Artificial intelligence (AI) intersects with finance in three practical domains: analytics, controls, and experience.

Analytics. Models can sift market structure data, order flow, and sentiment streams to surface anomalies or regimes. The value is in decision support, not automation for its own sake. Transparent inputs and clear caveats matter.

Controls. Supervised models can help detect unusual flows or permission requests, adding a layer of defense beyond static rules. Human review remains essential to prevent false positives from interrupting normal activity.

Experience. AI‑assisted interfaces—search, auto‑explanations of tx errors, or guided troubleshooting—reduce friction for newcomers without dumbing down expert workflows.

For projects exploring AI, responsible adoption means documented data sources, user consent where applicable, and the ability to opt out. Done well, AI augments judgment; done poorly, it obscures it.