The Total Economic Impact™ Of Migrating To Microsoft Azure For AI-Readiness

Business Benefits Enabled By Migrating To Azure For AI-Readiness

A Forrester Total Economic Impact Study Commissioned By Microsoft, June 2024

Artificial intelligence (AI) is transforming the world of business, and organizations are eager to invest in technologies that allow them to take advantage of this rapidly evolving technology. Having the right infrastructure to support AI is a critical consideration for organizations as they evaluate their need for scale, stability, and flexibility today and the potential for change moving forward.1 Forrester found that migrating from on-premises infrastructure to Azure can support AI-readiness in organizations with lower costs to stand up and consume AI services plus improved flexibility and ability to innovate with AI.

The Azure cloud platform comprises more than 200 products and services to help build, run, and manage applications and provides purpose-built, AI-infused infrastructure. Microsoft’s “Migrate to innovate” approach helps organizations migrate to products such as Windows Server, Azure SQL, Azure VMware Solution, and Azure Arc to support innovation initiatives.

Microsoft commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential benefits and financial impacts enterprises may realize by migrating to Azure for AI readiness.2

To better understand the benefits and risks associated with this solution, Forrester interviewed seven representatives at five organizations and surveyed 322 respondents with experience deploying AI and machine learning (ML) either with on-premises infrastructure or on Azure cloud infrastructure. For the purposes of this study, Forrester aggregated the experiences of the interviewees and survey respondents and combined the results into a composite organization that is an enterprise that uses AI and ML.

Most of the interviewees’ organizations migrated to Azure from on-premises infrastructure while a minority moved to Azure from other cloud providers. The interviewees said their organizations previously struggled with stability, scalability, the capital costs of infrastructure, and challenges with end-of-life legacy systems. They noted their organizations spent a great deal of time managing infrastructure rather than supporting strategic business solutions, and they theorized that the time, effort, and expertise required to pursue current AI/ML efforts would not have been feasible in the prior environments.

There are many benefits associated with migrating to the cloud, and Forrester has detailed those associated with migrating to Azure in other TEI studies, some of which can be found in Appendix C.

Interviewees for this study noted improved stability and scalability and reduced costs. Focusing on AI, they explained that migrating to Azure infrastructure enabled their organizations to take advantage of AI technology in more ways than they had anticipated. They said it promoted a culture of innovation that allowed them to reinvest in and upskill resources previously focused on infrastructure to instead focus on new AI initiatives, and provided the flexibility to build and change AI applications with lower risk than they may have had previously. These findings are supported by survey data that shows significantly higher confidence in the flexibility and ability to innovate with Azure infrastructure compared to on-premises infrastructure.

“The cloud has given us the ability to enable a lot of capabilities that we couldn’t have easily enabled in the past. We’ve been able to spin up instances, for instance, using AI. We didn’t really have that capability before.”

Head of cloud security, banking

Key Findings

Benefits. Benefits for the composite organization include:

  • Reduced costs to deploy and operate AI and ML. The composite organization deploys AI use cases for $558,000 less over three years than if they deployed on-premises.
    • Deployment costs are 17% lower for AI and ML on Azure cloud than they would be with on-premises infrastructure.  
    • Ongoing costs are 15% lower to enable and maintain AI and ML on Azure cloud than they would be with on-premises infrastructure.
  • Ability to scale and innovate AI and ML. The composite organization sees benefits in this area. When survey respondents were asked about their organizations’ flexibility to build and improve AI and ML applications and innovate, those from organizations on Azure cloud responded confidently at more than twice the rate of those from organizations with on-premises infrastructure.
    • Ninety percent of survey respondents from organizations with Azure infrastructure agreed or strongly agreed they have the flexibility to build new AI and ML applications compared to 43% from organizations with on-premises infrastructures.
    • Eighty-one percent of survey respondents from organizations with Azure infrastructure agreed or strongly agreed they have the flexibility to change and improve AI and ML applications compared to 25% from organizations with on-premises infrastructure.
    • Seventy-seven percent of survey respondents from organizations with Azure infrastructure agreed or strongly agreed their current environment makes it easy to innovate with AI/ML compared to 34% from organizations with on-premises infrastructure.
  • New employee and organizational opportunities. Migrating to Azure changes business needs for the organization and brings a culture of innovation.
    • The composite organization can invest in training resources previously focused on infrastructure management to build new capabilities around cloud technology and AI.
    • Moving to Azure provides access to new resources and capabilities that make it easy for people to test new technologies.

“When it comes to AI, you can’t get anything better than what Microsoft offers out there at all. … [Microsoft] made their AI strategy really easy to adopt for many different things. Even in the early days … it was just so easy to test and play with. The ease with which someone can get into something that is profoundly technical is almost gimmicky. [Microsoft is] very smart that way, and that’s worked for us.”

Head of R&D, technology

Key Statistics

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    Benefits PV:

    $558K
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    Lower costs to deploy AI & ML on Azure cloud:

    17%
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    Lower costs to enable and maintain AI & ML on Azure cloud:

    15%
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Azure Cloud Enables AI And ML Innovation And Scale

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Base: 218 IT decision-makers at global enterprise organizations
Source: A commissioned study conducted by Forrester Consulting on behalf of Microsoft, May 2024

TEI Framework And Methodology

From the information provided in the interviews and survey, Forrester constructed a Total Economic Impact™ framework for those organizations considering migrating to Azure for AI readiness.

The objective of the framework is to identify the benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that migrating to Azure for AI readiness can have on an organization.

  1. Due Diligence

    Interviewed Microsoft stakeholders and Forrester analysts to gather data relative to migrating to Azure for AI readiness.

  2. Interviews And Survey

    Interviewed seven representatives at five organizations with experience migrating to Azure and using AI/ML and surveyed 322 respondents at organizations with experience deploying AI/ML either on-premises or on Azure infrastructure to obtain data with respect to benefits and risks.

  3. Composite Organization

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

  4. 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.

  5. Case Study

    Employed fundamental elements of TEI in modeling the investment impact: benefits, flexibility, and risks. Given the increasing sophistication of 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.

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 benefits 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 migrating to Azure for AI readiness.

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:

Elizabeth Preston

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