Copilot+ PCs helped Levi Strauss & Co. move from fragile, crashing laptops to a consistent, AI-ready device experience that supports heavy data workloads, embedded Microsoft 365 Copilot, and faster decision-making. By standardizing powerful hardware, Levi’s removed friction from daily work and created a stable foundation for AI agents and automation.
Levi’s is a 175‑year‑old brand operating in more than 120 countries, with over 50,000 retail partners and 40 million members in its Red Tab loyalty program, according to Microsoft WorkLab. That scale created a huge data challenge: finance, HR, merchandising, and retail teams all needed devices that could handle complex workloads without slowing down.
Before modernizing, some employees were cycling through multiple PCs because none could handle their reporting needs. One finance manager at Levi’s worked with around 20,000 lines of data each month, and his machine often crashed in the middle of building reports, leading to lost data and serious frustration. This is exactly the scenario many growing businesses face: the business becomes data‑driven before the endpoint strategy catches up.
Levi’s responded by rolling out Surface Copilot+ PCs across its workforce. These AI‑focused devices pair fast Neural Processing Units (NPUs) with long battery life and modern security features. With Microsoft 365 Copilot built directly into Windows 11 and everyday apps, employees can analyze large datasets, draft summaries, and generate insights without constantly worrying about performance.
The visible change for staff was simple but powerful: workloads that used to “bring laptops to their knees” became routine. Anxiety about crashes dropped, and employees started to see AI as an everyday assistant instead of an extra app they had to remember to open.
Levi’s improvements didn’t start with AI; they started with fixing inconsistent device delivery and management. Before the transformation, onboarding looked different across regions, and users often joined meetings, requested apps, or accessed systems in completely different ways depending on where and how their device was configured.
Levi’s tackled this by deploying Microsoft Intune across all endpoints, as described in Microsoft’s customer story on Levi Strauss & Co. and Windows 11 (Microsoft Customer Stories). Intune gave the company a single, cloud‑based way to enroll, configure, and secure devices at scale.
From the user’s perspective, the new experience is straightforward: no matter where an employee is in the world, they receive a laptop, sign in with their company credentials, and watch as required applications and security policies are pushed automatically. IT does not need to build bespoke images or manually touch every device.
At the same time, Levi’s standardized on Windows 11 as its baseline operating system. Intune made that migration realistic: instead of ad‑hoc upgrades, the IT team could assign Windows 11 to device groups, monitor compliance, and roll out updates in staged waves. The result is a fleet of PCs that share the same security posture, update rhythm, and application catalog.
For mid‑sized organizations, this combination—Intune plus Windows 11—solves a common pain point: “shadow IT builds” and inconsistent provisioning that make troubleshooting nearly impossible. With centralized endpoint management, support tickets become easier to resolve, security baselines are enforceable, and you have the prerequisites to safely deploy AI tools like Copilot+.
Once the device and management foundation was in place, Levi’s leaned into Microsoft 365 Copilot to attack some of its most painful knowledge‑work projects. A standout example: auditing thousands of Standard Operating Procedure (SOP) documents to find overlaps, gaps, and opportunities to simplify.
In a traditional environment, this kind of SOP review would be a brutal, manual project. Lisa Stirling, Vice President of U.S. and Canada Finance at Levi’s, estimated that combing through the full SOP library could take up to a year of effort—and “a painful one,” according to the customer story on Levi’s modern workplace (Microsoft Customer Stories).
Instead, the team used Microsoft 365 Copilot to build an agent that could read, compare, and summarize the documents. With the content centralized and accessible, Copilot identified duplications and simplification opportunities in a single day. The human team still made the final calls, but the heavy lifting shifted from manual reading to AI‑assisted review.
That time compression—from a year to a day—is not just a headline. It represents a completely different way of planning work. Projects that were once “too big to start” suddenly become viable, because the hardest parts can be offloaded to AI running on capable devices.
For smaller businesses, this example is a cue to look for large, text‑heavy processes ripe for automation: policy reviews, contract comparisons, training material audits, or customer email analysis. With the right data access and an AI‑ready device fleet, these projects can move from “someday” to “this quarter.”
Levi’s didn’t stop at one‑off Copilot prompts. Teams began building persistent agents—specialized Copilot experiences tailored to recurring needs in HR, finance, and beyond. Two examples show how they kept these agents grounded in real‑world problems rather than AI experimentation for its own sake.
First, the SOP‑review agent turned a sprawling documentation set into actionable insights on simplification. Second, the HR team created an agent called “Ask Ben” to help employees navigate benefits information. Instead of digging through portals and PDFs, staff can ask natural‑language questions and get instant, policy‑aligned answers.
According to leaders quoted in Microsoft’s Levi’s stories, one of these agents went from concept to an executive‑ready demo in just three weeks (Microsoft WorkLab). That rapid cycle is critical: it proves value quickly, builds trust with stakeholders, and creates internal demand for more agents.
The pattern behind these successes is simple but powerful:
For IT and business leaders, the message is clear—AI agents are most successful when they are built on top of solid device, identity, and content foundations, and when they address one very specific pain point at a time.
You do not need Levi’s size or budget to apply the core elements of its AI strategy. The stack they assembled—Intune, Windows 11, Surface Copilot+ PCs, and Microsoft 365 Copilot—can be right‑sized for mid‑market organizations that want to modernize endpoints and prepare for AI‑driven work.
From the Levi’s case studies on Windows and Surface Copilot+ PCs (Microsoft Customer Stories), a few repeatable lessons emerge:
For a typical 100–500‑employee business, copying this approach means fewer device images to maintain, less time spent troubleshooting outdated laptops, and a clearer path to delivering AI tools safely to every employee.
If your current pain point sounds like Levi’s pre‑transformation—crashing laptops, inconsistent setups, and users skeptical of new tools—the path forward starts with a structured device and management plan, not with flashy AI demos. You need a roadmap that tackles foundational issues while creating space for Copilot projects.
Begin by auditing your existing device fleet: age, specs, operating system versions, and management status. Identify which machines are candidates for replacement with Copilot+‑class devices over the next 12–24 months. In parallel, evaluate Intune if you are not already using it, and plan a phased migration where every new device is cloud‑managed from day one.
Next, pick one or two high‑impact use cases for Microsoft 365 Copilot. Look for processes that are document‑heavy, time‑consuming, and easy to measure—such as monthly board reporting, sales pipeline reviews, or policy updates. Treat these as pilots to prove value and refine your governance approach.
Finally, create an internal “AI front door” similar to Levi’s planned “Rivet” super‑agent concept, which will use Microsoft Teams as a single portal to multiple behind‑the‑scenes agents. For smaller organizations, this could start as a simple Teams channel or app where employees can access Copilot scenarios, training, and support.
By aligning device strategy, endpoint management, and targeted AI projects, you can follow the same trajectory as Levi Strauss & Co.: from unreliable laptops and scattered processes to a secure, AI‑ready environment where projects that once took a year can realistically be done in a day.