In many organizations, there are already employees who know how to work well with AI tools. They formulate good prompts, summarize materials, extract points from documents, and save themselves time.
The problem starts when the knowledge stays only with them. And what happens if the employee leaves the company?
One employee is progressing quickly, others are still unsure how to work with the tools, and the outputs are coming out in different formats. Instead of organized teamwork, little pockets of efficiency are being created.
To make AI use a team capability, a collaborative workflow needs to be built. This means not just giving each employee a tool, but defining regular tasks, templates, a desired output structure, and examples to learn from.
For example, instead of each employee summarizing a meeting in a different way, a fixed process can be created where a meeting transcript is entered, and the tool extracts decisions, tasks, deadlines, and responsible parties into a uniform table.
The same principle can also work for a letter to the authorities, a prospectus summary, a tax regulation review, account analysis, or the preparation of a draft management report.
In practice, the finance team can work with a fixed template for credit aging checks. A structured file is uploaded, and the tool returns a table with overdue customers, exceptional amounts, change compared to the previous month, and an initial recommendation for further investigation. This way, no employee analyzes the file in a different way, but rather everyone works according to the same structure and receives a result that is easy to check and pass on.
To build teamwork, you can use predefined templates within ChatGPT, dedicated projects in Claude, Gemini Gems, or internal organizational tools that centralize instructions, examples, and documents. The idea is not just to choose a tool, but to create a single workflow that the entire team knows how to operate.
Which AI template would save your team the most time? Feel free to share examples with us.
