PwC Commercial and Professional Services Global

PwC

Enterprise Knowledge Search · IT Operations Automation

PwC needed to deploy generative AI across a global network in a way that improved everyday productivity while preserving local compliance, strong governance, and enterprise security.

1M+ hours of capacity created during the month of April 2026
20M+ Copilot actions during the month of April 2026
285,000+ global users across territories
54% of PwC’s global workforce using AI tools weekly

Reported impact

Business outcome

PwC operationalized one of the world’s largest Copilot deployments, generating more than 20 million monthly actions, over 1 million hours of capacity in one month, and a governed foundation for ongoing AI adoption across the network.

  • Productivity Improvement
  • Scalability

Solution

PwC turned Microsoft Copilot into a governed enterprise AI layer rather than a standalone productivity pilot. Working with Microsoft, the firm embedded Copilot into the Microsoft 365 environment its people already use, then rolled it out across more than 100 countries using a decentralized operating model. Territory teams could choose configurations that matched local regulatory and operational needs, while a hub-and-spoke governance model, global knowledge center, and sharing framework kept standards consistent. PwC also built dashboards from Microsoft data sources to track adoption, usage, efficiency gains, and behavior across Teams, Outlook, and later Copilot Studio agent reporting. Role-based training, prompt campaigns, and feedback loops refined how agents and features were used in practice. The result is one of the world’s largest Copilot deployments, with Responsible AI, local data controls, and enterprise security built into the rollout rather than bolted on later.

Data flow

Work content and Microsoft-provided data sources remain inside PwC’s Microsoft 365 estate, where Microsoft Copilot surfaces assistance within Teams, Outlook, and related applications. Usage and adoption data feed PwC-built dashboards, and local territory configurations plus governance controls determine how agents and features are deployed across the global network.

Solution architecture

5 components · 2 layers
  1. Serving
    • Microsoft Copilot Acts as the primary AI assistant embedded across PwC’s day-to-day work environment.
    • Microsoft 365 Provides the enterprise productivity environment into which Copilot was deployed at scale.
    • Microsoft Teams Supplies collaboration context and one of the main applications where Copilot usage is monitored.
    • Microsoft Outlook Provides communication context and another primary surface for Copilot adoption and workflow integration.
  2. Orchestration
    • Copilot Studio Supports the evolution of agent reporting and the next layer of Copilot-based automation.

Architecture clues

  • A hub-and-spoke governance model balanced territory autonomy with global standards.
  • PwC built dashboards to monitor Teams, Outlook, and other Microsoft application usage.
  • Role-based training included prompt-of-the-day campaigns and responsible-AI guidance.
  • The rollout began in 11 countries using a decentralized model.

Evidence from the source

AI agents now help research teams extract data from complex files in seconds, freeing PwC employees to focus on higher-value insights.
During the month of April 2026, PwC employees executed over 20M million actions in Copilot, freeing up over 1M hours of capacity in the process.
Today, Copilot isn’t just an assistant. It’s an integrated AI framework that powers smarter, faster, and more trusted work—for PwC and for our clients.
With 54% of PwC’s global workforce using AI tools weekly, employees average nine prompts per week.
With over 285,000 users in 100+ countries, we have built one of the world’s largest Copilot deployments—driving productivity, enhancing collaboration, and embedding trust throughout multiple workflows.
Transparency Evidence & methodology 100/100 reference value · 85% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. PwC

    PwC deploys Microsoft Copilot at enterprise scale: PwC

    First-party
    https://www.pwc.com/us/en/library/case-studies/pwc-microsoft-copilot-enterprise-ai.html
    Source type
    Vendor-published customer story
    Published
    Jan 16, 2026
    Supports
    • Customer
    • Region
    • Company size
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • Business outcome
    • Metrics
    • Architecture
    • Publication date
    • evidence quotes

Date evidence

  • First archived Jan 17, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jun 23, 2026 · PwC · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Jan 16, 2026 · PwC · Unknown Legacy extracted date without source-page confirmation.
    Open date source
Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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