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Using AI to make better decisions as an SME leader

•Nolann Bougrainville
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You run an SME and feel that your HR data, spreadsheets and endless email threads don’t really help you decide faster or better. Everyone talks about AI and automation, but you don’t clearly see how they could improve your decisions without a big IT project.

This article shows how to use AI not as a gadget, but as a decision co‑pilot for SME leaders and managers. The goal: move from gut feeling alone to decisions supported by clear information – without jargon, complexity or losing your freedom to choose. You’ll see concrete use cases, a simple method to structure your decisions, and a short action plan to get started in days, not months.

1. Why decision-making has become harder for SME leaders

In SMEs, decisions have always relied on common sense, proximity to the field and experience. But several changes now make this work harder:

  • Too much information (emails, files, spreadsheets, different tools)
  • More frequent decisions, taken under time pressure
  • Teams split across sites or working remotely
  • Stronger financial and regulatory constraints

The result:

  • You spend time looking for information instead of deciding
  • You often decide with partial or unclear numbers
  • You feel like you solve the same problems again and again

AI does not replace your judgement. It prepares the ground: gather, clarify, summarise and present options.

Before talking tools, it helps to understand what actually happens when you take a decision.

The 4 hidden steps behind most of your decisions

Most of your decisions, whether you notice it or not, follow four steps:

  1. Collect – emails, numbers, opinions, history
  2. Understand – sort, compare, highlight the essentials
  3. Choose – arbitrate between options
  4. Follow up – check that the decision is applied and useful

Today, you and your teams do most of this manually. AI and automation can take over parts of steps 1, 2 and 4, so you can focus your energy on step 3: choosing.

Rendering diagram...

This diagram highlights a simple principle: AI is best suited to collection, understanding and follow‑up, while you keep control of the actual decision.

2. Three concrete ways AI can improve your decisions without heavy IT

You don’t need to redesign your whole organisation. Start where decisions are frequent, important – and poorly prepared today.

2.1. Setting clear priorities for the week

Typical situation: every Monday you juggle projects, client urgencies, HR issues and admin. You end up “doing a bit of everything”, without really knowing if you’re working on what matters most.

How AI helps:

  • Automatically gather:
    • Overdue tasks in your tools
    • Emails flagged as "to handle"
    • Topics raised by your managers
  • Generate a prioritised summary:
    • 5 decisions to make first this week
    • 3 risks to watch closely
    • 3 topics you can safely postpone

AI becomes a kind of mini management meeting assistant, even if you are the only executive.

Outcome: you start the week with a clear view, instead of reacting to urgencies as they pop up.

2.2. Handling a sensitive people decision with structure, not improvisation

Examples:

  • Adjusting how a team is organised
  • Managing a conflict situation
  • Approving or rejecting a new hire

You have bits of information everywhere: meeting notes, emails, informal feedback, absenteeism data, etc. Hard to see the full picture.

How AI helps:

  • Bring together key information (while respecting confidentiality rules)
  • Produce a factual synthesis:
    • Context
    • Key issues and warning signs
    • Several scenarios (with pros, cons and risks)
  • Help draft your decision and the related messages (email, meeting notes, action plan)

AI does not decide. It structures facts, options and consequences. You remain fully responsible for the human judgement.

2.3. Choosing where to invest time and budget

You often need to decide:

  • Hire a new salesperson or invest in a tool?
  • Open a new region or reinforce an existing one?
  • Extend an internal project or stop it?

Without AI, decisions are usually based on:

  • A few partial figures
  • Team impressions
  • Whatever feels most urgent now

With AI, you can:

  • Quickly consolidate scattered data (sales, margin, time spent, client feedback)
  • Ask questions such as:
    • "Summarise the 3 main benefits and 3 main risks of this project."
    • "Over the last 12 months, which clients or projects were truly profitable?"
  • Get a simple decision support (comparison table, argument list, warning points)

You don’t replace your intuition – you back it up with facts.

3. Turning your recurring decisions into “augmented routines”

Rather than buying new tools for everything, the most effective move is to turn your recurring decisions into AI‑augmented routines.

Step 1: Identify 3 recurring decisions

For example:

  • Weekly priority‑setting
  • Hiring approvals
  • Approval of large discounts

Ask yourself: which decisions come back every month and really affect the business?

Step 2: Describe each decision in 5 minutes

For each one, quickly note:

  • What is the goal of this decision?
  • Which information do you always ask for?
  • Who is involved?
  • How often is it made?

This becomes your specification for AI’s role.

Step 3: Separate what must stay human

Before automating anything, be clear about:

  • What you want to keep 100% human (interviews, final arbitration, difficult announcements)
  • What can be prepared by the system: data collection, synthesis, scenario proposals

A good rule of thumb: anything involving emotion, trust or long‑term relationships stays human. AI prepares, you decide.

Step 4: Implement a simple “augmented ritual”

For each decision, design a small ritual, for example:

  • Monday 8:30–9:00: AI prepares a list of key decisions for the week, you review and adjust
  • Any discount request above £/€ X: AI compiles client history, margin, issues and suggests a recommendation
  • Before approving a hire: AI summarises interview notes, email exchanges and the business need

At first, you can rely on simple tools: mainstream AI assistants, basic connectors, exports. The key isn’t sophistication – it’s consistency.

4. Getting started in 10 days, without an IT project

You can lay the foundations of AI‑augmented decision‑making in less than two weeks if you move in small, focused steps.

Days 1–2: Pick your starting point

  • List 5 important recurring decisions
  • Select one as your pilot (the one that drains the most energy)

Days 3–4: Clarify the decision process

  • Describe the decision using the questions in section 3
  • List the information you look at every time (documents, dashboards, team inputs)

Days 5–6: Test AI as a preparation assistant

  • Use an AI assistant (ChatGPT, Claude, etc.)
  • Give it clear context:
    • The type of decision
    • The documents or elements to analyse
    • The expected output: “Summarise the context, list 3 options, and for each show benefits / risks / timing impact.”
  • Check its work carefully: you are the safety net.

Days 7–8: Turn it into a ritual

  • Block a fixed time slot in your calendar for this decision
  • Standardise the request you send to AI (a reusable prompt)
  • Track a few simple indicators:
    • Preparation time
    • Clarity of the decision
    • Number of U‑turns or re‑decisions

Days 9–10: Adjust and decide whether to scale

  • Fine‑tune the AI summary format so it matches how you like to decide
  • Decide whether to apply the same approach to a second recurring decision

You now have the basics of augmented steering: your key decisions are better prepared, faster and clearer.

Practical section: a checklist for AI‑augmented decisions

Use this checklist to make your next decisions more robust with AI:

  1. Is the decision clearly defined?
    • Yes / No
  2. Have you identified the information needed?
    • List of key numbers, documents, viewpoints
  3. Which preparation tasks can AI handle?
    • Data gathering
    • Email or meeting‑note synthesis
    • Scenario comparison
  4. Which parts must stay 100% human?
    • Final arbitration
    • Communication to people affected
    • Handling of sensitive cases
  5. Is AI’s role clearly framed?
    • Limited to decision support
    • Clear rules on which data it can use
    • Systematic human review
  6. Is the decision followed up over time?
    • Simple indicators to measure impact
    • Planned review point (in 1, 3 or 6 months)

If you can answer these six points, you are already practising augmented decision‑making: AI strengthens your leadership instead of diluting it.

Conclusion

To recap:

  • Most decisions follow a cycle: collect → understand → choose → follow up.
  • AI is particularly useful to prepare decisions (gather, summarise, compare), not to decide for you.
  • Turning a few recurring decisions into AI‑augmented routines gives you more clarity and peace of mind, without changing your whole IT landscape.
  • A focused 10‑day plan is enough to test this on one concrete case and measure its value.

The goal is not to make your decisions “automatic”, but to give you a better co‑pilot to steer your SME in a more complex environment.

If you’d like support on this journey, Lyten Agency helps you identify and automate your key processes. Contact us for a free initial assessment.

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