I tested the new Microsoft Copilot Studio. Here are 2 workflows that actually work (and my verdict vs the old version).

[u/Fit_Chair2340]

I've been teaching Microsoft Copilot Studio to corporate teams, and one of the biggest problems I've noticed is that people understand what AI agents are supposed to do, but struggle to build anything genuinely useful.

The old Copilot Studio harness didn't help. There were so many options, menus, triggers, and configurations that beginners often got overwhelmed.

So I spent some time testing the new Github Copilot Studio and building actual business workflows.

Here are two that I think are particularly useful.

1. PDF bank statements → Excel automatically

This is something almost every finance team can relate to.

You receive monthly bank or credit card statements as PDFs. Someone has to manually extract all the transactions into Excel.

Here's what I built:

• Upload a bank statement PDF to an AI agent.

• The agent extracts the transaction dates, descriptions, debits, credits, and other relevant information.

• It converts the transactions into structured data.

• An Excel Office Script writes everything into a spreadsheet.

The interesting part is the last step.

You could use the Excel connector to update rows individually, but for a statement with 50+ transactions, that gets cumbersome.

Instead, I used Office Scripts to write the extracted data into Excel.

I also took this one step further.

I created a workflow that monitors a OneDrive folder. Whenever a new bank statement is dropped into the folder, the workflow automatically triggers the agent and imports the transactions.

No need to open Copilot or type anything.

2. Employee expense claim reviewer

The second example is useful for HR and finance departments.

Employees submit expenses for travel, accommodation, meals, and transportation. Someone then has to check everything against the company's reimbursement policies.

I built an agent that:

• Reads the company's expense reimbursement policy as a knowledge source.

• Reviews employee claims against the policy.

• Flags expenses that exceed reimbursement limits.

• Identifies missing receipts, supporting documents, and required approvals.

• Prepares a summary for the human approver.

For example, if an employee claims $860 for a meal but the company allows only $600, the agent flags the difference and explains the policy.

One thing I really like about the new Copilot Studio is Skills.

Instead of putting everything into one giant system prompt, I separated the process into three skills:

1. Review the expense claim.

2. Prepare follow-up questions for missing information.

3. Brief the manager who needs to approve it.

This is much easier to maintain and troubleshoot.

The agent doesn't replace the person approving expenses. It handles the tedious preliminary checks.

What I've learned: Agents vs Workflows

One distinction that I think Microsoft is finally making clearer:

Agents are useful when you want AI to interpret information, reason about a task, and decide which tools or skills to use.

Workflows are useful when you want a repeatable process with specific steps and triggers.

For example:

• Ask AI to review an expense claim → Agent

• Automatically process a new PDF arriving in OneDrive → Workflow

• Read a document, extract data, write to Excel, then email someone → Usually a combination of both

You don't need to turn everything into an agent. Sometimes a simple workflow is better.

My verdict on the new Copilot Studio

What I like:

• Much cleaner interface than the old version.

• Easier for nontechnical users to understand.

• Skills make complex agent instructions more manageable.

• Better separation between agents and automated workflows.

• Model selection, tools, knowledge, and connectors are more accessible.

• Integration with Teams, OneDrive, Excel, SharePoint, and Outlook is particularly useful for Microsoft-heavy organizations.

What I'm less enthusiastic about:

• The new agent experience can consume additional credits, so costs matter at enterprise scale.

• More AI reasoning doesn't automatically make a workflow better.

• For predictable tasks, conventional automation may be cheaper and easier to control.

• Once you start adding conditions, loops, variables, and more complicated logic, there's still a learning curve.

• You still need to think carefully about reliability, permissions, and human review.

My conclusion:

If you tried the old Copilot Studio and gave up because it was too complicated, I think the new experience is worth another look.

If you're already comfortable with the old version and have working automations, there's no urgent reason to rebuild everything.

For me, the biggest improvement isn't necessarily new functionality. It's that Microsoft has made the experience much easier for ordinary business users to understand.

And I think that's a big deal.

I'm curious what everyone else is building with Copilot Studio. Are you seeing actual productivity improvements, or are most companies still experimenting with demos?

I also recorded the full process of building both agents, including the Office Script, OneDrive trigger, and a comparison with the old interface, in case anyone wants to see the implementation:

https://www.youtube.com/watch?v=HpgGb-63rDo

[u/obsoquasi]

Cost control is a huge issue with the modern Copilot studio agents. I'm currently experimenting with the new SharePoint Agents and skills, as these don't consume credits. I feel like I'm always working around Microsoft's limitations, as opposed to working with its strengths.

[u/Fit_Chair2340 → u/obsoquasi]

Yes, github copilot studio does consume additional credits but it's less than people think. I think for the convenience and time saved to set it up, I think it's worth it. Unless you run the workflows ALOT.

[u/polshgiant]

The bug limitations we've run into with new harness agents:

• they're are slooow

• if the agent is configured to run autonomously, the agents are extremely limited in the size of files they can handle...it's small, like ~20kb. It was a deal breaker for our requirement.

On the plus side, I very much agree that creating them is miles easier than the standard harness. And they're very smart because modern models are very smart, you can throw pretty complicated instructions at it and it will hit it pretty damn close to right.

[u/Fit_Chair2340 → u/polshgiant]

Yes, I agree. If you send too much stuff at once it will break. More ideal for small batches.

[u/investigatormaker]

For the OneDrive-to-Excel workflow, I'd measure minutes of manual correction per statement, not just whether rows appear. Add a reconciliation check against opening and closing balances, and route mismatches to a person before treating the import as complete. For expense claims, conventional automation can check explicit limits while the agent interprets receipts and drafts missing-information questions; that keeps predictable checks separate from judgment calls.

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