AI training for a team with different levels of experience

At Syntalith, we offer team training prepared around employees' tasks, their familiarity with AI, and the expectations of the people using their work. With L&D and the manager, we establish what the group needs together and which skills call for separate practice.

The trainer selects material and reviews participants' work, helping beginners understand what to give the tool and confident users see why their approach breaks down with more difficult material. You can see how the proposed program assigns practice to different participants before booking training.

Find out what people do with AI

Asking how often someone uses a tool is not enough to choose their training. A person who writes short emails every day may have no experience analyzing several documents. Someone just starting out may know the process well and immediately spot a faulty conclusion. Before training, discuss actual tasks and look at a piece of work alongside the author's explanation of their choices.

Job title does not establish AI proficiency either. A manager may be an advanced user, while a specialist needs an introduction. Someone drafting a reply needs different practice from a manager deciding whether it can go to a customer. Domain knowledge helps people understand the material, but does not replace practice with the tool.

CIPD's August 20, 2025 factsheet on learning needs connects organizational needs with assessment of current skills and knowledge. It describes formal or informal assessment at individual, team, and organizational levels. This provides a basis for discussing the program without assigning one level to the entire group.

What to work on together

The common foundation concerns how AI is used in the company. Staff need to understand the model's capabilities and limitations, data-use rules, and when a response needs checking or consultation. We agree on which company-approved tool and materials to use in the sessions. Fictional documents can reflect the team's work.

The program also covers defining the task's purpose and reader, selecting sources, analyzing documents, and drafting a response. Shared discussion helps establish what the person receiving the work needs. Quickly generating text does not help the team if a manager later has to reconstruct its basis. Practice therefore includes retaining references and explaining choices.

We tailor the introduction to what the group already knows. Existing users do not need to repeat every basic action in the tool, but they should know the same company rules for data use and handing work to colleagues.

A shared goal with different levels of difficulty

Suppose the team prepares customer replies. A beginner works with a short thread and complete information, independently defining the message's purpose, drafting it, and checking it. A daily AI user receives longer correspondence in which a later message changes an earlier agreement. Both prepare a customer reply, but face different difficulties.

Feedback on the first piece may address missing context that made the answer too general. On the second, the issue may be recognizing that the model retained an outdated agreement. The trainer explains these differences using the authors' work, while the shared discussion focuses on what the recipient needs. A confident colleague should not do the beginner's task for them, since that removes the chance to practice independently.

Leave room for an independent attempt

This group's program needs time for questions and revisions, although people will need that time on different tasks. Shared sessions can be combined with separate practice for some staff, or the group can return to harder material after initial attempts. Sessions, preparation, materials for later use, and any review after a period of practice are agreed in the proposal.

In a later independent task, each person works on a new case that calls for the skills they practiced. The manager can see who still needs help selecting sources and who needs help assessing or editing a response. Our article on assessing AI skills before and after training explains comparison of work in more detail.

We establish each person's access to the tool with the company before training. If employees have entirely separate goals, see our guide to individual versus team AI training.

Talk to Syntalith about a program for your team. Describe the tasks people perform with AI and where they need help. We can discuss the shared foundation and practice for different team members; further service information is available on our pricing page.