Levi Strauss & Co. transformed slow, inconsistent workflows by standardizing on modern Windows 11 devices managed with Microsoft Intune and powered by Microsoft 365 Copilot and Copilot+ PCs. Together, these tools eliminated device crashes, unified access to apps and data, and created a consistent, AI-ready experience for every employee.
Before its AI push, Levi Strauss & Co. had a classic enterprise problem: great ambitions, fragile tools. Employees joined meetings in different ways, requested applications through inconsistent processes, and wasted time just getting basic workflows to function. Finance teams working with 20,000-line spreadsheets routinely crashed their laptops and lost work, which killed momentum and eroded trust in IT.
Direct-to-consumer growth only made this worse. The shift created a flood of new data from retailers, loyalty programs, and digital channels. Finance managers like Ryan Katreeb needed to summarize huge datasets into monthly reports, but their devices couldn’t cope. He cycled through multiple machines, yet every month the same story repeated: freezes, crashes, and anxiety about losing data mid-report.
The problem wasn’t just annoying—it was strategic. Leaders like Derek Shirk and Jason Gowans were trying to build a “fan-obsessed” retail model, where decisions are driven by data and made quickly. But if staff can’t even open the data without crashing, you can’t become an AI-powered, real-time organization. Inconsistent device builds and fragmented endpoint management also made it hard to roll out new tools at scale.
Levi’s first decisive move was to create a consistent device and management baseline with Microsoft Intune across all endpoints. Instead of one-off images and local tweaks, every new laptop would now enroll into Intune, apply standard policies, and install the right applications automatically on first sign-in. Wherever an employee was in the world, they’d have essentially the same secure, modern workspace.
This consolidation enabled a smooth upgrade to Windows 11 as the company-wide standard. Intune gave IT granular visibility into device health, app deployment, and compliance, so future planning and reporting became much easier. Just as important, it gave the business a stable, modern canvas on which to layer AI, rather than bolting new capabilities onto outdated hardware.
With that foundation in place, Levi’s made its second big bet: Surface Copilot+ PCs for staff whose work depends on heavy data and constant collaboration. These devices ship with AI-specialized NPUs and tight integration with Microsoft 365 Copilot in Windows 11, so they can crunch large spreadsheets, handle complex multitasking, and keep battery life high for mobile workers.
For employees like Katreeb, the difference was dramatic. His Surface Copilot+ PC handled his finance workloads without crashing, even when he pulled together tens of thousands of rows of data into consolidated reports. He described the experience as “phenomenal,” noting reduced anxiety, no data loss, and a laptop that stayed light, fast, and reliable throughout the day.
Crucially, Copilot wasn’t yet another standalone tool to learn. With Microsoft 365 Copilot embedded directly into Windows 11 and everyday apps like Excel, PowerPoint, and Teams, it became part of the normal workflow. Features like a dedicated Copilot key meant that help with summarizing data, drafting content, or answering questions was just one click away.
This combination—standardized devices, centralized management, modern OS, and integrated AI—is what created Levi’s real turning point. Instead of spending cycles fighting their tools, employees could focus on designing better fan experiences, optimizing inventory, and accelerating decision-making. The technology finally matched the ambition.
Levi Strauss & Co. cut project timelines from a year to a single day by pairing Copilot+ PCs, Microsoft 365 Copilot, and Intune-managed Windows 11 devices, allowing teams to build agents that analyze thousands of documents and large datasets automatically instead of relying on manual, error-prone work.
Once Levi’s had Copilot+ PCs and Intune-managed Windows 11 devices in place, the company could start using Microsoft 365 Copilot for more than day-to-day productivity boosts. Teams began building Copilot-powered agents focused on specific business problems, especially those involving large volumes of unstructured content.
One finance-led initiative shows the impact clearly. Lisa Stirling and her team needed to audit thousands of Standard Operating Procedure (SOP) documents across the company to find redundancies and simplification opportunities. Done manually, this audit would have consumed up to a full year of work—and, as Stirling put it, “a painful one” for everyone involved.
Instead of assigning people to read and categorize documents line by line, the team used Copilot to help create an agent that could ingest and analyze the SOPs. The agent surfaced duplicative or outdated content and flagged candidates for simplification. Thanks to the computing power of Copilot+ PCs and the secure access foundation provided by Intune and Windows 11, the analysis ran at machine speed.
The result: work that was budgeted mentally as a year-long slog came back with useful results in about one day. That step change in timeline isn’t a one-off efficiency gain; it reshapes how leaders think about what’s possible. Instead of avoiding large-scale cleanups and documentation projects, they can now explore them proactively because the cost in time and attention has plummeted.
Another example is the internal benefits assistant dubbed “Ask Ben.” Sheena Kunhiraman and her People Systems team used Copilot on Windows to design an agent that helps employees navigate complex benefits information. Previously, staff would dig through intranet pages, PDFs, or email threads to answer simple questions about coverage, eligibility, or policies. Each request was a small friction point that pulled HR away from higher-value work.
“With Copilot on Windows, building an agent was so simple that my team went from concept to presenting a demo to the executive team in three weeks,” Kunhiraman explained in the Microsoft case study. That speed—from idea to live demo in under a month—shows how the combination of AI tooling and standardized infrastructure lowers the barrier to experimentation.
For workers across Levi’s, Copilot quickly became part of the flow of work. Finance staff could ask Copilot in Excel to summarize trends in those 20,000-line datasets. UX and product teams could use Copilot to turn unstructured meeting notes into structured action items. HR could generate draft communications tailored to specific regions or roles.
Beyond Levi’s, early-user research from Microsoft shows the productivity impact at scale. According to Microsoft’s own studies, around 70% of users say Copilot makes them more productive and 68% report that it improves the quality of their work. External analysis from companies like Panto.ai notes that Microsoft has disclosed more than 20 million paid Microsoft Copilot seats and that over 90% of the Fortune 500 now use Copilot, underscoring how quickly enterprises are adopting the technology.
The hardware side matters too. Microsoft reports that Copilot+ PCs can be up to five times faster than the most popular 5-year-old Windows PCs still in use, with all-day battery life and specialized NPUs for AI workloads. For organizations still running older devices, Levi’s experience is a concrete example of why pairing AI software with AI-capable hardware changes the game: without constant crashing and lag, you can trust Copilot to run heavy analysis in the background while you keep working.
All of this is possible because Intune, Windows 11, and Copilot+ PCs provide a governed, secure environment in which to deploy AI. IT keeps control of device compliance, app access, and data protection, while business teams gain the freedom to spin up agents that solve local problems fast. That balance of control and agility is what lets timelines collapse from months to days without increasing risk.
IT and business leaders can replicate Levi’s success by first standardizing endpoint management with Intune, upgrading to Windows 11 and Copilot+ PCs, and then targeting high-friction workflows where Microsoft 365 Copilot and simple agents can deliver outsized time savings.
The core pain point Levi’s solved—slow, fragile, inconsistent work environments—is common to many mid-market and enterprise organizations. If your teams are wrestling with crashing apps, manual reviews, and scattered data, the Levi’s story offers a practical template rather than a one-off outlier.
The first lesson is to treat endpoint modernization as a prerequisite for AI, not an afterthought. Deploying Microsoft Intune across all endpoints gave Levi’s a single pane of glass for device management, security policies, and application delivery. For IT leaders, this means fewer edge cases, easier reporting, and the ability to roll out new capabilities like Copilot consistently instead of in fragmented pilots.
At the same time, making Windows 11 the standard OS ensured that all employees have access to the latest security features and native integration points for Copilot. Features like a dedicated Copilot key on Copilot+ PCs move AI assistance from “extra step” to “muscle memory,” encouraging adoption without formal change management campaigns.
The second lesson is to be deliberate about where you point AI first. Levi’s didn’t start by trying to “AI everything.” Instead, they focused on work that was clearly painful and clearly document-heavy: SOP audits, benefits Q&A, and finance reporting. These areas shared a few common traits—large content sets, repetitive logic, and low current satisfaction—making them ideal candidates for AI agents.
For example, if your finance function manually reconciles data from multiple systems in spreadsheets, start by giving those analysts Copilot+ PCs and Copilot in Excel. Track measures like time-to-close, error rates, and employee sentiment. Similarly, if HR fields lots of policy questions by email, consider an internal Copilot agent like Ask Ben that can safely reference your policies and surface clear answers.
The third lesson is organizational: pair business ownership with IT guardrails. At Levi’s, HR, finance, and UX all participated in designing agents, while technology leaders ensured that devices, data access, and compliance were handled properly. You can mirror this by forming cross-functional AI pods that include process owners, power users, and IT partners.
To reduce risk, look at the emerging Copilot Control System capabilities from Microsoft, which are designed to help enterprises govern how Copilot is deployed, secure sensitive data, and understand usage and impact. Combined with Intune, these controls help you scale AI responsibly without losing visibility.
Finally, keep the customer—or in Levi’s language, the fan—at the center. The point of faster SOP audits and smoother benefits Q&A isn’t only internal efficiency; it’s enabling your people to spend more time on high-value work that improves customer experience. As Derek Shirk put it, Copilot is a tool that gets Levi’s closer to a “fan-obsessed model” by enabling faster, better decisions across the business.
If you follow a similar playbook—modernize devices and management, deploy Copilot where pain is highest, empower teams to build agents, and wrap it all in strong governance—you can move complex projects from “maybe someday” to “done this week.” Levi’s has shown that with the right AI foundation, even year-long efforts can realistically shrink to a single day.