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A field guide for buyers. What's working, what's hype, and what to demand from any platform you evaluate.
Most CI teams are evaluating AI tools right now. Some are running pilots. A few have already adopted, and most of those have stories about what didn't work. This guide is for that evaluation: what to demand, what to ignore, how to evaluate, and where the failure modes are.
Frameworks, scorecards, and templates you can take into your next vendor demo.
For the analysts, managers, and leaders inside competitive intelligence, market intelligence, and knowledge management functions. Whether you're already running pilots or just starting to evaluate, the failure modes and demands are the same.
Most "AI for CI" content is written for general business audiences and stops at high-level capability descriptions. This guide is written for the function. It names specific platforms, specific failure modes, and specific tests. It's the buyer's evaluation framework written down.
FAQ
Score it against the conditions a working CI function actually requires, not the features a vendor wants to demo; run a structured five-question pilot on questions your team has already answered; and sequence rollout so expansion is earned through real performance.
They hit predictable failure modes: cross-source contamination and document-level rather than claim-level provenance, which means you cannot trace a claim back to the exact source that supports it.
It is the ability to trace every individual claim in an answer back to its specific source, rather than just citing a document. Without it, a CI analyst cannot verify or defend the intelligence.
A five-question pilot on real questions, a vendor scorecard, a demo checklist, and a 90-day rollout plan, all provided as fillable templates in the guide.