Find the right use cases, validate value early and design with data protection, quality checks and human oversight from the start.
Start with the workflow and the people who use it. Choose technology only after the problem and success measures are clear.
Map candidate use cases, data readiness, business value and implementation complexity. Build a prioritised roadmap rather than a long wish list.
Design assistants around approved information sources, access permissions and useful answers that can be checked.
Identify repetitive work suitable for automation and keep exception handling and human approvals visible.
Establish practical governance for ownership, evaluation, approved tools, data handling and ongoing review.
Let's discuss the challenge, the options and a practical first step.