How to Introduce AI in Your Company in 30 Days

I know two types of companies. The first ones ignore AI completely. Management says "it's just hype, we'll wait," while their competition automates reports, speeds up sales, and saves dozens of hours each week. The second type gets overly excited, buys Enterprise licenses for everything at once, and three months later discovers that nobody actually uses the tools. Both approaches are wrong.

Over the past year at Rise.sk, we have helped companies ranging from 20 to 500 employees bring AI into real daily operations. Not as an experiment. As a working tool that people actually use. And we have repeatedly seen a 4-week approach work well. It is not perfect, but it delivers results. Here is the plan.

Week 1: Audit and Pilot Selection

The first week is not about technology. It is about understanding where the pain is.

Mapping Processes That Eat Time

Sit down with team leads and ask one question: "Where does your team repeatedly do something that is boring, predictable, and takes more than an hour per week?" Write it all down. You are looking for things like:

• Writing sales proposals from templates
• Summarizing meeting notes
• Answering repetitive questions from clients or internal colleagues
• Creating recurring reports from data
• Transcribing and categorizing documents
• Initial screening of resumes or applications

The goal is not to find the company's biggest problem. The goal is to find a specific, repeatable task where AI can help quickly and measurably.

Selecting 3 Candidates for Pilot

From the full list, pick a maximum of 3 processes. No more. We use three criteria:

• Frequency: Does it happen at least several times a week? If it is once a quarter, it is not worth automating first.
• Structure: Does the task have a clear input and output? If yes, AI can work with it. If it is "sometimes this way, sometimes that way, and it depends on gut feeling," set it aside.
• Measurability: Can you say how much time it takes now? Without that baseline, you will never know if AI helped.

Week 2: Tool Setup and Pilot Launch

Now you know what you want to solve. Time to pick the tools.

Choosing the Right Tool

There is no point buying a tool and then looking for a use case. Start from the process, not the technology. In practice, these tools work well:

• Microsoft Copilot for M365 -- If your company lives in Outlook, Teams, and SharePoint, this is the fastest path. Copilot summarizes emails, generates presentations, creates drafts in Word. License runs about 30 EUR per user per month.
• ChatGPT Enterprise/Business -- A more universal tool. Good for teams that need to generate text, analyze documents, and work with data. Business tier starts at 25 EUR per user per month.
• Notion AI -- If you use Notion as a knowledge base or project management tool, AI is natively integrated. Useful for summaries, content generation, and Q&A over company documents.
• Atlassian Intelligence and Rovo -- For teams on Jira and Confluence. Rovo searches across the entire Atlassian ecosystem. If you have hundreds of Confluence pages, this is a game changer.
• Slack AI -- Channel summaries, search across conversation history, answers to questions from thread context.

Setting Up Access and Rules

Do not buy licenses for the entire company. Start with 5-15 people who will run the pilot. Set up:

• Who has access and to which tool
• What data can go into AI (and what absolutely cannot -- personal data, sensitive financial data, trade secrets)
• Where outputs are saved and who reviews them

You do not need a 20-page policy document. A single page with clear rules is enough. What matters is that it exists from day one.

Week 3: Training and Adoption

You have the tool, you have access set up. Now comes the hardest part -- convincing people to actually use it.

AI Champions in Teams

In every team that is part of the pilot, identify one person who is enthusiastic about technology. It does not have to be someone from IT. It can be a marketing manager, a sales rep, or an account manager. What matters is that this person wants to try new things and is not afraid to ask questions.

These people are your AI champions. Give them an extra day or two of training, and they then help their colleagues in their own team. This works 10x better than centralized training for 50 people in a conference room.

Framework: Task, Context, Output, Check

Teach people to work with AI using a simple framework:

1. Task -- What exactly do you want AI to do? Be specific. Not "write something about the product," but "write 3 versions of an introductory email for a potential logistics client."
2. Context -- What information does AI need? Attach data, samples, previous outputs. The more context, the better the result.
3. Output -- What format do you expect? Bullet points, table, continuous text, maximum length? State it upfront.
4. Check -- Never send an AI output forward without reviewing it. Always. This rule has no exceptions.

What to Measure

• Active users -- How many people in the pilot group use the tool at least 3 times per week?
• Time saved -- How many minutes or hours per week does a specific process save thanks to AI? Ask people directly and have them log it.
• Output quality -- Are AI outputs comparable to or better than before? Let the people who work with the outputs evaluate this.

What Is NOT a Metric

• Number of prompts per day (tells you nothing about value)
• The "wow" feeling at the first demo (fades within a week)
• Number of installed tools (quantity without quality)

Week 4: Evaluation and Scaling

The fourth week is about hard data and decisions.

Measuring Pilot Results

Collect data from the pilot group. For each of the 3 pilot processes, answer:

• How much time was actually saved?
• What was the output quality compared to manual work?
• What resistance was there, and what caused it?
• Would people keep using it even without someone checking on them?

Decision: Scale, Adjust, or Stop

For each pilot, make one of three decisions:

• Scale -- It works, people use it, it measurably helps. Expand to additional teams.
• Adjust -- The potential is there, but something is not working. Change the tool, change the process, provide more training. Give it another 2 weeks of fine-tuning.
• Stop -- It does not work. AI does not make sense for this particular process. That is not a failure -- it is a valuable insight.

Internal AI Rules

Based on the pilot, write a simple internal policy:

• What we use AI for and what we do not
• What data must not be entered into external AI tools
• Who is responsible for reviewing AI outputs
• How to handle situations where an AI output contains errors

Budget and Costs

Calculate the real costs: licenses, training time, administration time. Compare with time saved. In most cases the ROI is quite clear -- if it is not, that is a signal you picked the wrong process to automate.

Checklist: 30-Day AI Plan

• [ ] Map time-consuming processes in every team
• [ ] Select 3 pilot processes (frequency, structure, measurability)
• [ ] Choose a tool based on existing infrastructure
• [ ] Purchase licenses for the pilot group (5-15 people)
• [ ] Write a one-page document with AI usage rules
• [ ] Identify an AI champion in each pilot team
• [ ] Train AI champions (framework: Task, Context, Output, Check)
• [ ] Launch pilot and measure: active users, time saved, output quality
• [ ] After 2 weeks, collect feedback from the pilot group
• [ ] Evaluate results for each pilot process
• [ ] Decide: scale, adjust, or stop
• [ ] Write an internal AI usage policy
• [ ] Calculate ROI and prepare budget for scaling

Rise.sk Case Study

We ran an AI Skills Sprint for a mid-size company in Slovakia. When we started, their relationship with AI was "a few people tried ChatGPT for writing emails." No structure, no measurement, no rules.

In 4 weeks, we went from "we tried ChatGPT for fun" to having 3 production workflows saving 25 hours per week. One team automated sales proposal preparation. Another used AI to summarize client calls. The third used it to generate first drafts of technical documentation.

The key was not the tools. It was the structured approach to identifying where AI actually makes sense -- and where it does not.

What Is Next?

If you want to bring AI into your company and do not know where to start, get in touch. We will not try to sell you tools. We will help you find the processes where AI genuinely saves time and money, and walk you through the entire 30-day plan.

Contact us and we will schedule a no-obligation introductory call.