If you’re an MSP considering adding Microsoft Copilot to your portfolio in 2026, it’s worth being deliberate about how you package and position it for clients. For many organizations, pitching AI as a novel “productivity booster” is no longer enough.
Customers increasingly expect the conversation to shift from experimentation to execution, anchored in defined use cases and easily measurable ROI. Without this, renewal negotiations become more difficult, and long-term trust may start to erode.
Below, we’ll walk through a practical approach MSPs can use to guide customers from initial Copilot deployment through ongoing optimization and long-term value.
What Microsoft Copilot is—and what it is not
Microsoft Copilot is an AI-powered productivity tool that leverages large language models (LLMs) to provide real-time assistance that helps users complete tasks more efficiently, boost productivity and skills, and improve the overall work experience.
Like most LLM-based AI tools, Copilot responds to prompts and can draft content, summarize information, generate insights, and support other everyday tasks.
As an enterprise AI solution, its main standout feature is its deep integration with the Microsoft 365 suite. Copilot is, for the most part, accessible directly in Word, Excel, PowerPoint, Outlook, Teams, and other Microsoft applications.
Even with Copilot’s expanding capabilities, it’s important for MSPs to set expectations up front and explain where the tool shines and where it has limits.
Common misconceptions to address include:
- It isn’t an autonomous agent. Copilot still relies on user prompts and direction to produce useful outputs.
- Consumer and business versions aren’t the same. Feature sets can differ, including data protections, usage limits, and whether Copilot can use organizational data.
- It’s not 100% accurate. Like other LLM-based tools, Copilot can still make mistakes or “hallucinate,” so outputs need human review.
- It’s not meant to replace people. Copilot is designed to streamline workflows and free users up for higher-value work, not eliminate roles.
What MSPs should validate before recommending Copilot
Utilize the Microsoft 365 Copilot readiness report
Microsoft provides a 365 Copilot readiness report to help assess an organization’s readiness to adopt Copilot. Among other insights, it can provide data on which users are most likely to benefit from their day-to-day use of Microsoft 365 apps, and where Copilot tends to add the most value.
The report can also support license planning and help admins monitor usage across the Microsoft 365 apps Copilot integrates with most closely.
Data, security, and compliance readiness
MSPs should set the expectation that a baseline security posture and sound data governance need to be in place first. This includes understanding where sensitive data resides, how permissions and access controls are managed, and whether the environment is structured to support safe Copilot outputs.
MSPs should also account for any lingering security threats or unresolved issues, as well as the organization’s willingness to trial an AI tool in its workflows.
Considering use cases before deployment
MSPs should assess a client’s pain points and confirm whether Copilot can realistically address them. That means prioritizing workflows that involve employees summarizing information, drafting content, searching for answers, or translating insights into deliverables.
Even with strong potential benefits, Copilot won’t deliver meaningful value if it’s deployed without use cases tied to actual business needs.
With that in mind, let’s explore key Copilot use cases MSPs can position as practical value propositions for the tool.
Core Microsoft Copilot use case categories for MSP clients
What’s changed since early Copilot rollouts—and what MSPs should revisit now
Before diving into general Copilot use cases (like content generation), it’s worth looking at the updates Microsoft has introduced since Copilot first rolled out in 2023.
While these features are still fairly new, there are already some clear MSP angles and practical ways they can help customers.
Voice commands and screen scan debut on Copilot
Late last year, Microsoft added voice capabilities to Copilot, letting users launch the assistant hands-free. Customers can now say “Hey Copilot” to wake the assistant, ask questions, and send prompts — all without touching the keyboard.
Microsoft also rolled out Copilot Vision, which enables Copilot to analyze what’s on a user’s screen and provide step-by-step guidance.
MSP use case: Useful for help desk and customer support scenarios — especially when a “show me how” walkthrough can shorten tickets and cut down on back-and-forth.
Anthropic’s Claude Models are now available in Microsoft 365 Copilot
In September 2025, Anthropic’s Claude AI models were also made accessible through Microsoft 365 Copilot. This meant that Opus 4.1 could be used in Microsoft’s Researcher Agent and, along with Sonnet 4, in Copilot Studio.
This gives users and clients the option to choose between Anthropic’s Claude models or OpenAI’s ChatGPT models for specific tasks.
MSP use case: Adds AI model choice for different tasks (and preferences), which can matter for accuracy or workflow fit depending on the client.
Copilot Chat in the web browser
Microsoft introduced Microsoft 365 Copilot Chat, a web-accessible AI chat experience for Microsoft 365 users, in early 2025. Copilot Chat provides an AI-powered chat interface that’s grounded in the web and integrated with Microsoft 365 productivity tools.
Organizations with Microsoft 365 subscriptions can access Copilot Chat through a browser or Microsoft 365 apps, without purchasing the full Microsoft 365 Copilot add-on. Like any subscription service, the capabilities vary depending on whether the user also has a full Copilot license.
The main difference between Copilot Chat and Microsoft 365 Copilot is what data the assistant can use. Copilot Chat pulls from public web sources, while Microsoft 365 Copilot can also work with your organization’s internal Microsoft 365 data (within the limits of existing permissions) to give more specific, work-context answers.
MSP use case: A lower-friction on-ramp for clients who want to start with web-based Copilot chat before committing to the full Copilot add-on.
Employee productivity and knowledge work
Outside of the newer Copilot updates, the core capabilities and benefits remain largely the same.
As an LLM-based tool, Copilot remains strongest in content generation, summarization, and analysis. With good prompting and guardrail-setting, it can cut knowledge-work tasks from hours to minutes. For example, it can:
- Serve as a writing assistant and collaborator: Help users draft, edit, summarize, and restructure documents. For example, it can generate an outline for a marketing proposal and suggest language to flesh out key sections.
- Improve email management: Summarize long threads, draft replies, and help users prioritize what to respond to first. For example, it can summarize messages that piled up while an employee was out of the office, speeding up catch-up once the employee returns.
- Generate initial data analysis: Provide a first-pass review of datasets to surface patterns, trends, and potential insights that teams can validate and incorporate into reports.
Customer support and service delivery use cases
Copilot can provide real-time AI assistance to help support agents automate time-consuming tasks and speed up issue resolution. When enabled, it can help support agents respond to customer questions, draft chat replies, and summarize cases or conversation history for faster handoffs.
Copilot can also support customer operations by helping teams analyze customer feedback and even assist with social media triage and response workflows.
Common support-focused use cases include:
- Chatbots and self-service assistants to deflect repetitive questions.
- Tailored responses based on the customer’s issue and context.
- Faster replies to common customer questions and chat prompts.
- Drafting knowledge base content (articles, FAQs, internal runbooks).
Security use cases (Security Copilot)
Security Copilot is a generative AI–powered security tool that helps security teams handle incident response, threat hunting, intelligence gathering, and posture management through a natural-language, assistive Copilot experience.
Use cases for Security Copilot include:
- Investigate and remediate threats: Add context to incidents and turn alerts into actionable summaries.
- Create stakeholder-ready reports: Summarize environment context, open issues, and protective measures.
- Accelerate IT troubleshooting: Synthesize signals fast and surface next-best actions to resolve issues.
- Improve security posture: Prioritize risks and identify opportunities to strengthen controls.
- Streamline policy management: Summarize security policies and manage organizational contexts across an organization.
Measuring ROI and business impact from Copilot use cases
Once Copilot is in place, MSPs should make it a priority to measure ROI and show what’s improving in day-to-day workflows.
Productivity benchmarks MSPs can use as baselines
First, define the productivity gains you’re aiming for with Copilot, and then measure them consistently. Below are a few key metrics that are best captured before and after deployment:
- Time saved on repetitive work: One of the clearest indicators is how much time Copilot cuts from routine tasks (drafting responses, summarizing threads, creating first drafts, etc.).
- Increase in output volume: If Copilot is working, teams should be able to produce more deliverables in the same amount of time. This can be measured by more tickets resolved, more customer emails handled, or faster turnaround on internal requests.
- Headcount avoidance: Another useful lens is what Copilot effectively “augments.” Identify tasks that would have required adding headcount or outsourcing work, then estimate what Copilot reduced or eliminated in those needs.
Tracking adoption and usage patterns over time
As an MSP, you should also monitor Copilot adoption over time to see whether usage improves after deployment—or drops off once the initial excitement wears off. If adoption increases, this may be a sign that Copilot is bringing sustained value to an organization’s everyday operations.
In addition to adoption, it’s worth tracking usage patterns.
This helps you understand how users are actually using the tool, where usage is concentrated, which departments or roles get the most value, and which use cases are lagging.
Translating Copilot outcomes into business value discussions
Finally, you should tie Copilot outcomes back to long-term business goals. Increased output volume can translate into higher revenue, and Copilot-enabled automation can reduce friction and improve the end-user experience.
The point is that ROI should not only be measured in productivity targets, but discussed in business terms as well.
How MSPs can help clients maximize ongoing Copilot value
Implementing Copilot for clients should include a plan to maximize value in the long term, not just during the initial rollout. Below are a few practical ways MSPs can keep Copilot adoption moving in the right direction.
Explore and expand use cases after initial rollout
Even if clients start with a defined set of Copilot use cases, it’s worth revisiting them regularly to look for new opportunities. This can be done through monthly or quarterly check-ins, or by tying the conversation to new Copilot features that may better support their workflows.
The goal is to treat Copilot as an evolving part of the environment, not a one-time deployment.
Training and enablement strategies that drive adoption
Copilot is only as effective as the people using it. To get consistent results, MSPs should offer ongoing training tied to real use cases, not just general “how Copilot works” sessions.
Training can take the form of short webinars, internal documentation, and prompt guides, or even lightweight hackathons.
Bringing in subject-matter experts can also help teams learn how to apply Copilot to specific functions and drive broader adoption.
AI governance and awareness
It’s also important to put guardrails in place as Copilot becomes part of day-to-day work. Like any AI tool, data security and permissions management matter, and productivity gains do not mean much if sensitive information is handled improperly.
MSPs should lead these conversations with clients, making sure governance, usage guidelines, and basic security training are built into the rollout plan.
When Copilot is rolled out securely, it creates a stronger proof of concept and makes wider adoption across the organization more likely.
Bottom line: Copilot adoption should be tailored and ongoing to succeed
Effectively offering Microsoft 365 Copilot requires MSPs to be deliberate in how they implement the tool for client organizations. That means assessing and prioritizing the most appropriate use cases, measuring ROI with real benchmarks, and continually optimizing how Copilot is used so it keeps delivering value over time.
Copilot’s advantage is its built-in reach across Microsoft 365 users. As a Microsoft product, it has a natural footprint across the modern workplace. As an AI tool, it is also flexible enough to support a wide range of business needs across different functions.
The MSP’s role is to narrow that broad potential into practical, role-specific opportunities and then turn those opportunities into a repeatable program that drives real business value for the organization.
