AI decision support is AI that helps a person make a specific call, while the person keeps the final say and the responsibility for the outcome. That makes it different from automation. The AI gathers evidence, frames the options and makes a recommendation; you decide whether to trust it or override it.
Dashboards describe what already happened. Decision support has to help with what to do next, and a confident wrong answer is worse than none.
The articles here look at specific settings: software teams setting sprint priorities with data scattered across Jira, GitHub and Confluence; clinicians deciding when to trust a model and when to override it; executives working from fragmented evidence. Others cover practical AI tools for decision-making and what decision management tools need to do under uncertainty. Start with AI decision support systems for business intelligence, which picks up where dashboards stop.
Suprmind’s 5-model AI boardroom gives you five frontier models that see and build on each other’s answers, so you weigh their agreement and their objections, not one opinion. You still make the call, with the objections already on the table.
