Enterprise AI
EY Achieves 70% Effort Savings in App Development with Microsoft Copilot
The professional services firm scaled Microsoft 365 Copilot across 150,000 users to deliver measurable productivity gains, with plans to extend agentic AI capabilities to its full global workforce.
EY's Microsoft 365 Copilot rollout is a large-scale enterprise AI deployment in the professional services sector that has resulted in substantial effort savings in application development.
Executive Summary
EY, a major player in the professional services sector, deployed Microsoft 365 Copilot to support its consultants in daily tasks including software development. The AI platform was introduced internally as a test bed for capabilities that could later extend to clients. The primary quantified outcome is a 70% effort savings in 50% of new application development projects.
The initial phase reached 150,000 users and generated a 15% productivity increase. Gains from this phase were directed back into client delivery and employee learning programs. EY now extends the platform through Microsoft 365 E7: The Frontier Suite to reach more than 400,000 people globally.
These results establish EY as the largest global consumer of Microsoft 365 Copilot by license count. More than 12 million lines of GitHub code and over 9 million prompts have been accepted. Employee feedback shows 92% intend to keep using the tools on a regular basis.
Background and Context
Professional services firms have historically depended on labor-intensive processes for client engagements in accounting, consulting, and technology advisory. EY treated its own operations as Client Zero to validate AI tools before broader client recommendations. The Microsoft partnership supplies the technical foundation while EY contributes sector-specific change management.
Application development previously required extensive manual coding and review cycles. Introduction of AI assistance targets repetitive elements of this work to free consultant time. The move aligns with industry-wide efforts to adopt digital tools that improve speed without sacrificing quality.
The global initiative announced by the two companies focuses on moving clients past pilot stages into enterprise-wide AI use. EY internal data serves as evidence that scaled deployment can produce measurable returns. This context explains why the firm prioritized Microsoft 365 Copilot for its own workforce first.
Tens of thousands of US consultants form part of the broader 150,000-user base. The scale demonstrates feasibility for organizations with distributed teams. Results from this rollout inform how similar firms might structure their own AI programs.
Deployment Details
Microsoft 365 Copilot licenses were issued to 150,000 users in the first wave of adoption. Usage data showed immediate application in software development workflows. Half of all new application projects began incorporating the AI assistant.
Effort required for those projects dropped by 70% once Copilot was in use. The platform assists with code suggestions, documentation, and routine debugging. Integration with existing Microsoft 365 and GitHub environments allowed seamless workflow adoption.
Following initial results, EY activated Microsoft 365 E7: The Frontier Suite for wider access. This step adds deeper agentic functions that can act on user instructions with greater autonomy. The expansion targets the complete workforce exceeding 400,000 individuals.
Usage metrics include acceptance of more than 12 million lines of GitHub code and over 9 million prompts. These figures reflect active engagement rather than passive licensing. The numbers position EY as the top Copilot consumer worldwide by volume.
Technical Specifics
Microsoft 365 Copilot runs inside the Microsoft 365 suite and draws on large language models to generate context-aware suggestions. In application development, it proposes code snippets and helps refactor existing modules. Direct connection to GitHub repositories enables one-click acceptance of recommended changes.
Agentic features allow the AI to execute multi-step tasks when guided by users. EY embeds these capabilities to handle repetitive elements of client projects. The Frontier Suite supplies the infrastructure for these advanced functions at enterprise scale.
Data handling follows enterprise compliance requirements typical in professional services. Access controls and audit trails maintain oversight of AI-generated outputs. This technical configuration supports the reported productivity and effort metrics without introducing new security exposures.
Quantified Business Outcomes
The standout result is the 70% reduction in effort for 50% of new application development work. This translates directly into lower hours spent per project. Resources previously allocated to routine coding can shift to client-facing or strategic activities.
The 15% productivity lift recorded after the 150,000-user deployment was reinvested into client service delivery and internal training. This approach multiplies the value beyond simple cost avoidance. Sustained use across the expanded user base is expected to compound these effects.
| Metric | Initial Deployment | Scaled Impact |
|---|---|---|
| Users with Access | 150,000 | More than 400,000 |
| Productivity Increase | 15% | Reinvested into operations |
| Application Development Effort Reduction | Baseline | 70% in 50% of projects |
| GitHub Code Accepted | Over 12 million lines | Ongoing |
| Prompts Accepted | More than 9 million | Ongoing |
These figures provide concrete benchmarks for other enterprises evaluating similar tools. The combination of code volume and prompt acceptance indicates practical utility rather than experimental use. Employee intent to continue usage at 92% supports long-term retention of the gains.
Market and Stakeholder Implications
The professional services sector can reference this deployment when assessing AI investments. Other firms may adopt comparable license volumes and measurement frameworks. Emphasis on agentic AI points to future stages of automation beyond basic assistance.
Clients of EY gain from faster internal development cycles that can accelerate solution delivery. The alliance structure supplies both technical engineering and domain expertise in one coordinated team. This model may influence how other service providers structure technology partnerships.
Movement from experimentation to scaled deployment changes expectations for AI program maturity. Organizations can use the reported metrics to set internal targets. The approach of reinvesting productivity gains offers one template for realizing broader organizational value.
C-suite leaders in knowledge industries should examine the user adoption rate and effort savings when planning their own initiatives. High employee willingness to continue use suggests lower change-management friction. The data offers a reference point without requiring identical industry conditions.
Leadership Perspectives
EY leadership has framed the Microsoft relationship as a means to combine technical capability with industry knowledge. The internal results serve as validation for client-facing recommendations. Continued scaling reflects confidence in the measured outcomes.
Together with Microsoft, EY is supporting clients to unlock value through rapid deployment of AI at scale. With access to a single, integrated team, clients will have at their disposal both Microsoft’s market-leading engineering depth, alongside EY teams’ deep industry knowledge and change management capabilities. By combining people and innovation in this next phase of the Alliance, clients will be empowered to realize the transformative power of agentic AI within the enterprise.Janet Truncale, EY Global Chair and CEO
The statement emphasizes rapid deployment and integrated support as differentiators. It ties internal success to the ability to assist external clients with similar transformations.
What's Next
EY intends to broaden Copilot and agentic features across remaining workforce segments. Ongoing measurement of development metrics will track additional gains. Expansion of use cases beyond application development is under consideration.
The firm will monitor acceptance rates for code and prompts as the user base grows. Integration of newer agentic functions will target additional workflow areas. These steps build on the foundation established by the initial 150,000-user cohort.
Peer organizations can draw from the documented sequence of deployment, measurement, and reinvestment. The following ordered list summarizes core phases observed in the EY program.
- Establish baseline productivity measures in target functions such as application development.
- Issue licenses to an initial cohort and track usage and output metrics.
- Calculate productivity changes and redirect gains into client work or training.
- Extend access through advanced licensing tiers to the full employee population.
- Incorporate agentic capabilities to automate additional task categories.
Frequently asked
What specific productivity gains has EY reported from its Copilot deployment?
EY recorded a 15% productivity boost from the initial deployment to 150,000 users, with 50% of new application development seeing 70% effort savings.
How many users does EY plan to reach with the scaled rollout?
EY is scaling Microsoft 365 Copilot and agentic capabilities to more than 400,000 people worldwide via the Microsoft 365 E7 suite.
Sources
- EY — EY is the #1 Copilot consumer across the globe: 150,000 Microsoft 365 Copilot licenses; Over 12m lines of GitHub code accepted and more than 9m prompts accepted; 50% of new application development is benefiting from Copilot, saving 70% in effort; 92% of EY employees expressed a desire to continue using their tools regularly.
- Microsoft — EY initially deployed Copilot to 150,000 Copilot users, recording a 15% boost in productivity that was reinvested into client delivery and learning. EY is also scaling Copilot through Microsoft 365 E7: The Frontier Suite, to its more than 400,000 people around the world, embedding agentic AI capabilities across the enterprise to drive business impact.