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Introducing AI in SMEs: a practical guide in 5 steps

By Michael Vogel, Co-founder, Klarframe · Updated

Small and medium-sized companies introduce AI most reliably in five steps: take stock, set rules, pilot one process, measure and decide, then scale on the same foundation. The starting point is a concrete loss of time, for example in enquiries, quotes or meeting minutes. Processes with clear rules and regular volume work best. Before the pilot, you define one goal and a baseline metric so that you can prove the benefit later. In parallel, you clarify ownership, data protection, approved tools and your duties under the EU AI Act. Within about 90 days this gives you a reliable result instead of a collection of loose experiments.

Where should a company start with AI?

The best starting point is a process that noticeably costs time today. Ask your teams about recurring tasks where people copy, search, summarise or answer the same questions again and again. Such time losses are usually easy to name and easy to measure later.

For the first project, choose a process with clear rules and sufficient volume. Clear rules mean that an experienced employee can explain what a good result looks like. Volume means the task occurs often enough for an improvement to be worthwhile and measurable.

Then define exactly one goal and record a baseline metric before you change anything. Examples are the handling time per quote, the share of missed calls or the minutes spent per meeting summary. Without this baseline, the success of a pilot is hard to assess.

The foundations: six areas of AI readiness

Whether an AI project holds up depends less on the tool than on the foundations in the company. The following six areas match the Klarframe AI Readiness Check:

  • Goals and ownership: there is a concrete goal and a named person who owns the project, makes decisions and has time for it.
  • Processes: the affected workflows are known and at least roughly documented. A process nobody can explain cannot be supported well by AI.
  • Data and knowledge: the required information is findable and up to date, such as price lists, product data, templates or answers to frequent questions.
  • Systems and technology: it is clear which systems the AI has to work with, for example email, phone system, CRM or document storage, and whether interfaces exist.
  • AI use today and team: you know which AI tools are already in use, including private use without approval (shadow AI). Company accounts replace private accounts, and the team receives short training.
  • Rules, data protection and approvals: there are defined rules on which data may go into which tools, who approves new tools and who checks AI results before they are sent.

The 5 steps: a 90-day roadmap

The following five steps have proven to be a sound order. The time frames are guide values and depend on scope and starting point.

  • Step 1, take stock (weeks 1 to 2): collect time losses, record existing AI use, assess the six foundation areas and select a pilot process.
  • Step 2, set rules (weeks 2 to 4): write a one-page AI policy, name approved tools and define data classes, such as public, internal and confidential, with clear rules on what may go into which tool.
  • Step 3, pilot one process (weeks 4 to 10): implement a single process with a small team, build in a human approval step and collect feedback regularly.
  • Step 4, measure and decide (weeks 10 to 12): compare the metric with the baseline, assess quality and acceptance and make a deliberate decision: expand, adjust or stop.
  • Step 5, scale (from week 12): add further processes on the same foundation, meaning the same rules, accounts, data classes and responsibilities.

Typical first use cases for SMEs

These areas are often suitable for a first project because they have clear workflows and regular volume:

  • Phone and enquiries: an AI phone assistant answers calls, handles standard questions, records requests and forwards them.
  • Quotes: AI drafts a quote from enquiries and templates, which an employee checks and approves.
  • Meeting minutes: meetings are summarised, and tasks and decisions are recorded.
  • Company knowledge: employees find answers from manuals, policies and project documents faster.
  • Documents: invoices, delivery notes or forms are read, sorted and transferred into systems.
  • Multilingual communication: emails, documents and conversations with customers and partners abroad are translated.

Law and rules in brief

Under the GDPR, three points matter most: a data processing agreement (DPA) with the provider, data location in the EU or another lawful basis for transfers, and the option to exclude your data from model training. Personal data belongs only in tools that meet these requirements.

Since 2 February 2025, Article 4 of the EU AI Act has required companies that use AI to ensure AI literacy among their staff. The 2026 Digital Omnibus softened this duty: companies must now take measures to promote AI literacy. Short training and an AI policy are a good start.

Since 2 August 2026, the transparency obligations of Article 50 apply. In customer contact it must be recognisable that an AI is speaking or writing, for example on the phone or in a chat. For the machine-readable marking of AI-generated content, a transition period until 2 December 2026 applies to systems that were already on the market. Our separate Klarframe guide on Article 50 of the EU AI Act explains the details.

This guide is not legal advice. For a binding assessment of your case, please consult your legal adviser or data protection officer.

Common mistakes when introducing AI

Many AI projects in SMEs fail at the same points. Knowing them helps you avoid them early:

  • Tool first: a product is bought first and a use case is searched for afterwards.
  • No owner: the project runs on the side, without a person who has time and decision-making authority.
  • No baseline: without measuring before the start, the benefit remains a claim.
  • Private accounts: employees use AI with private logins, so company data can leave the company without a contract or control.
  • No approval step: AI results go to customers unchecked, although a brief human review would catch errors.

Find your starting point with the AI Readiness Check

With the free Klarframe AI Readiness Check, you assess the six foundation areas for your company in about ten minutes. You receive an instant result with your readiness stage, a 90-day plan, suitable solutions and notes on the EU AI Act. On request, we also send you the result as a PDF.

Frequently asked questions

How do I start with AI in my company?

Start with a process that noticeably costs time today, has clear rules and occurs regularly, such as enquiries, quotes or meeting minutes. Define one goal and measure the baseline. Name a responsible person, write a short AI policy and run a time-limited pilot with a small team. Decide on expansion only after you have measured the results.

What does getting started with AI cost?

Costs depend on scope: the number of processes, required interfaces to existing systems, data volume and the level of support needed. A sensible start is a limited pilot for a single process. This keeps the effort manageable, and you decide on the basis of measured results whether and how far to expand.

Do we need an AI policy?

Yes, a short AI policy makes sense as soon as employees use AI. One page is enough to begin with. It defines which tools are approved, which data may go into which tool, who approves new tools and that AI results are checked before they are sent. The policy also supports the AI literacy duty under the EU AI Act.

What do SMEs need to consider under the EU AI Act?

For most SMEs, two points are central. Article 4 requires measures to promote the AI literacy of staff, such as training and clear rules. Since 2 August 2026, Article 50 has required AI to be recognisable in customer contact, for example with phone assistants and chatbots. The GDPR applies in addition. This note is not legal advice.

How long does introducing AI take?

A first pilot with one process can usually run in about 90 days, from taking stock to the decision. The duration depends on how well processes are documented, whether data is findable and which systems need to be connected. Extending AI to further processes is usually faster afterwards, because the foundations are already in place.

Which processes are best suited for AI first?

Processes with clear rules, regular volume and manageable risk are best suited. Typical examples in SMEs are phone and enquiries, quote drafts, meeting minutes, searching company knowledge, reading documents and multilingual communication. It is important that a person can check the result before it is sent to customers or partners.

How do I measure the success of introducing AI?

Before the start, record a baseline metric for exactly the process you want to improve, such as handling time per case, missed calls or response time to enquiries. Measure the same metric during and after the pilot. Add the quality of the results and feedback from the team to the figures.

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Klarframe AI Readiness Check

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