Start with the legal task, classify confidentiality risk, choose the right category of tool, prepare documents, test on a limited matter, verify outputs and adopt a policy before wider deployment.
Prepare a legal matter for supervised AI use by defining the task, classifying confidentiality risk, indexing documents, setting jurisdiction parameters and planning verification before conclusions are requested.
An organisational briefing on the legal, governance and operational risks of AI, including accountability, oversight, privacy, confidentiality, accuracy, bias, procurement and acceptable-use policies.
Plain-English explanation of deployment labels and their practical consequences for confidentiality, cost, control and support.
How to define permitted tools, information classes, supervision duties, verification requirements, record-keeping and escalation routes.
Questions to ask about source coverage, data retention, model training, security, audit logs, export, support and contractual terms.
A focused programme on how AI systems interact with personal data protection, including employee and customer data, automated processing, third-party platforms and organisational safeguards.
A practical framework for governing AI systems within an organisation, including responsibility structures, risk classification, vendor assessment, documentation, monitoring and incident management.