Who does the prioritizing?
In business intelligence, the reader does. A dashboard shows every metric; the person scanning it decides what matters. In decision intelligence, the platform does: it reads across sources, ranks what changed by relevance to the reader’s role, and presents a short list. The reader decides what to do about it.
What is the output?
BI outputs charts, tables and dashboards: representations of data. Decision intelligence outputs priorities: what changed, why it matters, what to do next, with the sources cited. A chart is something to interpret. A priority is something to act on or dismiss.
How is AI used?
Analytics tools have added AI assistants that answer questions about the data you are looking at. That is useful and reactive: it answers what you asked. Decision intelligence uses AI proactively, to watch, find, explain and draft, and pairs it with established statistical analysis for the measurement, so the recommendation is grounded in tested numbers rather than a language model’s summary.
When is each the right tool?
Use BI when the question is recurring and the reader knows what to look for: weekly sales by region, wave-over-wave tracker tables. Use decision intelligence when the question is “what should I pay attention to,” when signals are spread across many sources, and when the audience is business leaders who will not scan dashboards. Most organizations need both, with decision intelligence on top.
The one-line version
BI tells you what happened. AI helps you explore it. Decision intelligence tells you what deserves your attention.