The economics of enterprise AI: What the Forrester TEI study reveals about Microsoft Foundry

Customers are actively seeking more intelligent models, capable agents, and ready-to-use solutions to effectively implement AI workflows.

Business leaders are pursuing advancements in AI, transforming organisational structures to be human-focused and agent-driven. Consequently, customers are looking for smarter models, proficient agents, and market-ready options to put AI workflows into practice.

When Forrester partnered with Microsoft Foundry to model the economic impact of enterprise AI, they uncovered an unexpected finding: developer productivity was the crucial factor behind the 327% ROI over three years¹, amounting to $15.7 million across that period.

The findings indicated that by allowing developers to concentrate on what truly matters, the bottleneck affecting ROI can be significantly reduced.

The Hidden Cost of Your AI Investment

In many companies, senior engineers spend approximately one-third of their time on repetitive tasks, such as integrating various tools, recreating context pipelines, and adhering to custom governance processes. This effort does not provide any competitive advantages; rather, it hampers every AI initiative.

Forrester found that organisations utilising Foundry were able to avoid much of this unnecessary work, resulting in up to a 35% increase in productivity. Teams employing Foundry for AI application development experienced payback periods as brief as six months, with benefits continuing to grow annually¹.

The Details: Insights from the Forrester Study

Forrester interviewed 10 decision-makers from five organisations and surveyed an additional 154 AI leaders across the U.S. and Europe who have experience with Microsoft Foundry. They modelled a hypothetical enterprise with $10 billion in revenue, 25,000 employees, and 100 technical staff using Foundry. To ensure conservative estimates, they adjusted the benefits downward and costs upward; the results correspond to the hypothetical enterprise.

Figure 1: Survey Findings and Reported Advantages

When asked about the “benefits experienced through Microsoft Foundry,” respondents highlighted various operational outcomes:

The study revealed that investments made in platforms provide compounding value. For a team that invests $11.6 million in resources, the three-year present value of quantified benefits for the hypothetical organisation reached $49.5 million: Year one yielded $10 million, year two $21.1 million, and year three $30.5 million.

Figure 2: Breakdown of Benefits

When Every Project Begins Anew

AI projects require various components such as models, comprehensive knowledge, tools, and governance systems. Without a unified platform, teams often face unnecessary complications. For instance, teams need to create vector databases, RAG pipelines, and access-control rules for every AI endeavour, effectively building internal infrastructures that don’t directly impact business performance.

With Foundry, teams can build AI applications and agents using a cohesive, interoperable platform aimed at making these agents intelligent and reliable. This includes reusable knowledge bases and data security measures, all protected by built-in evaluations and agent controls. In Forrester’s TEI analysis, 75% of teams mentioned experiencing simplified integration of model foundations or knowledge sources with Foundry IQ.

The productivity boost alone over three years was valued at up to $15.7 million¹. One Foundry user shared:

Our developers can progress rapidly because they can find exactly what they need in Microsoft Foundry… We estimate an overall development time reduction of 30%–40%.

—Global Head of Technology Platforms, Professional Services

Companies witnessed growing returns when they reused components like templates, knowledge bases, and governance practices. This highlights a surprising insight: organisations focusing on a unified platform tend to have better results compared to those that do not. Streamlined execution leads to enhanced performance.

The Importance of Platform Thinking

Over time, organisations develop various point solutions that address specific issues, each adding its own governance and integration complexities. This accumulated hidden cost results from the effort needed to connect these disparate solutions.

In the Forrester study, 32% of participants who adopted Foundry were able to cut costs by retiring outdated AI tools, and the hypothetical organisation saved up to $4.3 million in infrastructure costs over three years by eliminating redundant workflows and operational overhead. One customer remarked on how they could phase out their container-based infrastructure, thus stopping expenses on prior AI model development tools, since Foundry already included these features:

Using Foundry instead of maintaining container-based models gives us the advantage of not needing to manage container infrastructure.

—Managing Director and Global Head of Co-Innovation, Professional Services

While department budgets tend to favour point solutions, achieving enterprise-level results necessitates platform thinking. This inconsistency often leads to AI investments failing to yield sustainable value as organisations transition from isolated experiments to broader implementations.

Trust Facilitates Higher-Impact Initiatives

Most enterprises begin with AI applications that serve internal functions before branching out to customer-facing solutions. Currently, around two-thirds of AI agents are focused on process automation, while one-third are designed for direct human assistance¹. This ratio is significant. Organisations first need to establish trust in AI for manageable, traceable tasks before relying on it to enhance human decision-making.

Foundry Control Plane allows businesses to manage the AI lifecycle with holistic observability and control mechanisms. This includes centrally administered policies for deploying models, adjustable safety measures, and ongoing evaluations to monitor performance, rectify issues, and ensure compliance in any environment.

Microsoft’s scanning of our models is essential for us. We want to ensure we understand the model’s content and verify there’s nothing that contradicts our policies.

—Principal Product Manager, Professional Services

It’s not surprising that 67% of respondents cited worries about AI security, privacy, and governance as top reasons for selecting Microsoft Foundry, ranking higher than model access, capabilities, and cost-related inefficiencies. In essence, trust serves as the gateway for organisations to expand beyond isolated automation projects to scaled, impactful initiatives.

What Leaders Need to Do About AI Now

The Forrester TEI study makes one thing clear: the ROI from enterprise AI grows when AI is regarded as a platform and not merely a sequence of individual projects.

The most significant benefits come from providing technical teams with a reusable foundation that includes models, agents, and tools that can scale across various use cases, removing repetitive tasks. When AI development is streamlined, value compounds and confidence increases.

Discover the Benefits of AI Workflows

The Forrester Total Economic Impact study on Microsoft Foundry was commissioned by Microsoft and conducted by Forrester Consulting.

¹The Total Economic Impact Of Microsoft Foundry, a commissioned study carried out by Forrester Consulting, February 2026

²Represents results for the hypothetical organisation