AI Excel tool inventory, 6 tested recommendations for automatically processing tables and functions in 2026

AI Excel tool inventory, 6 actual test recommendations for automatically processing tables and functions in 2026

Excel is always the hard currency in the workplace, but writing functions, making pivot tables, and cleaning data have always been pain points for a large number of people. VLOOKUP will be a big problem if it is nested to the third level. If there are more SUMIFS conditions, an error will be reported. If the fields of the pivot table are dragged to the wrong position, they will have to be redone. The AI ​​Excel tools of 2026 have already automated most of these scenarios. You only need to use natural language to describe what you want to do, and AI will complete the formulas, macros, and pivot tables in one step. This article takes stock of 6 tested and useful AI Excel tools, ranging from native integration to independent web pages, suitable for users in different scenarios.

Common scenarios of AI processing Excel

Introducing AI into the Excel workflow can solve many things.

The first category is formula generation. Please help me write a formula to find the rows containing a certain keyword from column A. AI will directly give you the correct SEARCH or FILTER function. This is particularly friendly to people who are not familiar with the Excel function system and saves time flipping through documents.

The second category is data cleaning. If there are null values, typos, and inconsistent formats in a piece of raw data, ask AI to write you a formula or a piece of Python to format the data into a standard format, and it will be done in a few seconds.

The third category is analytical insights. Give AI a piece of data and let it provide trend analysis, abnormal point tips, and visual suggestions. It can provide usable conclusions like a junior data analyst.

The fourth category is automated batch processing. Multiple copies of Excel with similar formats need to be processed in the same way. AI can generate reusable scripts and run them in batches with one click, which is dozens of times faster than manual processing one by one.

The following 6 tools each have their own strengths in these scenarios.

1. ChatGPT plus Code Interpreter

ChatGPT's Code Interpreter (now called Advanced Data Analysis) is the most flexible solution for working with Excel.

The workflow is that you drag the Excel file directly into the ChatGPT dialog box, and then use natural language to describe what you want to do. It will run a piece of Python code in the background to process your file, return the results in the form of tables, charts, and text summaries, and download the processed files back.

Its strength lies in its high flexibility. Almost any Excel operation can be implemented in Python and is not limited by Excel's own function capabilities. Can do complex data perspective, statistical analysis, visualization, and machine learning.

短板是要 ChatGPT Plus 订阅才能用,每月成本看 OpenAI 官方页面。 The processing speed of large files (more than hundreds of thousands of lines) will be slow, and there are compliance concerns about uploading sensitive enterprise data to the OpenAI server.

Suitable for people: data analysts, researchers, and freelancers doing one-time in-depth analysis.

2. Excel Copilot

Microsoft's own Excel Copilot is a solution that is deeply integrated with Microsoft 365. If your company uses Microsoft 365 Family Bucket, this is the most convenient choice.

Copilot appears directly in the ribbon at the top of Excel. You click on the sidebar and describe the task in natural language, and it will match formulas, pivot tables, and charts. Common scenarios include helping me summarize this column of data by month, finding products whose sales have dropped by more than 20% year-on-year, and generating a chart comparing male and female customers. Copilot can directly execute it.

The advantage is that it is best integrated with the native Excel experience, the data does not leave the enterprise tenant, and it has strong compliance. It is suitable for standard office scenarios of medium and large enterprises.

The shortcoming is that it requires Microsoft 365 plus Copilot subscription, which is not cheap. Please see Microsoft’s official website for details. Free users cannot enjoy this feature for the time being.

3. Numerous.ai

Numerous.ai is an Excel and Google Sheets plug-in that specializes in moving AI functions into cells.

Its gameplay is very interesting. Just write =AI("Generate product label based on the description of A1") directly in the cell. This custom function, AI will return the result, just like SUMIF and VLOOKUP. This style is very suitable for batch content generation, such as writing product descriptions in batches, writing emails to customers, labeling data, and doing translations.

The free version has a certain number of calls, and you need to pay for a monthly subscription. Please see the official website for specific prices. It can be used with Excel and Google Sheets, and the cross-platform experience is consistent.

Suitable for people: People who do content operations, e-commerce listings, customer management, and foreign trade communication.

4. Formula Bot

Formula Bot is a tool that focuses on formula generation to the extreme, and its positioning is very specific.

Open the web page and use natural language to describe the Excel operation you want. It will return the corresponding formula, which you can copy and paste into Excel to use. Supports Excel formulas, Google Sheets formulas, Airtable formulas and other syntaxes.

Its strengths are that it is free, can use basic functions without registration, has fast response, and is highly accurate for common formula scenarios. It can also reversely parse formulas. If you paste a complex formula that you don’t understand, it will explain what each paragraph does, which is very helpful for learning the Excel function system.

The shortcoming is that it only solves the link of formula generation. It cannot directly process files or run analysis. It needs to be used with Excel. But it is very suitable as a quick formula check tool. It can be used in seconds when encountering formulas that you cannot write every day.

5. WPS AI

WPS Office has a high share of domestic office scenes. WPS AI is integrated into WPS tables to provide native AI operation capabilities.

The advantage of WPS AI is that it is available for free (basic functions), the Chinese scene experience is smooth, and it is very suitable for the Excel habits of domestic users. It can do formula generation, data analysis, pivot table automation, and chart generation, basically covering the daily Excel needs in the workplace.

Advanced functions require WPS membership subscription, please see the WPS official website for details. For domestic users who are unwilling to pay for Microsoft 365 but want AI office capabilities, WPS AI is a cost-effective choice.

短板是和微软 Excel 在专业图表、超大数据集处理上还有差距,做日常办公完全够,做专业数据建模可能要回到 Excel 加 Python。

6. ChatExcel

ChatExcel is a domestic tool that specializes in AI Excel, focusing on operating tables through chatting.

You upload an Excel file and chat in natural language, and it will directly modify the file and return the results. For example, help me filter the rows with sales greater than 100, sort by date, and add a column to calculate month-on-month growth. ChatExcel will explain and execute it at the same time, and finally give you the modified file.

Its strengths are the Chinese interface, intuitive operation, and the free quota is sufficient for individual users. It is suitable for novices who are not familiar with Excel formulas to quickly complete daily table processing.

The shortcoming is that you will encounter limitations when processing complex logic or large files, and the free version is also limited. But for non-professional users who occasionally deal with simple forms, it is a very easy-to-use option.

Advanced gameplay: Use Python and LLM to run batches

If you are a technical person, the ultimate solution for handling batch Excel tasks is to write your own Python script to call LLM.

The workflow is roughly as follows: use pandas plus openpyxl to read Excel data, feed the data fragments to LLM (Claude, GPT, local Ollama will all work), let it do the analysis or generation you need, and then write the results back to Excel. The advantages of this approach are that it is fully customizable, can handle tasks of any complexity, and can access private data.

Frameworks such as LangChain and LlamaIndex provide ready-made tool chains, so you don't need to write code from scratch. The open source community also has PandasAI, a library that specifically combines pandas and LLM. You can use it directly like df.chat ("Find the 5 highest-selling products"). The experience is between the command line and chat.

It is suitable for technical teams that frequently process data and developers who do product integration. The long-term investment returns are very high.

Selection suggestions

Give a comparison based on the scene.

For occasional use of Excel, WPS AI or ChatExcel in the daily workplace, it is free and sufficient. If you want stronger capabilities, ChatGPT Plus plus Code Interpreter is an all-round solution for individual combat.

I often write formulas and are not familiar with the function system. Formula Bot is used as a quick reference tool. It is free and has fast response. You can use the formula immediately after you get it.

For enterprise-level users in the Microsoft 365 ecosystem, Excel Copilot is the default choice, with the best compliance and experience. If you are in the Alibaba and Tencent ecology, the related plug-ins of Tongyi and Hunyuan are also worthy of attention.

For e-commerce operations and content generation-intensive work, Numerous.ai's cell AI function gameplay is very suitable for batch content generation scenarios.

When the technical team does product integration or complex data analysis, they can directly use Python and LLM to build their own pipeline, which has the best scalability.

Several reminders on data security

There are several judgments to make before uploading Excel to AI.

If the data involves customer privacy, business secrets, or financial data, give priority to local deployment or internal enterprise AI solutions (Microsoft Copilot uses Azure tenants, WPS Enterprise Edition, Python + Ollama local models), and avoid uploading to public network AI.

If you only want public data, simulated data, or data for your own learning, any AI tool can be used, and the one with the best experience will be preferred.

If you are unsure, desensitize it first (replace PII information such as name, phone number, email, ID, etc. with fake data) before uploading, and then restore the desensitized fields after processing. Spending an extra two minutes on this step can avoid a lot of compliance risks.

FAQ

Will Excel formulas written by AI make mistakes?

There will be occasional mistakes, but the probability of mistakes is lower than that of human writing. AI has a high accuracy on simple to medium complexity formulas, but occasionally there will be misalignment or wrong function selection on complex formulas that are deeply nested and refer to many areas. After getting the formula, run some test data to verify the results. It only takes ten seconds.

Will Code Interpreter get stuck when processing very large data?

meeting. ChatGPT's Code Interpreter has limitations on single file size and execution time, and may time out when processing more than hundreds of thousands of rows of data. In this scenario, it is recommended to download the Python code provided by ChatGPT and run it locally on your own computer. The upper limit of the data amount depends only on your computer configuration.

Can Excel Copilot be used in China?

Microsoft 365 has a commercial version in the country, and the availability of Copilot is subject to Microsoft's official announcement. If domestic tenants have not yet opened it, you can consider using WPS AI or other domestic alternatives.

How to verify the accuracy of AI-processed Excel

Several common methods. The first is to check whether the processing results of several lines are in line with expectations. The second is to use Excel's own SUM, COUNT and other functions to summarize the processed data to see if the total is correct. The third is to verify on a small data set first, and then expand to a large data set if it passes. The pattern of AI errors is usually systematic (a certain type of data is all wrong) and can be discovered quickly by sampling.

Will these tools leak my data?

Commercial versions usually promise not to use your input for training, but the transmission and storage are still in the cloud. The only fully localized solution is Python + Ollama + open source model. If the data is sensitive, localization is preferred. It is possible to use cloud AI for daily ordinary data. The specific strategy depends on the company’s compliance requirements.