By 2030, AI-native products could account for as much as 25% of institutional banking revenues among the top 50 U.S. banks, according to an analysis by the Deloitte Center for Financial Services, potentially generating revenues between $53 billion and $79 billion. Banks are approaching an inflection point as AI shifts from internal productivity tools into the core architecture of client-facing products, moving from efficiency gains to top-line growth. These offerings are likely to include treasury-orchestration platforms, intelligent payment-routing engines, trade-documentation agents, and continuous credit-monitoring tools. In AI-native products, AI becomes the operating engine rather than an enhancement layer; for example, a treasury platform run by autonomous agents that continuously optimizes liquidity is potentially an entirely new stand-alone product. Such products are already emerging, as seen with buy-now, pay-later loans where credit decisions are made instantly through automated underwriting without human involvement. The strongest case for AI-native products is where decisions are frequent, data is abundant, and actions require judgment and adaptation within regulatory and risk boundaries, with treasury and payments among the earliest areas to see scaling.