The first mainstream action users take with new AI agents is commanding them to find and cancel all unwanted subscriptions. This simple use case directly attacks the "breakage" revenue model—where companies profit from users forgetting to cancel—signaling a fundamental shift in consumer power that could vaporize a key internet business strategy.

An Apollo economist warns that AI agents could trigger bank runs by overcoming human inertia. They will automatically sweep trillions in idle cash from low-yield accounts to high-yield alternatives simultaneously. This mass, high-velocity withdrawal could destabilize banks reliant on cheap, static deposits.

An economist's warning of an agent-driven bank run highlights a systemic risk: many industries rely on consumer inertia and complexity for profit. AI agents that automatically optimize choices for users—like moving cash to high-yield accounts—could destabilize these established economic models by removing this profitable friction at scale.

The ARR/SaaS model, built on predictable human usage, is failing. AI agents can consume resources worth thousands of dollars for a low subscription fee, breaking the unit economics. This forces a shift to metered, consumption-based pricing similar to utilities like electricity.

AI agents will attack corporate profit centers that rely on consumer inertia. They will automatically utilize unused flight credits, reclaim loyalty points, and dispute insurance claims. This shifts value back to the consumer and turns previously profitable friction into costly operational burdens for incumbent companies.

Apollo's chief economist notes that AI agents capable of moving money will automatically sweep idle cash into 3% to 5% yielding accounts instead of the 0.1% national average. Because banks rely on human inertia and keep tiny reserves while lending out deposits, automated optimization across millions of accounts could trigger rapid, agentic bank runs that expose traditional banking systems.

AI agents can automate tedious tasks like canceling subscriptions, finding refunds, and disputing charges. This directly threatens businesses whose models rely on customer inertia and friction—a market estimated to cost consumers $165 billion annually in lost time and money.

While AI currently gives Nubank an edge, its long-term effect could commoditize the entire banking industry. AI agents could constantly optimize consumers' finances, automatically switching them to the lowest-rate products and eroding industry-wide margins.

Businesses with moats based on network effects or consumer friction are vulnerable to "agentic commerce." AI agents, tasked with finding the absolute best price without experiencing the tedium of comparison shopping, will bypass brand loyalty and platform stickiness. This threatens any business model that relies on being the default or convenient choice.