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Total Economic Impact

The Total Economic Impact™ Of Microsoft Foundry

Cost Savings And Business Benefits Enabled By Microsoft Foundry

A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY MICROsOFT, FEBRUARy 2026

[CONTENT]
 

Total Economic Impact

The Total Economic Impact™ Of Microsoft Foundry

A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY MICROsOFT, FEBRUARy 2026

Cost Savings And Business Benefits Enabled By Microsoft Foundry

Forrester Print Hero Background

Table Of Contents

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Executive Summary

Microsoft Foundry offers a unified, interoperable platform to build, optimize, and govern AI innovation at scale. With Foundry, customers significantly cut the time and costs required to develop AI applications and agents. The faster development cycle allows customers to launch new AI agents and products faster, drive incremental revenue growth, improve employee productivity, and reduce operating expenses.

Microsoft Foundry provides professional developers and technical teams with tools to build, optimize, and govern AI applications and agents within a modular platform. With Foundry, technical teams can develop and fine-tune custom AI models and access a catalog of more than 11,000 AI models, including open-source AI, industry, and frontier models from providers such as OpenAI, Anthropic, DeepSeek, and Meta. Technical teams can orchestrate and monitor agentic workflows using Foundry and open-source agent frameworks.1 Foundry has built-in quality, safety, and security controls and observability to support production-grade AI development and operation.

Microsoft commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by building with Microsoft Foundry.2 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Microsoft Foundry on their organizations.

327%

Return on investment (ROI)

 

$37.9M

Net present value (NPV)

 

To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed 10 decision-makers at five organizations and surveyed 154 respondents with experience using Microsoft Foundry. For the purposes of this study, Forrester aggregated the experiences of the interviewees and survey respondents and combined the results into a single composite organization, which is a global organization with 25,000 employees and revenue of $10 billion per year.

The interviewees said that prior to using Microsoft Foundry, it was expensive and inefficient to develop AI applications and agents. Managing underlying compute and storage infrastructure required significant time and resources. Technical teams worked inefficiently across multiple platforms to develop AI applications and agents and did not always have access to the latest AI models. The interviewees were concerned that their organizations lacked appropriate security measures to help ensure responsible AI development and protect their organizations’ data and privacy.

After the investment in Microsoft Foundry, the interviewees had a single platform for AI application and model development, reducing development time and costs. With Foundry, their technical teams had access to the latest AI models, including frontier and open-source models. Microsoft managed and maintained the underlying compute infrastructure, ensuring that it was state of the art. With Foundry, interviewees’ technical teams had tools to improve their productivity, including reusable templates and AI model leaderboards to help them select the best AI models to meet their needs. Enterprise-grade security embedded in the Foundry platform and throughout the AI lifecycle accelerated production readiness.

“What benefits has your organization experienced with Microsoft Foundry?”

[CHART DIV CONTAINER]
Operational efficiencies Improved customer experience and customer retention Reduced time to build AI applications and agents Improved AI model and agent quality Decreased labor for technical teams Improved security and compliance Improved time to market Increased revenue Reduced cost to develop and deploy AI applications and agents Increased product and service innovation Decreased costs by decommissioning legacy tools Decreased labor for business end users

Base: 154 AI decision-makers at organizations in the US and Europe using Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

Key Findings

Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:

  • Technical team productivity improvement of 35% by Year 2, $15.7 million three-year PV. With Foundry, the composite’s technical teams develop AI applications and agents more efficiently using a single, comprehensive AI development platform. Foundry provides tools to help with AI application and agent development such as reusable templates and coding assistance. Leaderboards make it easier and faster to select which AI model to use for a particular use case. Over three years, this benefit is worth $15.7 million to the composite organization.

  • Streamlined operating expenses, with $17.2 million in savings over three years. The composite organization realizes operating cost savings with the AI applications and agents it develops with Foundry. Approximately two-thirds of the AI agents focus on process automation. Although Foundry does not impact all operating costs, the composite organization does see a 10% reduction in the categories of expense it streamlines. This benefit is worth $12.3 million over three years to the composite organization.

  • Faster time to market, with $17 million in incremental profit over three years. With Foundry, the composite organization reduces the time required to develop new AI applications and agents. The faster development cycle allows it to bring new products and services enabled by AI to market sooner, accelerating incremental revenue. Easier infrastructure management and enhanced technical team productivity with Foundry drives the time savings. This benefit is worth $12.3 million over three years to the composite organization.

  • End-user productivity improvement of 10% improvement, $4.8 million three-year PV. The AI applications and agents developed with Foundry improve employee productivity. Approximately one-third of the AI agents developed with Foundry focus on human assistance. AI agents can compile information and provide advice to help the composite’s employees work more effectively. Employees then spend their time on higher-value tasks, such as interacting with customers instead of information retrieval. This benefit is worth $4.8 million over three years to the composite organization.

  • Avoided prior infrastructure and services costs, worth $4.3 million over three years. After adopting Foundry, the composite organization avoids spending on legacy infrastructure and tools that had previously supported AI application and model development. The composite organization reduces the need for additional technical support FTEs for AI application and agent development. This benefit is worth $4.3 million over three years to the composite organization.

Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:

  • Confidence in Foundry’s security and compliance with privacy and governance requirements. Concerns about AI security, privacy, and governance were top reasons the composite decided to adopt Foundry. It leverages Foundry Control Plane for organizationwide observability and controls of AI agents, models, and tools to help ensure safe and secure AI performance.

  • Improved AI model quality. The composite organization sees an improvement in AI model quality with Foundry and finds it easier to fine-tune and ground models with the proper data.

  • Access to a diverse library of models, including open-source AI models. With Foundry Models, users at the composite organization have access to a catalog of more than 11,000 models, including models from providers such as OpenAI, Anthropic, DeepSeek, and Meta. Foundry quickly provides users with access to the latest AI models such as ChatGPT-5 and Claude Opus 4.5 shortly after their releases. Foundry scans third-party and open-source AI models for emerging threats and vulnerabilities and provides configurable guardrails to control inputs and outputs, so the composite organization has confidence in model deployments.

  • Agentic AI and enhanced agent management. The composite organization uses Foundry to orchestrate AI apps and agents with open, flexible frameworks. With Foundry Agent Service, the composite’s developers find it easier to do multiagent orchestration and technical teams can track and monitor AI agents.

  • Microsoft’s global reach. Microsoft’s global presence helps support the composite organization’s global footprint. The availability of Foundry’s AI models and services across the globe is also a significant benefit.

Costs. Three-year, risk-adjusted present value (PV) costs for the composite organization include:

  • Microsoft Foundry costs of $8.2 million over three years. The composite organization pays for Foundry primarily on a consumption basis. The cost depends on which Foundry services and AI models it uses.

  • Foundry implementation and maintenance costs of $3.4 million over three years. The composite organization spends two months piloting and implementing Foundry. Five technical team FTEs are devoted to maintaining Foundry.

The financial analysis that is based on the interviews and survey found that a composite organization experiences benefits of $49.5 million over three years versus costs of $11.6 million, adding up to a net present value (NPV) of $37.9 million and an ROI of 327%.

“Platform services like Microsoft Foundry are important because they take care of the security aspects and the patching and all those things add up to ease of use. People can build AI applications and agents super-fast because they can get what they need very quickly in Foundry.”

Managing director and global head of co-innovation, professional services

Key Statistics

327%

Return on investment (ROI) 

$49.5M

Benefits present value (PV) 

$37.9M

Net present value (NPV) 

<6 months

Payback 

Benefits (Three-Year)

[CHART DIV CONTAINER]
Technical team productivity improvement Streamlined operating expenses Faster time to market End-user productivity improvement Avoided prior infrastructure and services cost

The Microsoft Foundry Customer Journey

Drivers leading to the Microsoft Foundry investment
Interviews
Role Industry Region Annual revenue (USD)
Global head of technology platforms Professional services Global $53 billion
Leader, diversity and inclusion Professional services Global $53 billion
Managing director and global head of co-innovation Professional services Global $53 billion
Director Professional services Global $38 billion
Principal product manager Professional services Global $38 billion
EVP Financial services North America $1.7 billion
Senior solution architect Financial services North America $1.7 billion
Partner genAI AI software Asia $33 million
Principal architect AI software Asia $33 million
CEO AI software Asia $15 million (estimate)
Key Challenges

Prior to adopting Foundry, interviewees’ organizations typically developed AI models and AI agents on their own infrastructure and self-sourced third-party AI models. Interviewees and survey respondents noted how their organizations struggled with common challenges, including:

  • Managing and scaling underlying AI infrastructure. The interviewees wanted to focus on their core business priorities rather than devoting significant resources to managing the underlying infrastructure required to develop AI applications and agents. They did not want to manage servers in data centers or procure and manage cloud-based GPUs.

  • Spending time and money developing new AI applications and agents. Before Foundry, it was time-consuming and expensive to develop AI applications and agents. It required technical teams to work across multiple tools and platforms, which was inefficient.

  • Addressing security concerns. The interviews and survey respondents shared that it was challenging to establish the correct security procedures before moving to Microsoft Foundry. Interviewees called out concerns that open-source AI models could have hidden security issues. Survey respondents noted that concerns with AI security, compliance, and governance was the top reason their organizations decided to adopt Microsoft Foundry.

“What were the key factors or pain points that led your organization to adopt Microsoft Foundry?”

[CHART DIV CONTAINER]
Concerns with AI security, privacy, or governanace Challenges scaling AI infrastructure Delays and inefficiencies bringing new AI models to market Limited internal resources to develop AI models and AI agents Inability to easily customize or fine-tool AI models Challenges getting started with AI agents Difficulties orchestrating AI agents Limited access to third-party and open-source AI models Challenges tracking AI agent behavior Concerns about AI model quality Challenges deploying AI agents in a multicloud environment Challenges choosing which AI model to use

Base: 154 AI decision-makers at organizations in the US and Europe using Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

“We moved to Microsoft Foundry because we are not in the business of data center management, procuring GPUs, and deploying scaling and monitoring. We are interested in using AI as an API. Microsoft Foundry came across as the most useful provider because of its partnership with OpenAI, and they support open-source models.”

CEO, AI software

“Model scanning done by Microsoft on the models is really important for us and is a key requirement. When we leverage a large language model, we want to make sure we understand what the model contains and whether it contains anything that is not in line with policy.”

Principal product manager, professional services

Composite Organization

Based on the interviews and survey, Forrester constructed a TEI framework, a composite company, and an ROI analysis that illustrates the areas financially affected. The composite organization is representative of the interviewees’ organizations, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:

  • Description of composite. The composite organization is a $10 billion global organization employing 25,000 people. Before adopting Foundry, it developed AI applications and agents on its own infrastructure and procured third-party AI models directly from the model creators. Its technical team includes developers, data scientists, data engineers, machine learning engineers, data analysts, IT admins and security professionals, solution architects, and technical decision-makers.

  • Deployment characteristics. The composite organization uses multiple products within the Foundry platform including Foundry Agent Service, Foundry Models, Foundry IQ, Foundry Tools, Azure Machine Learning, and Foundry Control Plane. Foundry Agent Service supports building, hosting, and scaling AI agents; Foundry Models offers a library of more than 11,000 AI models; Foundry IQ provides a knowledge layer for agents based on next generation retrieval augmented generation; Foundry Tools offers a catalog of tools, connectors, and model context protocol services to build agentic apps; Azure Machine Learning offers tools to build, train, and fine-tune models; and Foundry Control Plane provides centralized identity, policy, observability, and security signals for AI developers.
    Approximately 100 technical team members use Microsoft Foundry to develop and manage AI applications and agents. The technical team at the composite organization uses Foundry to access third-party and open-source AI models, fine-tune AI models, train custom AI models, develop custom AI applications and agents, and orchestrate and track AI agent behavior. The technical team uses a variety of front ends to build with Foundry including the Foundry portal, GitHub, Microsoft Copilot, and Visual Studio Code. The AI applications and agents developed with Foundry support revenue growth and cost containment. The composite organization uses Foundry Agent Service, and about half of the AI agents it develops with Foundry are multiagent solutions.

 KEY ASSUMPTIONS

  • $10 billion revenue

  • 25,000 employees

  • 100 technical staff using Foundry

Analysis Of Benefits

Quantified benefit data as applied to the composite
Total Benefits
Ref. Benefit Year 1 Year 2 Year 3 Total Present Value
Atr Technical team productivity improvement $3,462,750 $7,271,775 $8,726,130 $19,460,655 $15,713,757
Btr Streamlined operating expenses $1,800,000 $5,400,000 $8,280,000 $15,480,000 $12,320,060
Ctr Faster time to market $2,700,000 $4,860,000 $7,776,000 $15,336,000 $12,313,298
Dtr End-user productivity improvement $607,500 $1,822,500 $3,645,000 $6,075,000 $4,797,014
Etr Avoided prior infrastructure and services cost $1,478,055 $1,734,785 $2,040,802 $5,253,642 $4,310,678
  Total benefits (risk-adjusted) $10,048,305 $21,089,060 $30,467,932 $61,605,297 $49,454,807
Technical Team Productivity Improvement

Evidence and data. The interviewees and survey respondents found that their technical teams saved significant time developing AI applications and agents with Foundry, ranging from 10% to 40%.

  • With Foundry, the developers at the interviewees’ organizations were able to develop AI agents and applications within a single platform. The global head of technology platforms in the professional services industry explained: “We’ve seen a 30% to 40% improvement in time to market to build AI agents with Microsoft Foundry. Before, we had to stick together many models. Now, with Foundry, we have one silo for development.” He added: “Our developers can go super-fast because they can get what they need in Microsoft Foundry. They have reusable templates, centralized governance, and integrations, and Microsoft manages the infrastructure.”

  • Foundry provided tools to help developers, including reusable templates, coding assistance, and tools to facilitate AI model selection. Developers at the interviewees’ organizations used the model leaderboards and benchmarks in Foundry to help pick which AI model would best meet their needs and requirements. The principal product manager at a professional services organization explained: “We don’t always need the most up-to-date model. Foundry has leaderboards, which are fantastic, and one looks at cost. We can see which model is going to be the most cost-effective.”

  • The interviewees found the Foundry platform easy to use. The principal product manager at a professional services organization shared: “With Microsoft Foundry, I can select a model, deploy it, put a content filer on it, and then start to use it. I can start getting test reports back. It’s very integrated and its integration is really nice.”

  • The CEO at an AI software organization noted, “Our engineering teams use Microsoft Foundry with [GitHub] Copilot for coding assistance, and it saves them 20% to 30% of their time.” The principal product manager at a professional services organization added, “Our developers are saving anywhere from 10% to 40% of their time with Microsoft Foundry.”

  • Fifty-two percent of survey respondents reported that Foundry decreased the labor required for their technical teams to build AI applications and agents. Of the respondents who saved time, 48% reported technical team time savings of more than 30% in building AI applications and agents with Foundry.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • One hundred technical team members use Foundry in Year 1 and the number of users increases 20% each year. The technical team includes developers, data scientists, data engineers, machine learning engineers, data analysts, IT admins and security professionals, solution architects, and technical decision-makers.

  • With Foundry, the technical team saves time building AI applications and agents. The time savings is 20% in Year 1 and increases to 35% by Year 2. The time savings increase as the technical team gains more experience working with Foundry.

  • The average fully burdened annual salary for a technical team member is $243,000.

  • Technical team members effectively repurpose 75% of their time savings.

Risks. The expected financial impact is subject to risks and variation based on several factors:

  • The number of technical team members using Foundry.

  • The skill of the technical team.

  • The technical team’s ability to repurpose time savings effectively.

Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $15.7 million.

35%

Technical team time savings by Year 2

“The time savings for our developers is 15% to 25% with Microsoft Foundry. It depends on the seniority and maturity of the developer and there is still a need to review what is produced.”

Global head of technology platforms, professional services

“You indicated that Microsoft Foundry has helped your organization’s technical teams save time building AI applications and agents. What percentage of time savings has your organization experienced since using Foundry?”

[CHART DIV CONTAINER]
0% 1% to 9% 10% to 29% 30% to 49% 50% to 69% 70% to 89%

Base: 80 AI decision-makers at organizations in the US and Europe who found that Microsoft Foundry reduced their technical team’s time to build AI applications and agents
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

Technical Team Productivity Improvement
Ref. Metric Source Year 1 Year 2 Year 3
A1 Technical team FTEs Composite 100 120 144
A2 Time savings Interviews and survey 20% 35% 35%
A3 Fully burdened annual salary for a technical team FTE Composite $243,000 $243,000 $243,000
A4 Productivity recapture TEI methodology 75% 75% 75%
At Technical team productivity improvement A1*A2*A3*A4 $3,645,000 $7,654,500 $9,185,400
  Risk adjustment ↓5%      
Atr Technical team productivity improvement (risk-adjusted)   $3,462,750 $7,271,775 $8,726,130
Three-year total: $19,460,655 Three-year present value: $15,713,757
Streamlined Operating Expenses

Evidence and data. The interviewees and survey respondents realized operating cost savings with the AI applications and agents developed with Foundry.

  • A subset of the AI agents and AI applications that interviewees’ organizations developed with Foundry were focused on streamlining internal costs. Process automation was the most common business use case, and survey respondents reported that two-thirds of the AI applications and agents they developed with Foundry focused on automation.

  • The interviewees shared that AI applications and agents developed with Foundry resulted in operating cost savings.

  • Seventy percent of survey respondents reported operational efficiencies with Foundry, and 42% of these reported that Foundry decreased operating expenses by 10% or more.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • AI applications and agents developed with Foundry do not impact every operating expense category. One percent of operating expenses are impacted in Year 1, and this increases to 2.3% by Year 3 as the composite rolls out new AI applications and agents.

  • The composite reduces impacted operating expenses by 5% in Year 1 due to automation and process improvements driven by AI applications and agents developed with Foundry. The reduction in operating expense grows to 10% in Years 2 and 3.

Risks. The expected financial impact is subject to risks and variation based on several factors:

  • An organization’s industry.

  • The mix of AI applications and agents focused on operating efficiencies.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $12.3 million.

10%

Reduction in impacted operating expenses by Year 2

“You indicated that your organization has been able to streamline operations and reduce operating expenses with Microsoft Foundry. On average, by what percentage has your organization been able to decrease its expenses since using Foundry?”

[CHART DIV CONTAINER]
0% 1% to 5% 6% to 10% 11% to 20% 21% to 30% 30% or more

Note: Percentages may not total 100 due to rounding
Base: 108 AI decision-makers at organizations in the US and Europe who streamlined operations and reduced operating expenses with Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

Streamlined Operating Expenses
Ref. Metric Source Year 1 Year 2 Year 3
B1 Operating expenses before Foundry Composite $4,000,000,000 $4,000,000,000 $4,000,000,000  
B2 Percentage of operating costs impacted by AI applications and agents developed with Microsoft Foundry Composite 1.0% 1.5% 2.3%  
B3 Operating costs impacted by AI applications and agents developed with Microsoft Foundry B1*B2 $40,000,000 $60,000,000 $92,000,000  
B4 Reduction in impacted operating expense Interviews and survey 5% 10% 10%  
Bt Streamlined operating expenses B3*B4 $2,000,000 $6,000,000 $9,200,000  
  Risk adjustment ↓10%        
Btr Streamlined operating expenses (risk-adjusted)   $1,800,000 $5,400,000 $8,280,000  
Three-year total: $15,480,000 Three-year present value: $12,320,060
Faster Time To Market

Evidence and data. Foundry reduced the overall AI application and AI agent development cycle for interviewees’ and survey respondents’ organizations. Easier infrastructure management and enhanced technical team productivity contributed to the time savings. The faster AI application and agent development cycle allowed organizations to launch new revenue-generating products faster, accelerating incremental revenue.

  • The partner, genAI at an AI software organization shared: “Microsoft Foundry makes our whole workflow and AI product development easier. We are still experimenting, but it’s probably 25% to 30% time and cost savings.”

  • Forty-eight percent of survey respondents reported that Foundry helped their organizations improve time to market for new AI applications and agents. Of the respondents that saw an improvement in time to market, 72% reported a time savings of more than 30% to build AI applications and agents with Foundry. On average, survey respondents reported that Foundry reduced the time to build AI applications and agents by 40%.

  • Faster time to market helped interviewees’ organizations launch new products faster, driving incremental revenue growth. Forty-three percent of survey respondents reported that Foundry helped their organizations increase revenue. Of the survey respondents who saw an increase in revenue with Foundry, 64% attributed it to the creation of new revenue streams and 58% to increased customer engagement.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • The composite organization’s technical team develops AI applications and agents with Foundry that support revenue uplift and growth.

  • AI applications and agents impact 6% of the composite organization’s total revenue in Year 1, and this increases to 8.6% by Year 3 as the composite organization rolls out additional AI applications and agents.

  • The AI applications and agents allow the composite organization to roll out new AI products and services more quickly. The faster time to market results in additional revenue uplift. The revenue uplift is 5% in Year 1, increasing to 10% by Year 3.

  • Forrester applies a 10% operating margin to reflect the costs associated with the incremental revenue.3

Risks. The expected financial impact is subject to risks and variation based on several factors:

  • The speed with which the composite organization’s technical team develops and rolls out AI applications and agents with Foundry.

  • The mix of AI applications and agents that support revenue growth and uplift.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $12.3 million.

$17 million

Incremental profit over three years

“We estimate that we reduce overall development time by 30% to 40% with Microsoft Foundry.”

Global head of technology platforms, professional services

“You noted that AI models and agents Microsoft Foundry enables have contributed to increased revenue. In which of the following ways has your organization experienced this impact?”

[CHART DIV CONTAINER]
Created new revenue streams Increased customer engagement Improved existing revenue streams Improved customer retention Accelerated time to market for products or services Improved operations Increased innovation Others

Base: 66 AI decision-makers at organizations in the US and Europe whose organizations experienced an increase in revenue with Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

Faster Time To Market
Ref. Metric Source Year 1 Year 2 Year 3
C1 Revenue before Foundry Composite $10,000,000,000 $10,000,000,000 $10,000,000,000
C2 Percentage of revenue impacted by AI applications and agents developed with Foundry Interviews and survey 6.0% 7.2% 8.6%
C3 Revenue impacted by AI applications and agents developed with Foundry Composite $600,000,000 $720,000,000 $864,000,000
C4 Revenue uplift due to faster time to market Interviews and survey 5.0% 7.5% 10.0%
C5 Incremental revenue C3*C4 $30,000,000 $54,000,000 $86,400,000
C6 Operating margin Research data 10% 10% 10%
Ct Faster time to market C5*C6 $3,000,000 $5,400,000 $8,640,000
  Risk adjustment ↓10%      
Ctr Faster time to market (risk-adjusted)   $2,700,000 $4,860,000 $7,776,000
Three-year total: $15,336,000 Three-year present value: $12,313,298
End-User Productivity Improvement

Evidence and data. The interviewees and survey respondents found that the AI applications and agents developed with Foundry helped their employees save time. The interviewees estimated that the time savings for end users varied from 2% to 30% based on roles and use cases. The survey respondents reported that approximately one-third of the AI agents they develop with Foundry target human assistance.

  • The EVP at a financial services organization described how an agent developed with Foundry made it easier and faster for their sales team to gather information ahead of client conversations. The sales team could then spend more time with clients rather than on information gathering.

  • The partner, genAI at an AI software organization noted that a call center virtual agent developed with Foundry saved human call center agents from 2% to 30% of their time depending on the use case. The call center virtual agent was able to address customer questions, resulting in a 20% to 30% improvement in call deflection (i.e., the number of calls that did not require human call center agents) and a 15% to 20% decrease in average call handle time.

  • The CEO at an AI software organization estimated that AI applications and agents developed with Foundry saved non-engineering employees 10% to 20% of their time.

  • The principal product manager at a professional services organization shared an example of a tax advice agent that supports tax professionals developed with Foundry. The tax agent researches tax laws, generates tax advice, and ensures the advice aligns with client requirements.

  • Twenty-seven percent of survey respondents reported that the AI applications and agents developed with Foundry created labor savings for business end users. Of these, 81% reported savings of more than 10% from AI applications and agents built with Foundry.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • In Year 1, applications and agents developed with Foundry positively impact 10% of the composite organization’s employees. This increases to 30% by Year 3 as it rolls out more applications and agents developed with Foundry.

  • The employees save 10% of their time with AI applications and agents developed with Foundry.

  • The employees productively repurpose 50% of the time savings.

  • The average fully burdened annual salary for an employee is $108,000.

Risks. The expected financial impact is subject to risks and variation based on several factors:

  • The speed with which an organization’s technical team develops and rolls out AI applications and agents with Foundry.

  • The mix of AI application and agent use cases focused on employee productivity enhancements.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.8 million.

10%

End-user time savings

“Our focus with Microsoft Foundry has been to develop tools to help our sales team find answers to common questions. Now salespeople can save 20 to 30 minutes a day searching for information and can spend that time in client conversations. If we give salespeople back a few hours a week, they can potentially cover three, four, five more clients.”

EVP, financial services

“You indicated that AI models and AI agents built with Microsoft Foundry have helped your organization’s end users save time. What percentage of time savings has your organization experienced since using Foundry?”

[CHART DIV CONTAINER]
0% 1% to 9% 10% to 29% 30% to 49% 50% to 69% 70% to 89%

Base: 42 AI decision-makers at organizations in the US and Europe who experienced business end-user time savings with Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

End-User Productivity Improvement
Ref. Metric Source Year 1 Year 2 Year 3
D1 Employees Composite 25,000 25,000 25,000
D2 Percentage of employees impacted by Microsoft Foundry applications and agents Interviews and survey 10% 20% 30%
D3 Percentage of work impacted by Microsoft Foundry Interviews and survey 5.0% 7.5% 10.0%
D4 Time savings Interviews and survey 10% 10% 10%
D5 Fully burdened salary for an end user Composite $108,000 $108,000 $108,000
D6 Productivity recapture TEI methodology 50% 50% 50%
Dt End-user productivity improvement D1*D2*D3*D4*D5*D6 $675,000 $2,025,000 $4,050,000
  Risk adjustment ↓10%      
Dtr End-user productivity improvement (risk-adjusted)   $607,500 $1,822,500 $3,645,000
Three-year total: $6,075,000 Three-year present value: $4,797,014
Avoided Prior Infrastructure And Services Cost

Evidence and data. After adopting Foundry, the interviewees’ and survey respondents’ organizations were able to reduce spending on legacy infrastructure and tools that had been supporting AI application and model development. They were also able to reduce the support required for AI application and model development.

  • The global head of technology platforms for a professional services organization reported avoiding legacy compute infrastructure spending after moving AI application and agent development to Foundry. The partner, genAI at an AI software organization shared that his company was able to decommission its prior container-based infrastructure and eliminate spending on previous AI model development tools since the functionality was included in the Foundry platform.

  • The managing director and global head of co-innovation at a professional services organization explained: “One of the benefits of using Foundry versus taking those models and running them in containers in the cloud is that then you don’t have to manage the container infrastructure. Foundry abstracts all that and our teams don’t have to spend any time even thinking about it.”

  • Thirty-two percent of survey respondents reported that with Microsoft Foundry, they were able to decrease costs by decommissioning legacy tools.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • The composite organization saves $1.4 million in Year 1 by decommissioning legacy tools. This increases to $2.1 million by Year 3.

  • The composite organization avoids hiring two technical support FTEs as a result of using Foundry. The average fully burdened annual salary for a technical support FTE is $108,000.

Risks. The expected financial impact is subject to risks and variation based on several factors:

  • Prior spending on infrastructure to support AI application and AI agent development.

  • Prior spending on AI model development tools and platforms.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.3 million.

“Microsoft Foundry is very cost efficient versus going to a GPU provider to run models from open-source libraries. It’s 30% to 40% cheaper with Microsoft than if we tried to do it on our own.”

CEO, AI software

Avoided Prior Infrastructure And Services Cost
Ref. Metric Source Year 1 Year 2 Year 3
E1 Avoided prior infrastructure and services spending Interviews $1,426,283 $1,711,539 $2,051,558
E2 Avoided technical support hiring (FTEs) Interviews 2 2 2
E3 Fully burdened annual salary for a technical support FTE Composite $108,000 $108,000 $108,000
Et Avoided prior infrastructure and services cost E1+(E2*E3) $1,642,283 $1,927,539 $2,267,558
  Risk adjustment ↓10%      
Etr Avoided prior infrastructure and services cost (risk-adjusted)   $1,478,055 $1,734,785 $2,040,802
Three-year total: $5,253,642 Three-year present value: $4,310,678
Unquantified Benefits

Interviewees and survey respondents mentioned the following additional benefits that their organizations experienced but were not able to quantify:

  • Confidence in Foundry’s security and compliance with privacy and governance requirements. The interviewees and survey respondents put a high premium on Foundry’s security. Concern about AI security, privacy, and governance was the top reason organizations decided to adopt Foundry according to survey respondents. The CEO at an AI software organization shared: “We have to go through a lot of security compliances and a significant part of that is the infrastructure, the network, the cloud, and the models. Foundry does the heavy lifting. We still need to deal with security compliance for our use cases, but they help us automate a significant set of compliance requirements.”
    The partner, genAI at an AI software organization added: “We want to focus on business problems and how to solve them rather than solving the fundamental technology problems like access to models or security. We believe Microsoft is better suited to do this. So when we build on top of Foundry, we don’t need to worry about the underlying security, scaling, and monitoring. All of those things are taken care of by Foundry.”

  • Improved AI model quality. The interviewees and survey respondents saw an improvement in AI model quality with Foundry. It was easier to fine-tune models and ground them with the proper data. The global head of technology platforms for a professional services organization explained: “We definitely see an improvement in model accuracy with Foundry with the proper data. It’s an easy way to do the fine-tuning work, but you need to know how to fine-tune and have the right data scientist.” Seventy-five percent of survey respondents reported easier model grounding, and 67% reported easier model fine-tuning with Foundry.

  • Access to a diverse library of models, including open-source AI models. With Foundry, users have access to more than 11,000 Foundry models. The global head of technology platforms at a professional services organization noted, “Microsoft Foundry offers 11,000 models and all of them are available for our people to experiment with.” Timely access to open-source models was an important benefit of Foundry. The CEO at an AI software organization shared: “Microsoft Foundry came across as the most useful provider because of their partnership with Open AI. They are supporting open-source models and commercial state-of-the-art models.” The principal product manager at a professional services organization shared: “The ability to get access to the most recent models is a really big push for us. So when GPT-5 was announced, it was available within Foundry within a day of the announcement.”

  • Agentic AI and enhanced agent management. The interviewees used Foundry Agent Service to develop and manage agentic AI workflows. They valued the ability to track and monitor AI agents and found it easter to do multiagent orchestration with Foundry. The principal architect at an AI software organization shared: “Foundry provides all the architectures known in the industry and gives us flexibility. It can be orchestrator level, multiagent, or a supervisor-based architecture.” The global head of technology platforms at a professional services organization added: “Our organization is decentralized, and it’s a massive advantage to have Foundry federate groups and give us visibility into the agents being created and the telemetry. It gives us an advantage versus disconnect stacks. We can reuse many of those agents and make them communicate with each other.”

  • Microsoft’s global reach. The interviewees appreciated that Microsoft’s global presence helped support their organizations’ global footprint. The managing director and global head of co-innovation at a professional services organization shared: “The nature of Microsoft’s global reach helps us. We are truly a global firm and that comes with its own host of challenges. The availability of services across the globe with Microsoft is a big benefit for us.” The CEO at an AI software organization added: “Foundry’s global scale is important to us. They bring up new AI models as soon as they are available and they’re production ready and globally ready.”

“The hosting and deployment of these models with Foundry comes with additional guarantees, which include safety controls, content safety filters, and more, which we really appreciate. It helps drive our responsible AI initiative.”

Senior solution architect, financial services

“We have seen both accuracy improvements and performance improvements when we fine-tune models with Microsoft Foundry.”

CEO, AI software

“Before, we would be responsible for the agentic infrastructure. Now Microsoft Foundry is providing a platform-as-a-service capability to host and execute AI agents. That’s a really big thing because a lot of time we have agentic workflows. It’s excellent and a key breakout feature to enable multiagent orchestration.”

Principal product manager, professional services

“How much value do the following security and governance features provide to your organization?”

[CHART DIV CONTAINER]
Enterprise-grade It security Encryption of data at rest and in transit Ability to detect and block prompt injection attacks and malicious code Third-party AI model screening for malware and vulnerabilities Ability to detect and redact personally indentifiable information Compliance certifications Integration with Microsoft Defender Ability to detect and filter toxic or biased content Foundry Locale for remote or disconnected environments Ability to detect and correct hallucinations Significant value Above average value

Base: 154 AI decision-makers at organizations in the US and Europe using Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

“How much do you agree with the following statements? For my organization, Microsoft Foundry has enabled:”

[CHART DIV CONTAINER]
Easier model grounding or knowledge sources integration Easier AI model fine-tuning More cost-effective AI model development Improved AI model accuracy Improved AI agent quality Access to a wide variety of data sources Strongly agree/agree

Base: 154 AI decision-makers at organizations in the US and Europe using Microsoft Foundry
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, November 2025

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Microsoft Foundry and later realize additional uses and business opportunities, including:

  • Access to latest AI tools and technology. Microsoft Foundry gives users access to the latest AI capabilities providing flexibility as AI technology advances. The managing director and global head of co-innovation at a professional services organization shared: “A lot of organizations just don’t have the capability to keep up with the latest GPUs and other capabilities. Foundry makes sure that you’ve got the latest capabilities and technology.”

  • Ease of use and support for a diverse group of users. Although technical users are typical Foundry users, it can support a broader and more diverse group of users. The principal product manager at a professional services organization explained: “Diverse user types can interact with Foundry. We’ve got developers, people concerned with responsible AI, testers, and product managers. It’s a very universal product and that is one of the top benefits.”

  • Supporting a neurodiverse workforce. One of the interviewees’ organizations partnered with Microsoft to examine how tools, including Foundry, can support a growing neurodiverse workforce. The leader of diversity and inclusion at a professional services organization estimated that 20% of the workforce today is neurodivergent, and that it is higher in data and emerging technology at 40% and increasing. In partnership with Microsoft, their professional services firm conducted a study with six to eight individuals who had not previously used Foundry. The participants provided feedback to Microsoft about how Foundry could best support neurodivergent individuals. This feedback helps ensure Foundry is flexible and can support all workers.

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).

“The various services in Foundry are configured to make sure that the AI services are delivered with the principles of responsible AI.”

Principal product manager, professional services

Analysis Of Costs

Quantified cost data as applied to the composite
Total Costs
Ref. Cost Initial Year 1 Year 2 Year 3 Total Present Value
Ftr Microsoft Foundry cost $0 $2,752,475 $3,302,970 $3,959,148 $10,014,593 $8,206,543
Gtr Implementation and maintenance $204,120 $1,275,750 $1,275,750 $1,275,750 $4,031,370 $3,376,721
  Total costs (risk-adjusted) $204,120 $4,028,225 $4,578,720 $5,234,898 $14,045,963 $11,583,264
Microsoft Foundry Cost

Evidence and data. Foundry costs are typically consumption based and will vary based on which Foundry services are used.

  • There is no direct charge for Foundry Agent Service, but users are charged for AI agents developed within Foundry based on the inference cost of each agent (the number of input and output tokens required by the agent).

  • Foundry Models offers two pricing options. The first option is a consumption-based model that allows users to pay based on which AI models they select and the number of input and output tokens required. The second option offers provisioned throughput units, where costs are based on the fixed throughput per AI model hour.

  • Foundry IQ costs vary and are primarily based on vector storage (cost per GB), the volume of data retrieval queries, and whether the queries require interaction with an AI model (if so, there is an additional cost per input/output token).

  • Foundry Tools are APIs integrated with Foundry and pricing will vary by API.

  • Azure Machine Learning charges apply only for underlying compute resources used during model training or inference. Options for machine type include general-purpose CPUs and specialized GPUs.

  • Foundry Control Plane includes Foundry Observability and Azure AI Content Safety. Foundry Observability pricing is based on the input and output tokens for evaluation. The Content Safety cost is based primarily on the number of text records processed but is included for free with Foundry direct models.

  • Please contact Microsoft for additional details on pricing for these and other Foundry services.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • The composite organization uses multiple tools within Microsoft Foundry and pays Microsoft based on usage. The tools include Foundry Agent Service, Foundry Models, Foundry IQ, Foundry Tools, Azure Machine Learning, and Foundry Control Plane. The cost to use Foundry increases over time as the composite organization uses Foundry more extensively.

  • The composite organization requires 300 billion AI model tokens in Year 1 for inference across AI model and agents, increasing to 432 billion by Year 3 as the composite organization’s usage expands. The composite organization stores 30 TB of raw vector data for AI model fine-tuning and agent queries. These assumptions drive the expected Foundry inference and storage costs.

  • Other costs include the cost for Foundry Tools and any additional Foundry services.

Risks. The cost of Microsoft Foundry will vary based on:

  • Which products within the Foundry platform are used.

  • Underlying compute and storage requirements.

  • Volume of AI model fine-tuning and third-party AI model usage.

  • Number of AI agents and use cases developed with Foundry.

Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $8.2 million.

Microsoft Foundry Cost
Ref. Metric Source Initial Year 1 Year 2 Year 3
F1 Estimated AI model tokens for AI models and agent inference (millions) Composite   300,000 360,000 432,000
F2 Cost per 1 million tokens Composite   $5.00 $5.00 $5.00
F3 Inference cost F1*F2   $1,500,000 $1,800,000 $2,160,000
F4 Storage (TB) Composite   30 36 43
F5 Vector storage cost per GB per day Composite   $0.11 $0.11 $0.11
F6 Data compression rate Composite   50% 50% 50%
F7 Vector storage cost F4*F5*F6*1,000*365   $602,250 $722,700 $863,225
F8 Other Foundry services Composite   $400,000 $480,000 $576,000
Ft Microsoft Foundry cost F3+F7+F8 $0 $2,502,250 $3,002,700 $3,599,225
  Risk adjustment ↑10%        
Ftr Microsoft Foundry cost (risk-adjusted)   $0 $2,752,475 $3,302,970 $3,959,148
Three-year total: $10,014,593 Three-year present value: $8,206,543
Implementation And Maintenance

Evidence and data. The interviewees found it easy to implement Foundry. Their technical teams were able to begin using Foundry quickly and the learning curve was straightforward.

  • The partner, genAI at an AI software organization described how the process to move to Foundry at their organization took 1.5 months. The technical team moved one AI agent use case to Foundry and benchmarked the results with their prior solution. The test was successful, and they then brought more solutions into Foundry.

  • The CEO at an AI software organization shared that two technical team members at their organization evaluated the Foundry solution internally, after which it took only a few days to implement Foundry.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

  • The composite organization spends two months piloting, testing, and implementing Foundry. It dedicates five technology team FTEs to the Foundry pilot and installation.

  • It dedicates five technical team FTEs to maintaining the Foundry platform.

  • The average fully burdened annual salary for a technical team member is $243,000.

Risks. The implementation and maintenance cost will vary based on:

  • The skill of an organization’s technical team.

  • An organization’s prior solution.

Results. To account for these risks, Forrester adjusted this cost upward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.4 million.

2 months

Time to pilot and test Foundry

“The shift to Foundry was not drastic. The learning aspect was quite straightforward.”

Principal architect, AI software

Implementation And Maintenance
Ref. Metric Source Initial Year 1 Year 2 Year 3
G1 Implementation   0.8      
G2 Ongoing maintenance     5.0 5.0 5.0
G3 Fully burdened annual salary for a technical team FTE   $243,000 $243,000 $243,000 $243,000
Gt Implementation and maintenance (G1+G2)*G3 $194,400 $1,215,000 $1,215,000 $1,215,000
  Risk adjustment ↑5%        
Gtr Implementation and maintenance (risk-adjusted)   $204,120 $1,275,750 $1,275,750 $1,275,750
Three-year total: $4,031,370 Three-year present value: $3,376,721

Financial Summary

Consolidated Three-Year, Risk-Adjusted Metrics

Cash Flow Chart (Risk-Adjusted)

[CHART DIV CONTAINER]
Total costs Total benefits Cumulative net benefits Initial Year 1 Year 2 Year 3
Cash Flow Analysis (Risk-Adjusted)
  Initial Year 1 Year 2 Year 3 Total Present Value
Total costs ($204,120) ($4,028,225) ($4,578,720) ($5,234,898) ($14,045,963) ($11,583,264)
Total benefits $0 $10,048,305 $21,089,060 $30,467,932 $61,605,297 $49,454,807
Net benefits ($204,120) $6,020,080 $16,510,340 $25,233,035 $47,559,335 $37,871,543
ROI           327%
Payback           <6 months

 Please Note

The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the composite organization’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.

These risk-adjusted ROI, NPV, and payback period values are determined by applying risk-adjustment factors to the unadjusted results in each Benefit and Cost section.

The initial investment column contains costs incurred at “time 0” or at the beginning of Year 1 that are not discounted. All other cash flows are discounted using the discount rate at the end of the year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations in the summary tables are the sum of the initial investment and the discounted cash flows in each year. Sums and present value calculations of the Total Benefits, Total Costs, and Cash Flow tables may not exactly add up, as some rounding may occur.

From the information provided in the interviews and survey, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Microsoft Foundry.

The objective of the framework is to identify the cost, benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that Microsoft Foundry has on an organization.

Due Diligence

Interviewed Microsoft stakeholders and Forrester analysts to gather data relative to Microsoft Foundry.

Interviews And Survey

Interviewed 10 decision-makers at five organizations and surveyed 154 respondents at organizations using Microsoft Foundry to obtain data about costs, benefits, and risks.

Composite Organization

Designed a composite organization based on characteristics of the interviewees’ and survey respondents’ organizations.

Financial Model Framework

Constructed a financial model representative of the interviews and survey using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewees and survey respondents.

Case Study

Employed four fundamental elements of TEI in modeling the investment impact: benefits, costs, flexibility, and risks. Given the increasing sophistication of ROI analyses related to IT investments, Forrester’s TEI methodology provides a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.

Total Economic Impact Approach
Benefits

Benefits represent the value the solution delivers to the business. The TEI methodology places equal weight on the measure of benefits and costs, allowing for a full examination of the solution’s effect on the entire organization.

Costs

Costs comprise all expenses necessary to deliver the proposed value, or benefits, of the solution. The methodology captures implementation and ongoing costs associated with the solution.

Flexibility

Flexibility represents the strategic value that can be obtained for some future additional investment building on top of the initial investment already made. The ability to capture that benefit has a PV that can be estimated.

Risks

Risks measure the uncertainty of benefit and cost estimates given: 1) the likelihood that estimates will meet original projections and 2) the likelihood that estimates will be tracked over time. TEI risk factors are based on “triangular distribution.”

Financial Terminology
Present value (PV)

The present or current value of (discounted) cost and benefit estimates are given at an interest rate (the discount rate). The PVs of costs and benefits feed into the total NPV of cash flows.

Net present value (NPV)

The present or current value of (discounted) future net cash flows given an interest rate (the discount rate). A positive project NPV normally indicates that the investment should be made unless other projects have higher NPVs.

Return on investment (ROI)

A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.

Discount rate

The interest rate used in cash flow analysis to take into account the time value of money. Organizations typically use discount rates between 8% and 16%.

Payback

The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.

Appendix A

Total Economic Impact

Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.

Appendix B

Survey Demographics
[CONTENT]
 ROLE  
C-level executive 11%
Vice president 16%
Director 30%
Manager 43%
[CONTENT]
INDUSTRY  
Financial services and/or insurance 10%
Retail 10%
Technology and/or technology services 10%
Healthcare and life sciences 7%
Manufacturing and materials 6%
Telecommunication services 6%
Business or professional services 5%
Media and/or leisure 5%
Electronics 5%
Other 37%
[CONTENT]
ANNUAL REVENUE  
$1 million to $199 million 5%
$200 million to $299 million 9%
$300 million to $399 million 14%
$400 million to $499 million 24%
$500 million to $999 million 22%
$1 billion to $5 billion 14%
 > $5 billion 12%
[CONTENT]
GEOGRAPHY  
United States 44%
Canada 21%
United Kingdom 13%
Germany 8%
France 6%
The Netherlands 6%

Note: Percentages may not total 100 due to rounding.

Appendix C

Supplemental Material

Related Forrester Research

Agentic AI Glossary, Forrester Research, Inc., October 8, 2025.

Predictions 2026: Cloud Computing, Forrester Research, Inc., October 21, 2025.

Appendix D

Endnotes

1 Forrester defines agentic AI as “systems of foundation models, rules, architectures, and tools that enable software programs to flexibly plan and adapt to resolve goals by taking action in their environment, with increasing levels of autonomy.” Source: Agentic AI Glossary, Forrester Research, Inc., October 8, 2025.

2 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.

3 Source: Stern School of Business at NYU.

Disclosures

Readers should be aware of the following:

This study is commissioned by Microsoft and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.

Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the study to determine the appropriateness of an investment in Foundry. For any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect’s business. Forrester believes that this analysis is representative of what companies may achieve with Foundry based on the inputs provided and any assumptions made. Forrester does not endorse Microsoft or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, Microsoft and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein. The interactive tool is provided ‘AS IS,’ and Forrester and Microsoft make no warranties of any kind.

Microsoft reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.

Microsoft provided the customer names for the interviews but did not participate in the interviews.

Forrester fielded the double-blind survey using a third-party survey partner.

Consulting Team:

Jennifer Adams
Amanda Alberts

Published

February 2026

 

ABOUT FORRESTER CONSULTING

Forrester provides independent and objective research-based consulting to help leaders deliver key transformation outcomes. Fueled by our customer-obsessed research, Forrester’s seasoned consultants partner with leaders to execute on their priorities using a unique engagement model that tailors to diverse needs and ensures lasting impact. For more information, visit forrester.com/consulting.

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The Total Economic Impact™ Of Microsoft Foundry

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