does not exist.

Big promises

As interest in forward deployed engineers intensified, major technology firms announced aggressive expansion plans for their AI engineering operations.

Google Cloud launched a recruitment drive in May, posting 59 distinct job openings for forward deployed engineers across U.S. and international locations. CEO Thomas Kurian promoted the opportunity on LinkedIn, stating, "If you are a builder who wants to work on the world's largest stages and be at the center of the agentic era — join us."

AWS committed $1 billion in June to establish a dedicated forward deployed engineer unit. Microsoft allocated $2.5 billion in July to launch an AI deployment division, pledging to deploy 6,000 engineers to assist customers in operationalizing artificial intelligence.

The enthusiasm spread to the consulting channel. Accenture announced in early September that it would expand its Google Cloud-focused Gemini Business Group by recruiting 1,000 AI deployment specialists. Managed service provider Lemongrass highlighted forward deployed engineers as a new offering within its SAP ERP migration services in August.

Some vendor pledges may prove aspirational rather than achievable. DXC Technology announced in June a partnership with Anthropic to prepare tens of thousands of Claude-certified forward deployed engineers. By July 31, however, DXC had only 86 such engineers operational and was serving 57 customer environments, according to CEO Raul Fernandez during an investor earnings call.

Gartner acknowledges that forward deployed engineer models can deliver positive results when properly structured and managed. "If you truly have the right FDE model, we see it bringing good outcomes," Saha explained. "But the type of resources you're going to need to get this sort of engagement done are very particular, high-caliber resources."

Palantir, widely recognized as the originator of the forward deployed engineer framework, has demonstrated the model's effectiveness in practice. Saha noted that Palantir's success stems from work with prominent government clients requiring top-tier resources to complete complex projects on tight timelines, a formula the industry is now attempting to replicate across commercial sectors.

Channel inroads

Forward deployed engineer capabilities bear considerable overlap with traditional partner-led consulting, systems integration and managed services. While channel partners should monitor developments in this space, the shift toward forward deployed engineers is unlikely to fundamentally reshape the AI implementation services market, according to Saha.

If you're a product vendor, you don't want a large team of consultants sitting on the bench bleeding money. You also don't want to burn the bridges with the partners who know the customer contacts and have those existing relationships. You're better off educating and training your partners to help them become better at AI deployment.

Mukul Saha, Gartner senior director analyst

Anthropic and OpenAI both engaged partners for AI enablement support in the first half of the year, while the three major cloud providers have maintained their commitment to channel partnerships. Microsoft introduced the Frontier Transformation Engineer credential in July as part of a broader effort to equip partners with forward deployed engineer competencies.

Leading AI vendors are developing standardized certifications for forward deployed engineers, Saha noted.

The managed service provider channel appears particularly well positioned to bring deployment expertise to mid-market enterprises seeking to capitalize on AI transformation opportunities. Craig Donovan, chief operating officer of technology marketplace Pax8, told Channel Dive, "The MSP channel will be the forward deployed engineers for small and midsize businesses." Pax8 is leveraging forward deployed engineers to help its MSP partners establish AI practices they can then offer to their own customers.

We're just going to offer up some of our own forward deployed engineers that will wear the shirt, if you will, of the MSP until they're ready to step into that space. It's just a helping hand that helps our partners activate a little bit faster.

Craig Donovan, COO of Pax8

Demonstrating return on AI investments requires deliberate action, Saha emphasized. "Product companies want to make their product sticky," he said. "They want to be able to show good numbers to Wall Street investors. The honeymoon period after a contract is signed is not that long. You want to go in there, get the work done and showcase the value right away because competition is fierce."