In many Canadian organizations, AI adoption is moving from experiments to operational pilots. The biggest risk is not choosing the wrong model. It is scaling without a repeatable evaluation routine. Before broad rollout, pick two to three measurable tasks and define acceptance criteria that include accuracy, privacy exposure, and user experience.
For pilots, prefer low-risk internal workflows first: drafting and summarization with human review, structured extraction where outputs can be verified, and retrieval-augmented answers that cite your approved documents. Pause customer-facing automation if you cannot monitor failure cases, capture user feedback, or provide a clear escalation path to a human agent.
Checklist for the week: define who owns model changes, write a short policy for staff usage, create a small test suite of edge cases, and document where sensitive data could be introduced. If you need a tailored version, our services can help.