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✍️Xavier Vincent

Using AI with Your Excel Files: A Simple First Step into Automation for SMEs

You probably spend a good part of your week in Excel or Google Sheets, but AI still feels distant or "too technical". In reality, your spreadsheets are one of the easiest ways to start using AI and automation in your SME, without changing tools or starting a big IT project.

In this article, we’ll show how to turn your existing Excel files into a concrete playground for AI: automatic checks, clean‑up, summarising data, preparing decisions… All without technical jargon, with examples that match your daily work.

We’ll cover:

  • why your spreadsheets are a perfect starting point for AI;
  • 4 practical use cases in finance, HR, sales and admin;
  • a simple 5‑step method to test AI on a single file;
  • a checklist to move from a one‑off test to a reliable routine.

1. Why spreadsheets are the perfect first step into AI

Before thinking about a "big AI project", look at where you already spend your time:

  • sales pipelines and customer lists
  • cash‑flow and forecasting sheets
  • lists of contracts, invoices and suppliers
  • holiday planning and absence tracking
  • monthly reporting for your accountant or shareholders

These files have three key advantages if you’re starting with AI:

  1. Your data is already there. No need to build a new database or deploy a new system.
  2. The structure is clear. A table with rows and columns is ideal for AI.
  3. The risk is easy to control. You can start from a copy of the file and keep the real system untouched.

The goal is not to replace Excel, but to add an AI and automation layer on top of it, to save time and make decisions more reliable.

In practice, AI can help you:

  • detect inconsistencies or duplicate entries;
  • summarise hundreds of rows into a few clear messages;
  • generate simple indicators and alerts from your data;
  • prepare concrete actions (follow‑ups, priorities, items to review).

2. Four practical AI use cases on spreadsheets (finance, HR, sales, admin)

2.1. Finance / cash‑flow: spotting risks without scrolling for hours

Typical situation:

  • You have a cash‑flow file or a bank export in Excel;
  • You spend time filtering and sorting to find overdue payments or unusual expenses.

With AI, based on a simple export (kept in a secure environment), you can ask it to:

  • categorise your expenses (rent, software, salaries, travel, etc.);
  • highlight cost categories that increased sharply vs last month;
  • list receivables above a certain amount that are overdue by more than X days;
  • summarise the 5 main cash‑flow risks for the month.

Instead of starting by “reading the table”, you start by reading a clear summary, then you review a few key lines.

2.2. HR: structuring people decisions with a simple table

You might already maintain a table showing:

  • employees,
  • seniority,
  • role,
  • salary,
  • some indicators (targets, bonuses, presence, etc.).

Rather than re‑starting from scratch for every decision (raise, bonus, promotion), you can ask AI to:

  • spot pay gaps for similar roles, based on experience or seniority;
  • suggest groups of employees you should review first (risk of leaving, underpaid, etc.);
  • prepare a structured briefing for your one‑to‑one meetings (facts, strengths, areas to work on).

AI doesn’t decide for you. It prepares the ground based on data you already have.

2.3. Sales / CRM: turning an export into a prioritised action plan

You export a list from your CRM or keep a simple Excel file with:

  • customers and leads,
  • revenue to date,
  • pipeline stage,
  • date of last contact.

AI can help you:

  • automatically classify each row (strategic client, churn risk, hot lead, cold lead);
  • build a follow‑up plan: who to call this week, who to email, who to park for later;
  • draft message templates adapted to each situation (gentle reminder, firm reminder, meeting proposal).

Your spreadsheet goes from a static list to a concrete list of next actions your team can execute.

2.4. Admin: cleaning, checking and standardising data

You probably manage lists of:

  • suppliers,
  • contracts,
  • file numbers,
  • addresses,
  • product references.

AI can help you:

  • flag potential duplicates (same supplier under two names, duplicated client records);
  • standardise key fields (address format, phone numbers, postcodes);
  • identify missing information (missing IBAN, contract end date, missing document);
  • produce a list of corrections to apply.

This may sound basic, but a clean spreadsheet is often the foundation you need for more advanced projects (cash‑flow, contract management, reporting…).

3. What does an "AI + Excel" workflow look like in real life?

Here is a simple workflow you can build on top of your existing files:

Rendering diagram...

This diagram highlights a key point: humans keep the final say.

  1. You start from a raw file (bank export, CRM, ERP, HR tool, etc.).
  2. You work on a copy or export, in a secure environment.
  3. AI analyses, classifies, detects anomalies, suggests actions.
  4. You review and approve (or reject) these suggestions.
  5. You then update the official file or system.

As long as you keep this "AI suggests, human validates" logic, you limit risk while capturing the time savings.

4. A 5‑step method to test AI on a single file

You can run a first experiment in less than a week, on one file only.

Step 1 – Pick a simple, useful file

Criteria:

  • you use it at least once a week;
  • it contains structured rows (one row = one invoice, one client, one employee…);
  • the risk is limited (no direct legal decision based only on the file).

Examples: client reminder list, CRM export, contract list with due dates.

Step 2 – Clarify what you expect from AI

Write down a simple request:

  • "I want AI to find overdue items and prepare a follow‑up plan."
  • "I want AI to highlight anomalies and missing data."
  • "I want AI to summarise the key points for my monthly meeting."

The clearer your request, the more useful AI will be.

Step 3 – Prepare a copy of the file

  • Duplicate the file.
  • Remove columns you don’t need.
  • Anonymise if necessary (e.g. replace names with IDs).

The goal: limit sensitive data to what’s strictly needed for the test.

Step 4 – Work with AI from that file

Depending on the tool you use (AI assistant connected to your files, Google Sheets add‑on, etc.), you can:

  1. Import or connect the file.
  2. Explain the context in plain language:
    • "This file lists our customer invoices, with the amount, due date and paid/unpaid status."
  3. Ask step‑by‑step questions, for example:
    • "Identify invoices overdue by more than 30 days and rank them by priority."
    • "Summarise the 3 main cash‑flow risks you see in this file."

Step 5 – Validate and formalise the workflow

Once you’re happy with the result:

  • save the instructions that gave good results (the prompts you used);
  • decide who will run this workflow in the future (you, a finance assistant, a sales manager…);
  • decide when to run it (every week, at month‑end, before a management meeting…).

You’ve just created your first mini "AI + Excel" process, without building any new tool.

5. Hands‑on section: checklist to move from test to routine

Use this checklist to turn a one‑off test into a stable, useful routine.

5.1. Setup checklist

  • [ ] One pilot file chosen (simple, recurring, limited risk)
  • [ ] A clear description of the goal ("why AI is used here")
  • [ ] A secure tool to handle the file (trusted AI tool, restricted access)
  • [ ] A tested prompt template kept for future use
  • [ ] A named owner responsible for running the workflow

5.2. Reliability checklist

  • [ ] Systematic comparison between AI suggestions and human checks
  • [ ] Monthly review of potential errors or gaps
  • [ ] Prompt updated when the process changes
  • [ ] AI limited to suggestions (no automatic edits to the official file)

5.3. Rolling out to a second file

  1. Pick another important spreadsheet (for example: an HR overview or sales report).
  2. Re‑use the same 5‑step method.
  3. Adapt your prompts to this new context.
  4. Train a team member to run this workflow without you.

Within a few weeks, you can build a small library of "AI + Excel" workflows tightly aligned with the way your company already works.

Conclusion

By starting from your existing Excel or Google Sheets files, you can:

  • try AI without changing tools, on a limited, low‑risk scope;
  • turn heavy spreadsheets into clear summaries and concrete action plans;
  • build simple, secure "AI + human review" mini‑processes;
  • prepare the ground for deeper automation projects later on.

The goal is not to have "AI everywhere", but AI where it clearly saves time and brings clarity, without making your organisation more complex.

If you set up a first "AI + Excel" workflow, track for a few weeks:

  • time saved vs your previous manual approach;
  • reduction in errors or missed items;
  • impact on the quality of decisions (cash‑flow, HR, sales, admin).

If you’d like support with your digital transformation, Lyten Agency can help you identify and automate your key processes. Get in touch for a free audit.

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