Putting AI Agents to Work With Copilot Studio

For the past several years, knowledge workers have been experimenting with generative artificial intelligence solutions. They’ve used Microsoft Copilot, for example, for tasks that improve individual productivity, such as research, meeting preparation and content creation. But for the most part, these have been ad hoc use cases, with each employee making countless decisions about when and how to use AI throughout the workday.

We’re rapidly moving into a new era of AI, beyond AI as an assistant that helps individual users work more efficiently. With Copilot Studio, organizations can automate repetitive processes at scale, transforming workflows and fundamentally changing how business gets done.

Financial services organizations offer a clear example of how AI is moving into the workflow. Previously, employees might have used Copilot to prepare for client meetings or summarize action steps afterward. Today, organizations can create custom compliance-focused agents that review policies, flag potential exceptions and help prepare audit packages.

Because the agent is grounded in the organization’s specific information, its recommendations and decisions will be based on real-world context.

In higher education, AI agents can help reduce repetitive administrative work, giving staff time back to focus on higher-value activities.

For example, a college might use Copilot Studio to create a student services agent grounded in information specific to the institution and its students. The agent could answer common questions and direct students to the appropriate office, website or resources they need to solve their problem, freeing up staff to spend more time handling issues that require human judgment or personal attention.

Retailers can create custom agents to handle the most common questions they receive about product sizing, returns or other routine issues. Here again, Copilot Studio lets companies tie their agents directly into their data, ensuring that the technology is equipped to answer nuanced questions with a high degree of accuracy.

Increasingly, retailers are also relying on AI agents to complete work on behalf of users (such as initiating an exchange or refund), rather than to simply carry on back-and-forth conversation with customers.

Human resources teams can use AI agents to take on repetitive work across recruiting, hiring and onboarding.

During the hiring process, for example, an agent might help review applicants’ information, identify candidates who appear qualified for a role and analyze materials such as cover letters or writing samples. With agents handling routine work, HR professionals can spend more of their time on the parts of the process that benefit most from human interaction, such as interviews and candidate conversations.

The same model can be extended to onboarding, with AI agents answering common questions from new employees and handling routine administrative tasks.

In the next phase of enterprise AI, organizations will have to move beyond experimentation to keep up, using agents to reliably create measurable business value. This requires leaders to look strategically at the processes that slow down work or create friction for customers, and then build agents that directly address those problems. 

CDW is already helping our customers make this shift. For organizations that are still building AI fluency, engagements like our QuickStart and Deployment Accelerator for Microsoft 365 Copilot can help establish a secure foundation for AI, identify high-value use cases and accelerate adoption. And for those ready to scale agentic AI, we can help with governance, data readiness, agent ideation and custom solutions built through Copilot Studio.

With the support of a partner like CDW, organizations can move their agentic AI efforts forward faster, without creating unnecessary new risks.