Kazatomprom AI Training

Kazatomprom needed an applied introduction to AI that would not stop at "write a post with ChatGPT". The program had to explain the basics clearly, then show where AI fits into reports, meetings, letters, counterparty analysis, transaction checks, and sanctions-risk screening. The training was built as two dense days: first the mechanics of modern generative AI, then practical business scenarios where participants could see what changes in their own work.

2 days Program
Corporate teams Audience
Video testimonial Media
Need

Move from curiosity to useful habits

People had already heard about ChatGPT and other generative tools. The harder question was practical: how do you use AI when the work is documents, meetings, reports, counterparty files, and risk-aware decisions?

  • Explain AI evolution and generative models in plain language.
  • Teach prompt structure: context, task, constraints, and output format.
  • Show workflows for meetings, emails, reports, counterparties, transactions, and sanctions risks.
Workshop room during the corporate AI training
Discussion of practical business scenarios
Program

A practical two-day AI workshop

Day one covered foundations: AI history, modern generative models, prompt engineering, document simplification, idea generation, meeting transcription, summaries, and business correspondence.

Day two moved into applied scenarios: anomaly detection in operational and financial reporting, counterparty evaluation, stakeholder affiliation, transaction parameters, supply chains, price checks, and sanctions-risk screening.

Prompt work

Participants learned how to give the model context, define the task, set limits, and ask for a usable format.

Meeting intelligence

The course covered tools for recording, transcription, action items, and structured meeting summaries.

Business risk scenarios

The second day connected AI to reports, counterparties, transaction parameters, and sanctions-risk checks.

Workshop design

Theory only where it helped the work

The content was layered deliberately: enough theory to understand modern generative AI, then work patterns people can reuse: write, summarize, compare, check, structure, and prepare a decision.

Generative AI overview: ChatGPT, DALL-E, MidJourney, and business examples.
Prompt-engineering patterns for clearer answers and less rework.
Meeting capture, transcription, action plans, and dialog analysis.
Email drafting, correction, tone adaptation, and document simplification.
Finance, reporting, counterparty, transaction, and sanctions-risk scenarios.
ChatGPTPrompt engineeringMeeting toolsBusiness risk analysis
Hands-on work with practical AI scenarios
Training material connected to real corporate tasks
Workshop atmosphere from the two-day program
Video testimonial

Participant testimonial

Before the testimonial, the page now shows what happened in the workshop: the two-day structure, the practical scenarios, and the way the content moved from AI basics into corporate reporting, counterparties, transactions, meetings, and business writing.

What changed

Common language

The team left with shared vocabulary for AI, prompts, outputs, and practical limits.

Concrete workflows

The examples were tied to daily work, not abstract demos.

Reusable program

The format can be adapted for departments and deeper operational tracks.

Tell us what you're building

Start with a few details

We reply within one business day. Then Azamat joins every first call personally, so you get an honest scope, budget, and fit from the person responsible for delivery.

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