The rapid increase in AI adoption — and the uphill battle of deployment across workflows that comes with it — has led to the rise of a new forward deployed engineering model to support enterprises as they scale the technology.
The approach of embedding specialized talent to speed up enterprise adoption is quickly expanding amid heightened complexity. By the end of 2026, more than 85% of tech providers will have launched FDE programs as the core method for delivering AI and condensing deployment timelines, according to Alex Coqueiro, senior director analyst at Gartner.
FDEs help vendors maximize the product’s value within enterprises that don’t always have the skills readily available to scale AI, he added.
Palantir is credited with originating the forward deployed engineering model, but other tech providers quickly followed suit. Microsoft said earlier this month that it will pour $2.5 billion into the Microsoft Frontier Company, which will add 6,000 engineering experts to customer operations, with companies like Land O’Lakes and Unilever already tapping into the service.
AWS also shared in July that it is spending $1 billion on its own forward deployed engineering hub to help roll out AI systems within enterprises, while Google began looking to fill forward deployed engineering roles within an AI-focused go-to-market unit.
“AI is not just one more technology. It will actually change the way people work.”
Alex Coqueiro
Senior Director Analyst, Gartner
Frontier model providers OpenAI and Anthropic, as well as service providers like Accenture and Deloitte, are also investing in hiring FDEs. IT teams are facing increasing pressure from CEOs and boards on AI investments, with much higher speed to deployment expectations and demand to show returns. In turn, it’s pushing service providers to help enterprises navigate the shift, said Jennifer Hamel, research VP of enterprise data and AI services at IDC.
“We’re moving beyond this period of experimentation,” Hamel told CIO Dive. The focus for IT leaders now is prioritizing AI products that drive business value, she added.
The FDE model, in theory, is not AI-specific, Coqueiro said. But it is largely driven by the technology’s rapid growth and its effects on the workforce and business operations as it’s embedded in “every single process.”
“Why it became a fact in enterprises today is because many organizations, especially enterprises, realize AI is not just one more technology,” he said. “It will actually change the way people work. Because there’s a lot of experimentation, many of those new ways of work, sometimes there’s no prescription guidance on that.”
While hyperscalers build out their forward deployed engineering programs, there is a more nascent effort among enterprises to develop their own talent internally, Coqueiro said. Yet FDEs provided by tech providers tend to be more popular, he added.
Enterprise use of FDEs
The forward deployed engineering model is one that Travelers Insurance is tapping into both internally and through external partners, said Mojgan Lefebvre, EVP and chief technology and operations officer at Travelers.
The insurance firm’s operating model is composed of product-centric, cross-functional teams that include engineers, product managers and business leaders — a model that’s been core to building and delivering AI capabilities throughout the organization, Lefebvre told CIO Dive.
An enterprise AI team with deep technical experts operates at the center, with engineers deployed into the cross-functional teams to help address business problems and pass on AI expertise. The goal over time is that “everybody is an AI engineer,” she said.
“For the cross-functional agile teams who are solving specific business problems, we want to make sure they all have AI expertise and, by embedding these folks for a period of time within them, we give them that expertise,” Lefebvre said. “Then they go back to their central team where, if they have built capabilities that are going to be reusable, they bring that back and they embed it in the AI platform we have available for everyone.”
Travelers is also in talks with service providers and technology partners like Databricks and Snowflake when it comes to bringing in expertise and building out agentic workflows, Lefebvre said.
“Some of them talk about having teams of two or three people max with one product manager and a couple of engineers that are building huge capabilities in short amounts of time,” she said. “We’re certainly experimenting a lot with that as well.”
Before pursuing vendor FDEs, Coqueiro issued a word of caution, noting that CIOs will need to be strategic about bringing them into an organization. Seven in ten enterprises will be forced to drop agentic AI projects led by FDE engagements due to lack of internal skills to keep projects going and potentially high costs, according to a Gartner report.
“As an enterprise leader, am I able to keep maintaining those solutions, or will I need to pay a premium fee forever?” Coqueiro said as an example of what CIOs should be asking.
Competition for FDEs strains availability
Forward deployed engineering models across technology vendors and service providers will likely take a while to mature, which is prompting companies like Liberty Mutual to develop internal talent, said Andrew Palmer, EVP and CIO of global retail markets at Liberty Mutual.
Anthropic, for example, has “everyone asking them for help,” Palmer said.
“It’s very hard to compete for that attention,” he told CIO Dive in a June interview.
With enterprises pursuing their own AI engineering talent, and AWS and Microsoft alone looking to hire thousands of FDEs, the amount of available talent is simply not there, Coqueiro said.
The FDE skillset goes beyond the technical, which makes such employees difficult to come by, he said.
“It’s hard to find someone who understands agents properly, it’s hard to put those things into production,” he said. “Imagine someone who can put agents into production and understands the business at the same time.”
Indeed, embedding FDEs isn’t so different from existing consultancy staff augmentation models, IDC’s Hamel said. But the purpose of the FDE role — to serve as the link between the business and having the skills to build readily deployable AI — sets the model apart, she said.
The FDE model is here to stay as AI evolves and continues to get more complex for enterprises to deploy, Coqueiro said. The technology is a game-changer for companies in a lot of ways, which is why enterprises will continue pursuing AI deployment support in the form of FDEs, he added.
