Employees learn useful AI practice by working through familiar tasks and inspecting what the output gets wrong. A completed exercise should show how they checked the evidence and changed the work.
An operations log records a machine stoppage and a later restart. An AI-generated summary says the stoppage was caused by poor maintenance, although the log records no cause. What should the employee change before sending the summary?
Remove the unsupported cause. The summary can report the stoppage, its recorded timing and the restart. It should leave the cause unresolved until the appropriate investigation supplies evidence.
Training should require the employee to point to the unsupported sentence, explain the correction and produce a revised summary. That demonstrates a review action a manager can assess.
Choose a task from the employee's role, define the required output and supply approved source material. Ask AI for a draft, then check facts, omissions and unsupported inferences. Revise the work and retain enough evidence for a colleague or manager to review it.
Employees practise defining a task, providing context, inspecting assumptions and comparing outputs. They decide whether AI is appropriate for the work and check the result before using it.
The resulting work should include enough context, sources and reasoning for another person to review it.
HR teams may practise interview rubrics and learning plans. Finance teams may examine variance explanations and research notes. Faculty may redesign an assessment, while operations teams may summarise incidents.
Function-specific examples help employees assess how AI applies to their own work and help managers choose tasks for a follow-up trial.
Follow-up reviews examine which tasks employees attempted, what they checked and what required revision. Managers and teams can compare examples and record questions that need further work.
The review identifies routines to retain and workflows to improve next.
The survey reported that 75% of knowledge workers were using AI at work, while only 39% of global AI users said they had received AI training from their company.
Employee cohorts use work samples from participants’ roles. Each exercise asks what AI can assist with, what information it may use and what the employee or manager needs to check before acting.
It should include AI literacy, practical use cases, prompting, verification, responsible-use rules, function-specific exercises, and manager routines for adoption after the workshop.
Yes. The programme is designed for business teams and managers who need to use AI in everyday work without becoming technical specialists.
Yes. Examples can come from the participants’ function, including HR, finance, sales, operations, marketing, education or government services.
