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Virtually all banks have put a high priority on customer-facing AI, but fewer than a third of them are realizing significant returns. 1The gap isn’t in the technology—adding technology is a faster way to being average. What’s needed is an effective decision layer, one that continually learns through experimentation and tests, learns, adapts and compounds that knowledge over every decision cycle. The result is faster, more precise and more confident actions.
Agentic AI automates known workflows and accelerates execution. One of its principal risks is that it can automate a stale strategy perfectly. Decision intelligence, on the other hand, governs high-value decisions under uncertainty. It discovers the right strategy through experimentation that is continuously improved based on what actually happens after a decision is executed.
The evidence speaks for itself. Decision intelligence has been shown to lift response rates by 300%, funded balances by 250%, digital engagement by 70% and adoption of demand deposits, principally checking, by 90% (see chart).
What Decision Intelligence Delivers
increase in acquisition response rates
higher funded balances at 3 months
increase in digital engagement
increase in demand deposit account adoption
While agentic AI can generate a plausible next-best-action for a customer based on what similar customers have done, decision intelligence can discover findings that no amount of pattern matching against historical data would surface. That’s because the combination was never tried before. Agentic AI reasons from precedent whereas decision intelligence learns from experimentation. It’s the most effective path from insight to impact.
1Oliver Wyman Research
