Identify the assistant’s role and scope
Begin by clearly defining the specific tasks your AI assistant will perform within your business. Common roles include answering questions from approved information, qualifying enquiries, routing requests, or preparing summaries for staff. Understanding this scope helps determine which staff members need access and what level of interaction they require with the assistant.
Consider what the assistant can say or do, when it should ask questions, and when it should hand over to a human. This clarity is essential to establish sensible limits and avoid confusion or misuse.
Map staff roles to access needs
List the different staff roles that will interact with the AI assistant and assess their information needs and permissions. For example, customer service staff might need to review summaries, while managers may require access to performance reports. Ensure that sensitive functions, such as payments or consequential decisions, have stricter controls and approvals.
Evaluate existing software and data systems your team uses to understand how the AI assistant will integrate and what permissions it requires. This helps prevent duplicate records and ensures smooth workflows.
Establish clear access controls and escalation paths
Design access controls based on the principle of least privilege—staff should have only the access necessary to perform their tasks. Define who can approve changes to the assistant’s behaviour or data sources, and set up visible paths for staff to escalate issues or hand over interactions to a human when needed.
Plan for handling failures such as integration errors or missing information. Staff should know how to respond and whom to contact, ensuring business continuity and maintaining trust in the assistant.
Plan training and ongoing support
Provide training that focuses on real tasks staff perform with the AI assistant. This includes giving effective instructions, checking outputs, protecting sensitive information, and recognising when the assistant is outside its scope. Practical training helps build confidence and reduces errors.
Develop simple guidance documents and escalation procedures so that AI use does not depend on a single person’s enthusiasm. Regularly review performance metrics like successful completions, corrections, and staff feedback to identify improvement areas.