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AI training for companies
How much time do your people spend on emails, offers and reports? Let's find out where AI can win it back.
A consultant comes to your company and shows, on your people's own tasks, what AI can make faster and simpler. After the training we keep working with the team: practice, online consultations and a quarterly AI review. You get a summary: what we found in each department and what needs your decision.
Training at your company · On participants' real tasks · Online consultations afterwards · Quarterly AI review
Illustrative example · improvement card from the workshop
- Today
- A long email from the customer, searching folders for similar offers and writing from a blank page.
- With AI
- AI turns the customer's requirements into a list and drafts a reply on the company template.
- Person
- Checks the draft, sets price, discount and lead time, decides whether it goes out.
- Data
- The request only goes into the AI tool the company has approved.
Next: try it in practice, note the time before and after, review it at the consultation.
Starting point
AI is already in companies. The question is whether your people can use it in their work.
Some of the team use ChatGPT on their own, each differently, and some paste everything into the chat, customer data included. Meanwhile the same things still take the most time as a year ago: emails, offers, meeting notes, reports and looking for information in documents.
The tool is often already there. What's missing is someone who shows people where AI fits their work, what not to hand over to it and how to check the result.
Sound familiar?
- “Everyone uses it their own way, and some don't use it at all.”
- “I'm not sure I'm allowed to paste this into the chat.”
- “I tried it once. It was all generic, so I wrote it myself.”
- “We have the licences. A few people use them.”
- “The training was interesting, but a week later everything was back to normal.”
Do the simple maths
Work it out for one team
This is the pool of time, not a promised saving. We assume 160 working hours a month. In the training we check which part of this work AI can help with.
The question we start with
“Show me what you do every day. Let's see where AI can help you.”
Our approach
We don't teach AI in isolation from the job. We look for uses in specific roles.
Instead of showing what AI can do in general, we work out with each participant what it can change in their own work. We look for tasks that can be done:
Faster
The first version of an email, offer or note is ready straight away. People edit it instead of writing everything themselves.
More simply
A long contract, report or email thread reduced to what matters for this particular person.
Partly automatically
Repetitive steps, such as copying data from emails into a table, done with a ready-made prompt and template.
Independently
An Excel formula, a table or a presentation without waiting for someone in another department to find the time to help.
To one standard
The same templates, checklists and reply standards every time, whoever does the task.
Without retyping
Less retyping, copying and pasting, and searching for the same information in several places.
It's not about replacing people. It's about giving good employees better tools.
Run by a practitioner, not a lecturer
Mientha consultants roll out automation and AI agents in companies every day. They know where AI saves time and where it creates risk, and they show it on your team's tasks, not on examples from the internet.
When the training surfaces something bigger than a single prompt, for example a process that could be automated, it goes onto a separate list for management. What happens to it is your decision.
See our implementationsWhy we don't stop at the training
One day leaves inspiration. Habits form in the weeks that follow.
A classic training ends when the trainer leaves the room. Participants go back to a full inbox, and the workshop ideas lose out to the daily rush. That is why, with us, the training is the second of six stages, not the whole service.
The usual wayClassic training
- Training
- Inspiration
- Back to work
- Old habits
Mientha's methodAI that stays
- Discovery
- Training
- Application
- Practice
- Consultation
- Improvement
- Embedding
- Growth
Every quarter another round
After the training every participant has an implementation task: they watch their own work and test what they learned on real cases, not on exercises.
The first failed attempt is when people usually give up. The consultations deal with exactly those problems, so the team doesn't slip back into old ways.
AI changes fast. Every quarter we come back with what will be useful in your work and check which improvements have stuck.
The “AI that stays” method
Six stages: from getting to know your company to habit
On paper you are buying a training. In practice you get AI built into your team's daily work, spread over six stages. Before the training we get to know your company, and afterwards we help people embed the new habits and take them further.
Stages 1–3Before and on the day
- 01
Getting to know your company
We talk to you and to the people who lead the teams, and participants describe their typical tasks in a short survey. This way, before the training, we know what each role does and what takes the most time.
ResultThe consultant arrives with examples from your company, not a one-size-fits-all deck.
- 02
Training at your company
Fundamentals first: how AI works, where it gets things wrong, how to describe a task and how to check the result. Then practice on examples and problems as close as possible to participants' daily work.
Result“OK, now I know where I can use this tomorrow.”
- 03
First improvements
While still in the room, everyone looks for simple uses they can take straight back to work and writes them on their own improvement card.
ResultEveryone leaves with their own list, and you get a first picture of where AI can help in the company.
This is where most trainings end. For us, the second half starts here.
Stages 4–6After the training
- 04
Practice
Participants get an implementation task. Over the following weeks they watch their own work and ask themselves: “What regularly takes up a lot of my time, and can AI help me with it?”. They test what they learned, note the time before and after, and write down new ideas.
ResultThe team tests new ways of working on real tasks, not just in the training room.
- 05
Consultations
We meet online: one to one, as a team or separately with each department. People come with specifics: “I do this every week. Can it be done better?”.
ResultRefined prompts, templates and ways of working the team can use every day.
- 06
Quarterly AI review
Every quarter we come back to the team, on site or online, with three questions: what is new in AI that will be useful to you, what has stuck and what comes next. We fix what doesn't work and look for further uses.
ResultYou don't have to follow hundreds of AI announcements. We pick the ones that will be useful to your company.
After every review another round: practice, consultations, review.
The training day
What the training looks like at your company
The training takes one day or two half-day blocks. We form groups of up to 12 people by department or role, and the consultant works with people at their own computers, on their own tools and documents.
Fundamentals
How AI works, where it gets things wrong and why. Which tools you use and which data must not go into them. How to describe a task to get a useful result, and how to check it.
Your examples
We show what AI can do on tasks collected before the training: your emails, offers, reports and procedures, anonymised where needed.
Working on their own tasks
Participants work on what they do every day. The consultant moves from desk to desk and helps wherever the result isn't good enough yet.
Plan for the coming weeks
Everyone notes on their improvement card what they will use straight away and what they will test in practice. They get an implementation task and a consultation date.
Each participant leaves with
- an improvement card with their own tasks
- tested prompts and templates for their work
- clear rules: what to use and what not to paste
- a practice plan for the coming weeks and a consultation date
You get
- a summary of the uses found, by department
- a list of decisions to make, for example on tools and data access
- topics for bigger improvements that go beyond AI alone
- a plan for the consultations and the first quarterly review
AI in specific roles
AI is not just for marketing and IT
AI can help wherever people write, read, compare and summarise a lot. Below are examples you can start with. Which of them make sense for your company is something we agree when we get to know it.
Sales
A salesperson earns money for the company when talking to customers. Preparation and paperwork take up time that is then missing for those conversations.
- Preparing for a callA note on the customer's company from public sources, questions to ask and likely objections.
- ResearchThe market, competitors and the latest news about the customer in one place.
- OffersRequirements from the enquiry put into a list and a draft reply on the company template.
- Follow-upA summary of the call and an email with the agreed points, ready to send once checked.
- Making sense of informationConclusions from notes, contact history and a CRM export.
Stays with peoplePrice, discount, terms and everything that goes to the customer.
DataCustomer data and price lists only in the tool the company has approved.
Leadership and managers
Managers get more information than they can read. AI can help to put it in order before a decision has to be made.
- Preparing meetingsAgenda, materials and questions based on earlier notes and emails.
- SummariesA long report or email thread cut down to what needs a decision.
- Reviewing documentsContracts, offers and departmental reports: key points, risks and inconsistencies.
- Organising informationNotes from many sources brought together into one picture.
- Supporting decisionsScenarios, arguments for and against, and the questions nobody has asked yet.
Stays with peopleThe decision. AI organises information but does not decide for you.
DataStrategic and financial documents only in a tool with proper data protection.
HR
HR involves a lot of writing and answering the same questions. It is a good place for first improvements, provided there are clear rules for personal data.
- Preparing materialsJob ads, role descriptions, onboarding materials and presentations.
- CommunicationInternal announcements and answers to employees' recurring questions.
- Reviewing documentsPolicies and procedures: summaries, version comparison, list of changes.
- RecruitmentInterview questions tailored to the role and tidy notes after interviews.
Stays with peopleAssessing candidates and every decision about people.
DataCVs and employee data strictly under company rules. AI does not assess candidates.
Marketing
Marketing usually finds AI on its own. What is missing is a shared standard, so results don't depend on one person.
- ResearchMarket, competitors and trends in one summary.
- AnalysisCampaign results and customer feedback turned into conclusions.
- ContentDrafts of posts, articles, newsletters and product descriptions in your brand's voice.
- PlanningA publishing plan and a campaign brief based on the goals.
- Working with materialsShortening, reworking and translating what you already have.
Stays with peopleStrategy, brand voice and sign-off on every publication.
DataPre-launch materials are treated as confidential.
Administration and back office
The back office keeps the company in order. It involves a lot of repetitive work that can take less time with AI.
- DocumentsLetters, minutes and summaries on company templates.
- CorrespondenceReplies to routine matters and keeping the inbox in order.
- SummariesMeeting notes and summaries of long documents.
- Repetitive tasksTables, checklists and moving data out of documents.
Stays with peopleSignature, sending and every unusual case.
DataDocuments with personal data only in an approved tool.
Finance
In finance, AI does not replace accounting. It can help with commentary, analysis and spreadsheet work.
- Commentary on resultsA draft explanation of variances for the monthly report, based on the tables.
- ExcelFormulas, data clean-up and macros without searching forums for answers.
- Reviewing documentsContracts, payment terms and regulations: the key clauses as bullet points.
- ProceduresInstructions, for example for month-end close, written up from notes and emails.
Stays with peopleThe figures in reports and every financial decision.
DataUnpublished financial data only in an approved environment.
Customer service
The same questions come back every day. AI can help to answer faster and to one standard.
- RepliesA draft reply based on your knowledge base and templates.
- ComplaintsLong correspondence reduced to the facts and a list of missing information.
- One standardThe same tone and quality of replies, whoever is answering.
- Knowledge baseNew instructions and answers prepared from the most frequent questions.
Stays with peopleThe decision on the customer's case and the reply in disputed matters.
DataCustomer data only in the tool the company has approved.
Purchasing and logistics
Comparing quotes, corresponding with suppliers and writing instructions is work where haste and mistakes come easily.
- Comparing quotesSupplier quotes side by side in one table: prices, lead times and terms.
- CorrespondenceEnquiries, reminders and complaints to suppliers on ready templates.
- Contracts and termsThe key clauses of contracts and delivery terms as bullet points.
- InstructionsInstructions and checklists for the warehouse and transport.
Stays with peopleChoosing the supplier, negotiating and the order terms.
DataSupplier prices and terms only in an approved tool.
These are examples, not a fixed programme. What makes sense in your company depends on the tasks, the tools and the security rules. Whenever company data is involved, your rules apply.
What can change
Less routine in daily work. More independence in the team.
We don't promise percentages. The effect depends on how much repetitive work a team has and how consistently people apply the new habits. That is why participants note on their improvement cards how long a task took before and after the change, and at the quarterly review you see figures from your own company, not from someone else's slides.
In the team's work
- Less retyping, copying and pasting, and writing from scratch
- Drafts of emails, offers, notes and reports ready faster
- Easier preparation of documents, analyses and communication
- Confidence about what to use, how to check the result and when not to use AI
In the company
- More time for what you value your people for: customer work, analysis and decisions
- Employees who use new tools on their own
- Shared rules instead of “everyone their own way”
- A habit of looking for improvements: people put forward new ideas themselves
- A list of improvements from which you can pick topics for further automation
Who it's for
For companies where people write, read and analyse a lot
The size of the company matters less than the kind of work. The training suits a small or mid-sized company as well as a department of a large organisation.
Small and mid-sized companies
The owner can see the team is stretched, and another office hire is not the only answer. In a small company one group and one day is enough; in a larger one we train selected departments.
Departments in large organisations
Sales, finance, HR or a shared service centre that already has AI tools but does not yet see the effect in daily work. The training can serve as a pilot before a wider rollout.
Boards and senior management
When leaders first want to see for themselves where AI can help the company, before deciding on training their teams or buying tools.
You'll get the most out of it if:
- a large part of the work is emails, documents, offers, reports and notes,
- people already try AI on their own, but without shared rules,
- the company has AI tools, but few people use them,
- you want to start with people and their work, not with buying another system.
It's not the right choice if:
- you are looking for a one-hour inspirational talk for a company conference,
- you need a programming course or training on building your own AI models,
- the company does not allow any AI tool at all. In that case, let's start with a conversation about the rules.
Frequently asked questions
Questions worth asking before you decide
Your question isn't here? Ask it on a call and we'll answer it using your company as the example.
Book a 15-minute callYes, and that is where we start. Before we come, we talk to you and the team leaders, and participants describe their typical tasks in a survey. The examples and exercises come from your work.
No. We start with the fundamentals, so anyone can join. People who already use AI get harder tasks in the workshop and can help the rest of the group.
Yes. The consultant comes to you, because the best place to learn is where the team works every day: at their own computers, tools and documents. The consultations after the training are held online.
Yes. We form groups by department or role so that the examples fit the participants' work. Several departments can be trained on one day in separate blocks or on consecutive dates. Consultations and quarterly reviews can also be separate for each department.
The training takes one day or two half-day blocks, scheduled around your calendar. The practice afterwards is not an extra task: it is the same daily work, done differently. Consultations are held online.
The second half of the method begins: practice on an implementation task, online consultations and the quarterly AI review. You get a summary: what we found and what needs a decision on the company's side.
They are online meetings, one to one, as a team or separately for departments. Participants bring a specific situation, for example: “I tried to do X, but I have this problem”, and the consultant helps refine prompts, templates and the way of working with AI.
Yes, that is what the quarterly AI review is for: new capabilities useful in your work, a check on what has stuck, and further uses. You don't have to follow every new announcement yourselves.
For as long as we agree in the offer. We set the scope before the start: the number of groups and consultations, and for how many quarters you want reviews. You know in advance what you pay for and how long we agree to work together.
We work according to the security rules that apply in your company. Before the training we agree with you and the person responsible for IT which AI tools the team may use and which data must not go into them. In the exercises we use anonymised examples or ones you have approved, and the rules for using AI are part of the programme from the first hour. We don't need access to your systems for the training.
Participants can take the first uses back to work the next day, because they write them down while still in the room. What has stuck shows at the consultations and the quarterly review, and the improvement cards, with the time before and after the change, show it in figures from your own company.
Before the training we agree with you how to talk about it. In the room we say openly: we work on participants' tasks so that they have less routine. From the start, the exercises are about their own work.
The ones you already have or that the company approves, for example Microsoft 365 Copilot or ChatGPT for business. If you are still choosing a tool, we discuss it when we get to know the company. The training is not tied to buying any particular product.
The price depends on the number of participants and groups, the number of departments and the scope of consultations and quarterly reviews. On a short call we agree the scope, and you receive the quote in writing.
After the training. If the team wants to go further than working with an AI assistant, we also describe AI agents on Microsoft Teams and process automation for whole processes.
First step
Tell us what your team does. We'll tell you where to start.
In 15 minutes we pick the teams and tasks to start with. Then you receive a written proposal for the scope and a quote.
We reply within one business day · A 15-minute call, no obligations