By Tuesday, most teams have a clear view of where the week is getting stuck: approvals waiting in inboxes, customer requests being retyped, and reports assembled by hand. These are not glamorous problems, but they are often the best starting point for AI and process automation.

The goal is not to automate everything. It is to make a few high-friction processes faster, more consistent, and easier to manage.

Start with work people repeat

Look for tasks that happen frequently, follow a recognizable pattern, and require people to move information between systems. Common examples include routing support requests, summarizing meetings, checking invoices, creating status updates, and notifying managers when approvals are overdue.

Ask teams three simple questions: Where do we copy and paste information? Where do requests wait? Where do errors or rework happen most often? Their answers will usually reveal better opportunities than a top-down list of fashionable AI ideas.

Connect automation to a business result

A successful pilot needs a clear measure. That might be reducing invoice-processing time, shortening response times, increasing completed approvals, or giving managers several hours back each week.

Before changing the process, record a basic baseline: volume, time spent, delays, and error rates. Then compare results after 30 or 60 days. This keeps the conversation focused on value rather than activity, such as the number of bots created or licenses purchased.

Use Microsoft 365 where work already happens

For organizations already using Microsoft 365, a practical starting point is to connect familiar tools such as Outlook, Teams, SharePoint, Forms, and Power Automate. For example, a form can collect a request, Power Automate can route it for approval, and Teams can notify the right owner without another manual handoff.

AI can add useful judgment around the edges: summarize a long request, classify incoming messages, extract key details from a document, or draft a response for employee review. Keep a person involved when the decision affects money, customers, employees, or compliance.

Build trust before you scale

Set simple guardrails from the beginning. Define who owns each automation, what information it may access, when a human must review the result, and how failures will be reported. Start with low-risk processes, monitor outcomes, and invite the people doing the work to improve the design.

Adoption improves when automation removes frustration rather than threatening roles. Explain what is changing, provide short training, and show the time saved in terms employees recognize.

Take the next step

This Tuesday, choose one repetitive process with a visible cost and a supportive owner. Document its current steps, agree on one success measure, and test a small improvement within 30 days. A focused experiment can reveal more—and create more confidence—than a broad AI strategy deck.