Patterns, risk profiles, and practical examples to identify and prototype safe AI-driven decision automation with human oversight.
A practical, reusable gallery for capturing, evaluating, and turning trend watches and research questions in analytics & AI into short experiments and funded pilots. Each entry follows a clear template (background, why it matters, testable experiments, success criteria, owners) and a lightweight prioritization workflow to avoid chasing fads.
A practical, repeatable framework teams can use to identify, evaluate, and prototype AI agent automation opportunities while preserving human oversight, traceability, and measurable outcomes. Includes mapping templates, risk profiles, monitoring metrics, a prototype checklist, and a sample small pilot plan for an insight-generation agent.
A practical, structured research-brief template to capture LLM-powered analytics opportunities with clear decision context, data and privacy considerations, architecture options and guardrails, measurable evaluation metrics, human-in-the-loop plans, pilot success criteria, and rollout considerations. Includes example prompts and a short worked example to help move from curiosity to a testable pilot.
A practical, reusable template and starter bank for capturing, evaluating, and prioritizing trend watches, research questions, experiment ideas, and near-term AI & analytics opportunities. Includes a clear brief structure, evaluation rubric, sample entries, and suggested first experiments so teams can move from curiosity to testable evidence.