Service Overview
AI Readiness and Use-Case Mapping
A practical guide to preparing your business for Artificial Intelligence, focusing on structure over hype.
Preparation before integration
Successful AI adoption starts with understanding the problem, not the technology. We help businesses assess if their data and processes are ready for AI implementation.
Our Assessment Process
- Business problem definition: Identifying exactly what inefficiency AI is meant to solve.
- Use-case prioritisation: Ranking opportunities by feasibility and impact.
- Data quality review: Assessing if internal data is structured enough to feed models (like RAG for internal knowledge).
- Access permissions & Privacy considerations: Mapping out what data is safe to expose to internal or external models.
- Pilot planning: Designing small, controlled tests before wide rollout.
Critical Considerations
Before starting any AI initiative, organisations must plan for the following:
- Sensitive information handling: Ensuring PII is not inadvertently fed into public models.
- Hallucination risks: Understanding that generative AI can confidently produce incorrect information.
- Output quality checks: Establishing processes to verify AI-generated insights.
Crucial Requirement: AI outputs require human review. Models are assistants, not autonomous decision-makers.
Disclaimer: stratosecho provides strategic planning and operational advisory services. We do not provide legal, security, or compliance certification regarding AI implementations.