A short research playbook using data analysis, process mapping, and stakeholder interviews to surface non-obvious AI use cases.
Find hidden AI opportunities that actually matter. If your team wants breakthroughs instead of incremental ideas, this short research playbook helps you discover non-obvious, testable AI opportunities in a domain without getting lost in speculative brainstorming. What this resource helps you do: run a compact...
Research Project Guide: A practical method to surface non-obvious AI use cases. This guide describes a compact, evidence-first method you can run in 1–3 weeks to discover AI opportunities that matter. It focuses on observable problems, measurable outcomes, and quick validation. The method is deliberately lightweight...
Process Mapping Worksheet — find friction and knowledge gaps. Use this worksheet to document a focused process slice (one end-to-end flow or a single handoff). Keep the map small—4–12 steps. The goal is to expose where decisions, manual work, and hidden knowledge live. How to use. Name the process (e.g., "Customer...
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Opportunity Archetypes — practical examples to spark synthesis. Use these archetypes as lenses when you synthesize interview and process data. They are deliberately practical and cross-sector; each archetype includes brief examples to make them easier to spot in your domain. 1. Structured extraction from unstructured...
A practical, timeboxed playbook to surface non-obvious AI use cases using short stakeholder interviews, a focused process-mapping checklist, light data probes, and a simple scoring template to prioritize candidates.
An interactive, role-aware interview workbook and analysis template: pre-interview consent and checklist, structured question sets, free-text notes, numeric ratings, taggable affinity-mapping fields, post-interview summary, and suggested follow-ups. Saves each interview as structured JSON for comparison, prioritization, and later analysis.
A ready-to-run, guided interview form with differentiated question sets for executives, domain experts, frontline staff, and customers plus structured note capture, an outcome-framing section, and a quick scoring rubric. Submissions are saved for later affinity mapping and use-case hypothesis generation.
Practical, reusable interview scripts for frontline staff, operations, and managers, plus a note-taking layout and a synthesis template that converts interviews into measurable opportunity statements, pilot briefs, and prioritized use cases.
A practical, reusable set of experiment designs, pre-analysis planning guidance, sample-size guidance, randomization and guardrail checklists, and a ready-to-copy A/B experiment template to validate AI pilots and other changes with rigorous evidence.
A practical, step-by-step playbook to design disciplined AI pilots: frame testable hypotheses, define minimal datasets, create an experiment protocol, map success criteria, build a measurement plan, run controlled validation, and use decision gates and handoff checklists to move confidently from pilot to operation.
Interactive experiment protocol and A/B template: hypothesis framing, primary-metric definitions, sample-size guidance, logging & instrumentation checklist, guardrail metrics, analysis plan, and result-interpretation checklist. Saves protocols for reproducibility and handoff.
Interactive assessment to capture stakeholder impacts, readiness, risks, remediation actions, training needs, and communication plans for proposed AI solutions. Save one entry per stakeholder group to build an impact map, readiness scoring, adoption risk register, and targeted remediation & communications plan before scaling.