Practical AI training for companies teaches teams how to use ChatGPT, Microsoft Copilot, Claude and Gemini in daily work: from prompt engineering and document analysis to process design. MKM Labs delivers it under ISO 9001:2015 no. 17489 (QS Zürich AG), whose scope covers training and consulting in AI and digital skills. A 1-day workshop starts at PLN 9,900 net per group of up to 10 people; a 2-day training starts at PLN 13,900 net; online training starts at PLN 6,000 net per day (minimum 6 hours). Closed-company training only. Teams leave with a prompt library, a safety checklist and a ranked list of automations to implement after the workshop.
MKM Labs Sp. z o.o. holds an ISO 9001:2015 certificate (no. 17489, QS Zürich AG) whose scope explicitly covers training and consulting services in IT, AI, programming and digital skills. The July 2026 recertification audit closed with zero non-conformities. Certificate page - Audit report (PDF).
Teams learn how to use AI for real business work: sales, marketing, operations, HR, documents and data analysis.
The company receives prompt libraries, safety checklists and a clear map of processes worth automating.
Managers understand where AI can create ROI and where automation would be risky or premature.
Participants work on their own cases, so the workshop leaves usable workflows, not only notes.
Co-founder
He runs closed-company AI training: ChatGPT, Microsoft Copilot, Claude and Gemini on the client's real processes. At MKM Labs he owns discovery, proposals, AI training, workflow automation and steering a project from kickoff to production. He combines Claude API, Python and Next.js, so the workshop ends with a ranked list that can be implemented.
Modules are adjusted to the department and participant level. We practice on ChatGPT, Microsoft Copilot, Claude and Gemini. Executive workshops, sales enablement, marketing workflows, operations and support training need different examples.
How language models work, where they fail, how to verify answers and how to define internal AI usage rules.
Roles, context, input data, output format, examples, iteration and reusable prompt patterns for office work.
Finding repeatable tasks, scoring automation potential, designing a simple workflow and preparing a ranked list of automations to implement after the workshop.
Lead analysis, emails, offers, personas, research, scripts, FAQs, ticket summaries and quality control.
What not to upload to AI, how to anonymize data, how to work with documents and when private models or RAG are needed.
We work on real participant cases and finish with a prioritized list of AI implementations that can start after training.
Prices are per closed group of up to 10 people, not per person (about PLN 1,000 per person). We run closed-company training only - no open public sessions. A longer cost breakdown is in How much AI training for companies costs. Prices current as of September 2026.
Intensive AI training for one team. Best for starting quickly and aligning practical AI usage.
Training plus practical workshops on company processes and a ranked list of automations to implement after the workshop.
Live with the trainer, for a group of up to 10 people. Good for distributed teams and shorter modules.
Training cycle for multiple departments with consulting and an internal AI working standard.
We run workshops across Poland and on site, in the office or online.
After the workshop the team leaves with a ranked list: what a prompt can fix, what needs a workflow and what should become a live system.
AI training that leads to implementation
Typical AI training ends with people knowing what ChatGPT is, then returning to old habits the next day. We build the program around real roles and tasks: sales teams write offers and follow-ups, marketing prepares research and variants, HR works on job posts and summaries, administration organizes documents and managers learn how to evaluate processes by ROI.
That turns the training into a workshop. The team leaves with prompts, workflow examples and a list of processes that can be automated.
Participants need to know what not to paste into public AI tools, how to anonymize data, when to use company accounts, how to verify answers and where a human decision must remain in the loop. This matters especially in customer support, HR, finance, B2B sales and administration.
We assume that a model can be wrong, so we teach quality control: logs, limits, roles, examples, human approval for risky decisions and clear rules for working with data.
The highest value appears after the exercises. You can see which processes are ready for simple prompts, which need automation and which should become a larger AI project. We collect those observations into a ranked list: quick improvements, workflow prototypes and larger implementations that require integrations.
This lets the company move from education to action with clear decisions: what to deploy now, what to test next month and what to avoid because the risk is too high.
We create a prompt library for company roles: sales, marketing, customer support, administration, HR and operations. Each prompt has a goal, input data, expected output format and verification rules.
We define which tasks can be handled in public AI tools, which require company accounts and which should stay outside the model until a safer architecture is implemented.
The team gets a simple way to evaluate AI answers: checking sources, spotting hallucinations, comparing variants, escalating to a human and avoiding sensitive data.
Managers receive a map of processes for automation. Training then naturally shows which workflows are worth prototyping later.
Training teaches the team how to work with AI on their own processes. An implementation is a live system with integrations and monitoring. We keep those as two separate decisions.
Good AI training separates participant maturity levels. A person opening ChatGPT for the first time works differently than a manager looking for savings in a process or a technical team that wants to build automations and agents.
After training, the team should not be left with a vague "use AI more often" message. We define concrete scenarios: how to prepare an offer, summarize a document, compare answer variants, perform research, build a simple workflow and when to stop using the model.
That is why AI training should be treated as a competence implementation, not a one-off inspiration session. A well-prepared workshop gives the team a shared language, reduces data risk and shows managers where automation is worth investing in.
Training organizes how people work: prompts, tools, security rules, examples and responsibility for the result.
Managers get a language for AI evaluation: where ROI exists, where risk is too high and where a separate technical project is needed.
After the workshop there is a list of automation candidates, but system delivery starts only after data and integration assessment.
Training defines which data should not be entered into AI, when company accounts are needed and how answers are verified before use.
The best workshop ideas become a ranked list of prototypes, so education turns into concrete business decisions.
AI training
Common questions about AI training for companies - format, cost, security, team level and implementation after the workshop.
For sales, marketing, support, administration, HR, operations teams and business owners who want to use AI in real work, not only watch a trend presentation.
No. We adapt the program to the team level. Non-technical teams learn practical prompts and workflows, while technical teams can cover automation, APIs and AI agents.
We first define roles and processes. Then participants work on company examples: emails, offers, documents, research, reports, support cases and automation ideas.
Yes. We run online, onsite and hybrid training. Online works well for distributed teams, while onsite is useful for intensive implementation workshops.
The listed price covers a closed group of up to 10 people. Larger teams are split into groups or quoted separately so the exercises stay concrete.
Yes. They receive prompt libraries, checklists, workflow examples, tool recommendations and a list of processes to continue after the workshop.
Yes. We explain what not to upload to public AI tools, how to anonymize data, when company accounts are needed and how to design safer workflows.
Yes. Training can lead into an audit, prototype, process automation or a dedicated AI agent for a specific department.
Yes. We adapt examples to services, e-commerce, production, logistics, education, marketing, customer support or administration.
We measure implemented workflows, saved time, prompt quality, faster offer creation, shorter reporting cycles and improved customer response quality.
Ideally they already have access to ChatGPT, Microsoft Copilot, Claude or Gemini. If the company does not have a standard toolset yet, we help select a practical and safer setup before the workshop.
Yes. Good training exposes repeatable processes and helps choose the first AI project with measurable ROI.
Company, headcount, preferred date and contact. We reply with a program proposal - no redirect to another page.
Free 30-minute consultation. We'll come back with a proposal within 24h.