Many companies already pay for ChatGPT, Claude or other AI tools, yet teams use only part of what those tools can do.
We help apply AI to real work tasks, set clear rules for its use and work out where AI can become part of the working day.
We shape the content around the tasks your team actually performs, the AI tools already in use and the experience already in the room.
We work with document analysis, information retrieval, drafting text and replies, data handling and other real working situations. We cover how to frame requests, how to check results, where human control belongs and how to handle company information safely.
The training focuses on practical AI use in the team’s daily tasks. We work with information retrieval, document analysis, drafting, data processing and other situations relevant to that particular team.
The team learns not only how to frame requests, but how to choose the right working method, check what the AI returns and use company information safely.
We analyse a specific company process and assess which of its stages AI can handle. We look at the data sources, the repetitive tasks, the points of human control and the possible directions for automation.
Through the exercises the team sees how to move from one-off AI prompts to a consistent workflow, an AI agent or an internal tool.
After the training the team knows where and how AI can be applied to daily tasks, how to check the results it produces and which data must not be passed to the tools in use.
For a manager it becomes clearer where better use of existing AI subscriptions is enough, and where a process genuinely needs automation, an AI agent or a separate internal solution.
Before the session we assess the team’s current level of AI use, the tools available and the most pressing work tasks.
From that we prepare the content, the worked examples and the scenarios, all tied to what that team actually does.
Yes. Before the session we assess the AI tools in use, the nature of the team’s work and the most pressing tasks, and we choose the content and the worked examples accordingly.
Yes. Often the tools are already in use but there is no shared way of using them, or only a small part of what they can do is being used. Much of the session goes into applying the existing tools to real work.
No. We match the content to the team’s level. We can start from the basics of practical AI use, or work with more advanced scenarios, process analysis, agents and applying AI to repetitive tasks.
Yes. The exercises are tied to the work the team does. Where real company data cannot be used, we prepare equivalent tasks that exercise the same working principle.
Yes. We cover what information may be passed to AI tools, how to assess the access those tools have, when human review is required and how to check what the AI returns.
No. AI is not the right tool for every task. We also show where a simpler process, rule-based automation or an existing system feature is enough.
Yes. If the session identifies a process that needs a separate technical solution, we can assess it as its own automation, AI agent or internal system project.
We start with a short conversation about the team, the AI tools in use and the main work tasks. From there we can suggest the right direction and format.
“I had already audited my own site and thought everything was fine. Kognev's audit revealed new issues in places I would never have thought to look.”
