Intelligent Analytics: A Practical Guide
What to keep, what to replace, what to build, with a clear-eyed view of what actually works. A framework for making sensible decisions about your data landscape in the age of AI.
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10 parts. Zero vendor pitches.
The Reality Check
Why the vast majority of AI pilots fail, and the uncomfortable question nobody asks.
Analytical Maturity
The five-level hierarchy, why you can’t skip levels, and why ML should come before LLMs.
The LLM Problem
Hallucinations, drift, and operational risk. What it actually takes to deploy AI safely.
Text-to-SQL Reality
Why “ask in English, get an answer” is brutally hard, and how to make it work anyway.
AI Governance
Proportionate controls, EU AI Act compliance, and governance that enables rather than blocks.
The Waiting Fallacy
Why “let’s wait for better AI” is a strategic error, and the compounding cost of delay.
This guide has been prepared by Smart Associates for general informational purposes only. It does not constitute professional, legal, regulatory, or technical advice, and should not be relied upon as such. Whilst reasonable care has been taken in its preparation, Smart Associates makes no warranty as to the accuracy or completeness of the content, and accepts no liability for any loss arising from reliance upon it. References to regulatory frameworks are for contextual guidance only; independent legal advice should be sought regarding your specific compliance obligations. This guide is the intellectual property of Smart Associates. No part may be reproduced or redistributed without prior written consent.