Corporate AI training
Corporate AI training is a hands-on programme in which your teams learn to use AI tools in their own work, within company rules and data protection law. Corrplus designs the programme by role and runs it with examples taken from your processes and with the tools you already use, such as ChatGPT, Microsoft 365 Copilot and Google Gemini.
Book a free callTiming
From a few half-day workshops to a programme spread over several weeks, depending on scope
Pricing
Fixed-scope quote based on participant groups and number of sessions, given in writing after the discovery call.
Tools we use
ChatGPT (Team and Enterprise), Microsoft 365 Copilot, Google Gemini, Anthropic Claude, Copilot Studio, n8n
Who it is for
- Companies whose staff use AI tools on their own, without rules and with uneven results
- Managing directors who want the leadership team to understand AI before committing budget
- HR and digital teams that bought ChatGPT, Copilot or Gemini licences and need them used in daily work
- Software and data teams about to build AI into their products
When it is not a fit
- Anyone looking for a generic certification course. The programme is built around your work and your tools.
- One-off awareness talks after which nobody goes back and applies anything.
What you get
- Role-based curriculumSeparate content and length for leadership, office teams, sales and customer teams, and technical teams.
- Company-specific example libraryPrompts and worked examples taken from your own documents and processes.
- Hands-on workshopsSessions where participants complete one task from their own job with AI, start to finish.
- Safe use rulesShort rules on which data may go into which tool, tied to your company policy, or drafted if you have none.
- Before and after assessmentA short measure of how teams use the tools at the start and at the end of the programme.
- Post-training supportRegular Q&A sessions for a defined period after the workshops.
How we work
Discover
After a free first call we map where each department could use AI and which tools are already licensed.
Design
We prepare the role-based curriculum, the example library and the safe use rules, and agree them with you.
Build
We run the workshops in person in Istanbul or online, in English or Turkish.
Run
Q&A sessions and the final assessment show how the tools are used; we plan extra sessions where needed.
Who needs to learn what?
Giving everyone the same course is the most common mistake in AI training. A managing director asks “where should we invest?”, while an accountant asks “how do I build this spreadsheet faster?”. So we build the programme by role. The leadership session usually comes first, because leadership decides which tools and rules the teams will work with. Hands-on groups stay small so everyone can finish their own task within the session.
| Role | Focus | Typical session content |
|---|---|---|
| Leadership | Decisions and risk | What AI can and cannot do; investment priorities; data protection and accountability |
| Office teams | Daily productivity | Emails, reports and meeting notes; summarising documents; working with Excel |
| Sales and customer teams | Customer communication | Drafting quotes and replies; preparing with customer history; checking tone and accuracy |
| Technical teams | Building AI into products | Using APIs, RAG, automation workflows, evaluation and cost |
How is this different from a generic AI course?
There are plenty of generic courses online. Ours is built around your work. In the workshops people use their own company’s emails, reports and documents, not a fictional company’s. During preparation we collect real tasks from each department and build example sets with personal data removed.
Our trainers do not just talk about AI; they use it to build our own products. Building the website-aware assistant in Promptor gave us many of the examples we use. The question teams ask most comes from that experience too: when does the model get it wrong, and how do I notice?
Safe use: what should never go into an AI tool?
Every role shares one module: safe use. It covers keeping personal data, customer information and confidential documents out of unapproved tools, checking facts the model may invent, and the fact that responsibility for the output stays with the user. For teams in Europe we tie this to GDPR and, for staff in Türkiye, to Türkiye’s data protection law, KVKK. If your rules are missing or thin, we pair the training with AI governance and compliance for lasting rules and technical controls.
This training is tool-agnostic. If you are rolling out Microsoft 365 Copilot, the technical readiness and pilot belong to Microsoft Copilot consulting, and training can be planned as part of that work.
How we start
In a free first call we agree which departments take part, how many people and which tools. We then propose a draft curriculum and session plan in writing.
How would this work in your business?
Tell us where you are in a free first call; we will say plainly where it makes sense to start.
Related services and use cases
Further reading
Does the EU AI Act apply outside the EU?When the EU AI Act reaches companies outside the EU: scope, roles, risk levels and the current application timeline.
How to pick your first AI use caseScore candidate AI use cases on six criteria, filter them for data and risk, and define a pilot you can measure.
Microsoft 365 Copilot readiness checklistA step-by-step checklist for permissions, oversharing, labelling, the pilot and training before Copilot goes live.Our own products
We use the tools and checklists from client projects on our own products too.
All products →Key terms
- Prompt engineeringPrompt engineering is the practice of writing, testing and refining the instructions, examples and context given to a language model so that it produces consistent, accurate results.
- LLM (Large Language Model)An LLM (large language model) is an AI model trained on very large amounts of text that answers questions, summarises, translates and writes by predicting what text should come next.
- AI hallucinationAn AI hallucination is output in which a language model presents information, a source or a figure that does not exist, fluently and confidently, as if it were true.
- AI governanceAI governance is the set of policies, roles and processes that determine how an organisation selects, uses, oversees and manages the risks of its AI systems.
Frequently asked questions
Which tools do you train on?
The ones your company uses or plans to use: ChatGPT, Microsoft 365 Copilot, Google Gemini or Claude. If your team uses something else, we adapt. The goal is not to sell a tool but to work well with yours.
Can non-technical staff take part?
Yes. Sessions for office teams need no technical background. Participants work on tasks drawn from their own emails, reports and documents. Technical teams get separate content covering APIs, RAG and automation.
What should staff never put into an AI tool?
As a rule, personal data, customer information, contracts and financial data never go into an unapproved tool. Your company policy sets the exact list. If you have none, we draft one alongside the training for your legal counsel to review.
Do you train teams outside Türkiye?
Yes. Workshops run online in English for teams anywhere, and in person for teams in Istanbul. Hands-on parts work best in small groups, so larger teams are split into several sessions.
How do we know the training worked?
We run a short assessment at the start and the end: where teams use AI, how confidently and whether they follow the rules. The real test is whether the tools are still part of daily work weeks later.
How is this different from Copilot consulting?
Copilot consulting covers the technical readiness, pilot and agents for Microsoft 365 Copilot. This training is tool-agnostic and focuses on how people work with AI. If you are rolling out Copilot, we run both together.
Corporate AI training: let’s take the first step together
Tell us where you are in one call; we will share a scope and roadmap in writing.
How we start
- A free first callWe pin down the problem and the goal together.
- A 2-week discovery sprintWe look at the data, the process and the tools, and decide where to start.
- A written proposalScope, architecture and timeline, in writing.