AI training for a group of companies: what to share and what to adapt
Head office wants one AI program, but group companies use different documents and handle similar tasks differently. Shared training can provide foundations and an opportunity to exchange experience. It needs a clear distinction between work people genuinely do in similar ways and practice requiring local context. The number of companies alone does not determine how many programs are needed.
Syntalith
Syntalith can prepare a training proposal for a group of companies after discussions with head office and representatives of participating businesses. We select tasks, compare available materials, and identify shared learning goals. Before commissioning, the buyer can review proposed joint practice and areas requiring adaptation. Preparation for individual companies should be visible in the scope.
Similar roles can involve different work
Two purchasing departments may compare proposals, but one buys services while the other buys production components. Shared skills include defining the question, selecting sources, and checking a conclusion's basis. People familiar with each purchasing process explain the materials and meaningful differences. The program should preserve that knowledge instead of assuming one company's example is obvious to everyone.
Shared content can cover model capabilities and limitations, task description, document analysis, and response assessment. Adapted practice develops a selected use case, writing the result, and working with its reader. ChatGPT Work or Claude Cowork can provide the environment where the company permits them. There is no need to assume the whole group has identical app and file access.
CIPD describes learning needs at individual, team, and organizational levels and recommends considering them together. For a group, this means examining local requirements alongside the shared purpose of the purchase.
One example can have two useful versions
Suppose two companies practice answering a customer's request to change a date. In one, the author can use a date confirmed by operations; in the other, they first need to collect contractors' availability. The shared discussion concerns clarity and sources, but the drafts must reflect different material. The instructor helps authors explain why their responses differ. Making the wording identical would remove useful context.
In a later independent attempt, participants prepare a response for their version of the task. A reader from their company assesses usefulness while the instructor reviews the approach to AI. The group can share a method while preserving differences in the work.
What head office needs to establish
The engagement needs a coordinator and a contact in each company who understands the work. We agree who selects material and confirms that it may be used. Shared examples can be fictional. Attending one training group does not itself make every company's documents suitable for sharing with other participants.
Assess AI familiarity individually, regardless of which group company employs the participant. Each business may have beginners and experienced users. Grouping practice by task can make more sense than a separate course for each entity; in other cases, differences justify separate sessions. The proposal should explain that choice without promising one universally best format.
The engagement specifies local example preparation, sessions, materials for continued use, and any consultations. If the group wants to pass developed resources to other companies later, their reuse and maintenance also need agreement.
Describe tasks from two companies you want to include in a shared program. We can discuss similarities and where separate practice is needed. See our pricing page for information about working together.
Plan AI training around your team’s work
Tell us about the participants, their tools and experience. We will discuss a suitable training scope and how it would be priced.
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