AI in Excel

AI in Excel uses Microsoft 365 Copilot to help you work smarter by speeding up certain spreadsheet tasks, like adding columns and formulas, formatting tables, and coming up with insights about your data.

To get started with Copilot in Excel, follow these steps:  

1. Open an existing Excel spreadsheet stored on OneDrive or SharePoint.
2. From the Home tab, select the Copilot icon to open the chat pane. If you don’t see the icon, you’ll first need to sign up for Microsoft 365 Copilot.
3. Choose one of the prompt suggestions or type your own.
4. If you’re feeling stuck about what to ask, select the View Prompts icon from the chat box to explore some of what you can do with Copilot in Excel.

Data cleaning

One of the most useful Excel AI tools is the ability to clean up data quickly. Large datasets often have inconsistencies, errors, or duplicates. Ask Copilot in Excel for help automatically detecting these issues and correcting them. For example, ask Copilot to standardize data formats and remove duplicate entries, so your data is more accurate and easier to work with.

Seeing trends in data can be hard, especially when you’re dealing with complex or extensive datasets. AI for Excel simplifies this process by analyzing your data and highlighting important patterns or trends. You can even ask Copilot in Excel to create charts or graphs that sum up your spreadsheet more clearly.

Not all formulas are created equally—some complex formulas can be time consuming and prone to errors. Speed things up and reduce mistakes by asking AI in Excel to suggest the correct formulas based on the data you’re working with. If you need to perform complicated calculations or combine multiple functions, Copilot in Excel can guide you through the process or generate the right formula for you.

As you work in Excel, Copilot provides context-aware recommendations based on your actions. For example, if you’re sorting data or creating PivotTables, Copilot might suggest alternative methods or shortcuts that could improve your workflow. These suggestions help streamline the process and make working with data more intuitive.

By understanding the structure and content of your data, Copilot in Excel can generate detailed reports automatically. The AI can also include summaries, visualizations, and key insights based on your data—all formatted professionally. This feature is helpful for quickly producing presentations or sharing findings with others without having to manually compile the information.

Increased efficiency

Automate tasks that would otherwise be time-consuming to increase how efficiently you work. For example, AI in Excel can automatically clean up data, suggest formulas, and generate reports. This makes work easier because you’ll complete tasks faster and be able to focus on more important details.

It’s not unusual for people to accidentally introduce errors in data analysis and management, which can then lead to incorrect conclusions and decisions. Help reduce these errors by having Copilot in Excel suggest formulas and perform complex calculations.

Good decisions rely on good data. Enhance your decision-making by asking Copilot for insights based on your data. AI in Excel can identify patterns, trends, and key information that might not be immediately obvious.

Handling large datasets can be overwhelming and challenging, but Copilot in Excel makes it simpler to scale your work by processing large amounts of data quickly. This scalability means that no matter how large or complex your data is—like thousands of rows or multiple complex sheets—you can manage it more easily.

Even if you’re not an Excel expert, the user-friendly design of Copilot in Excel makes it straightforward to use. Get help with tasks and receive suggestions and explanations about different functions by just explaining what you need or choosing an existing sample prompt.

Here are some practical examples of how Copilot in Excel can be used in different business scenarios and industries.
 

Financial analysis

 

• Creating financial forecasts: Instantly generate financial forecasts by analyzing historical data and predicting future trends.

• Budget analysis: Create detailed budget analyses by comparing actual spending against budgeted amounts to highlight differences.

• Investment evaluation: Evaluate investment opportunities by analyzing financial metrics and projecting potential returns.

• Analyzing key performance indicators (KPIs): Review marketing data to see which KPIs, such as conversion rates and customer acquisition costs, are doing well.

• Trend analysis: Detect trends in marketing data, like seasonal spikes in customer interest, to help strengthen campaigns.

• Customer segmentation: Analyze customer data based on purchasing behavior, demographics, and engagement levels, allowing for more targeted marketing.

• Predicting sales trends: Anticipate future sales trends by analyzing past sales data, so you can plan more effectively.

• Customer behavior analysis: Forecast customer behavior, such as purchasing patterns, for more accurate sales strategies.

• Quota setting: Set realistic sales quotas by analyzing performance data and market conditions.

• Meeting inventory requirements: Predict future inventory needs based on past sales data to avoid stockouts or overstocking.

• Optimizing your supply chain: Analyze supply chain data to find inefficiencies.

• Cost management: Monitor and manage inventory costs to keep expenses in check.

• Employee performance analysis: Evaluate employee performance data to identify top performers and pinpoint opportunities for growth.

• Turnover rate analysis: Understand trends in employee turnover, so HR teams can proactively address retention issues.

• Workforce planning: Estimate future staffing needs based on current data and trends.

• Student performance trends: Identify trends in student performance to understand areas where students excel or struggle.

• Resource allocation: Decide how to best use educational resources by analyzing how often they’re used and how effective they are.