Technology vendors are investing heavily in forward deployed engineering (FDE) teams, as providers compete to help enterprises challenged with delivering measurable outcomes from their AI implementations.
Amazon recently announced a $1BN investment to create a dedicated Amazon Web Services (AWS) Forward Deployed Engineering organization, while Microsoft has introduced the Microsoft Frontier Company, a new business unit focused on helping enterprises design, deploy and manage AI systems.
Francessca Vasquez, Vice President of Frontier AI Engineering and Services at AWS, wrote in a blog post:
“I have… heard loud and clear that many customers need expert AI engineers working directly with their teams to help them build and become AI-native organizations.”
The organization’s agentic-first approach aims to reduce project timelines “from months to days,” and leave customers self-sufficient when a deployment ends.
Similarly, Microsoft is investing $2.5BN in Microsoft Frontier Company, embedding 6,000 industry and engineering experts at customers to “co-design, co-innovate, deploy and continuously improve AI systems at scale based on measurable business outcomes,” Judson Althoff, CEO at Microsoft Commercial Business, wrote on the Microsoft blog.
Enterprises need to establish an intelligence platform that compounds their proprietary data, expertise, workflows and decision-making processes over time, and a trusted platform that allows them to govern and secure their AI solutions, according to Althoff. “Enterprise AI engineering expertise with deep industry knowledge is required to build a system that acts as a continuous loop of improvement between the two platforms.”
The announcements indicate that enterprise AI vendors are placing greater emphasis on helping customers bring AI into their day-to-day operations, as enterprises increasingly encounter the challenges of moving projects from proof of concept into production.
Enterprise AI Buyers Need More Than Access to Models
While foundation models have become widely available, and AI developers have moved on to frontier models, deploying AI in enterprise environments remains a complex task. Teams must integrate AI with existing systems, prepare proprietary data, establish governance frameworks and meet security and compliance requirements before they can deploy applications.
That implementation challenge is driving demand for FDEs, technical teams that work directly with enterprise customers.
For enterprise buyers, the growing investment suggests vendors increasingly recognize that successful AI adoption depends on deployment expertise as much as model performance.
As John Kim, Co-Founder and CEO of Delight.ai, told CX Today in an interview, enterprise buyers need to evaluate AI vendors not only on model capabilities but also on their ability to guide organizations in their deployments.
“It’s really, really important to understand how a lot of these AI vendors are approaching rolling out into production.”
Organizations should assess whether vendors have established frameworks for evaluating AI readiness, proven processes for preparing enterprise data and the operational experience needed to deploy AI “as quickly and safely as possible,” Kim added.
That will become increasingly important as enterprises begin deploying AI against sensitive business data. As Kim said:
“When you’re dealing with massive amount of very important client customer data, you have to really invest in… the trust environment for adopting AI.”
Enterprise customers are no longer evaluating AI vendors solely on the quality of their models, but also on their ability to implement AI securely, govern it effectively and deliver measurable business outcomes.
Technology Vendors Embrace Embedded Engineering
While AWS and Microsoft are among the latest companies to expand forward deployed engineering, Palantir Technologies helped establish the modern model following the launch of its Artificial Intelligence Platform (AIP) in early 2023.
Rather than selling AI software alone, Palantir paired its platform with FDEs who worked directly with customers to integrate AI into operational workflows and enterprise systems. The strategy accelerated commercial adoption and helped transform the company from a business primarily associated with government contracts into a major commercial AI software provider.
The success of that approach demonstrated that many enterprises were seeking implementation expertise alongside AI platforms, particularly for deployments involving proprietary data and mission-critical operations.
The trend has now extended to hyperscalers as well as AI model providers looking to establish enterprise business.
Anthropic, which previously detailed plans to increase its Applied AI team, recently formed a standalone enterprise AI services company backed by Blackstone, Hellman & Friedman and Goldman Sachs.
The organization brings together Anthropic’s engineering resources with enterprise consulting capabilities to help customers integrate its Claude AI model into their core business operations.
“Applied AI engineers from Anthropic will work alongside the firm’s engineering team to identify where Claude can have the most impact, build custom solutions, and support customers over the long term,” the company stated.
Companies from community banks to mid-sized manufacturers and regional health systems lack the in-house resources to build and run frontier AI deployments, which require hands-on engineering and deep familiarity with business processes.
“Enterprise demand for Claude is significantly outpacing any single delivery model. Our partnerships with the world’s leading systems integrators are central to how Claude reaches large enterprises,” according to Krishna Rao, Chief Financial Officer of Anthropic.
Rival developer OpenAI has also launched its own enterprise FDE firm, the OpenAI Deployment Company, acquiring 150 specialists from Tomoro, an applied AI consulting and engineering firm. The new company has more than $4BN of initial investment, which it will use to scale operations and make further acquisitions.
“These FDEs will work closely with business leaders, operators, and frontline teams to identify where AI can make the biggest impact, redesign organizational infrastructure and critical workflows around it, and turn those gains into durable systems,” OpenAI stated.
The company is a partnership with 19 global investment firms, consultancies and system integrators, led by TPG, with Advent, Bain Capital and Brookfield as co-lead founding partners. Goldman Sachs and SoftBank are among the founding partners.
These moves by some of the largest vendors suggest that forward deployed engineering is becoming a standard component of enterprise AI go-to-market strategies.
As foundation models continue to converge in capability, providing expertise to assist enterprise buyers in implementation is emerging as a competitive differentiator. The shift reflects a growing recognition that deploying AI at scale requires the engineering expertise to integrate AI into business operations securely, responsibly and efficiently.
