Artificial intelligence in banking: changing the rules of the game
McKinsey’s latest Global Banking Annual Review contains a message that every banking leader should sit with for a moment: The industry is performing exceptionally well — and yet the future looks increasingly uncomfortable.
Global banking net income reached $1.3 trillion in 2025. Revenues, profits, capital buffers, and shareholder distributions remain strong. On the surface, this is a success story. But the more interesting insight is not that banks are doing well. It is that investors still do not fully believe in the long-term story.
Despite record results, banking continues to trade at weaker valuation multiples than many other industries. That suggests a clear message from the market: profits today are not enough if the business model for tomorrow is uncertain. And that is where the report becomes especially relevant.
The balance sheet is no longer the whole story
For decades, the core logic of banking was simple: collect deposits, lend money, manage risk, and earn spread. That model still matters. But McKinsey points out that the balance sheet is becoming a smaller part of the global financial system. The economics of value creation are shifting: more value is moving toward distribution, transaction banking, wealth management, platforms, and advisory services.
This is a subtle but important shift.
If the balance sheet becomes less central, then customer access becomes more important. And customer access is exactly where banks are becoming vulnerable.
The new competitors are not just fintechs. They are better habits.
The old fintech narrative was too simple: startups would disrupt banks. That did not fully happen. Many fintechs failed. Many were acquired. Many struggled with profitability. But the stronger players survived, matured, and learned how to scale. Neobanks such as Revolut, Nubank, Wise, Robinhood, and others are no longer just “digital challengers.” They are increasingly profitable, trusted, and expanding across product categories.
This is not growth at any cost anymore. It is growth with better unit economics, better technology, and lower marginal cost of serving customers. That should worry incumbents. Because the advantage of many traditional banks was not always love. It was inertia. Customers stayed because switching was inconvenient. But AI may remove that inconvenience.
AI may attack the most profitable thing in banking: customer laziness
One of the most surprising insights in the report is not about chatbots or internal productivity. It is about deposits. Many customers do not actively optimize where their money sits. They keep balances in familiar accounts, often accepting lower returns because moving money is inconvenient. That inertia is valuable to banks.
But artificial intelligence changes the equation in banking. An AI assistant can monitor balances, compare rates, move idle cash, optimize card usage, refinance debt, search for better financial products, and make switching easier. In other words, AI does not only help banks become more efficient. It helps customers become less passive. That may be a much bigger disruption.
There will be no “digital grace period” this time
Banks survived the internet and mobile waves partly because adoption was gradual, especially among older and more profitable customers. AI is different. Adoption is much faster and less limited by age. Customers are already using AI for complex tasks, including financial decisions. Banks cannot assume that high-value customer groups will move slowly again. This time, the customer may learn faster than the institution. That is the real strategic risk. Banks should stop treating speed as the opposite of safety.
Banking culture is built around control, compliance, resilience, and risk management. That is necessary. But it is no longer sufficient. The recommendation from McKinsey is convincing: banks need to become “multi-speed” organizations. Not everything should move at startup speed. Core banking, compliance, and risk systems require discipline.
But experimentation, AI-enabled propositions, ecosystem partnerships, and new customer journeys need a different rhythm. Banks need a model where some parts of the organization protect stability, while others test, learn, and scale much faster.
The mistake would be to apply one speed to everything. Too slow, and the bank becomes irrelevant. Too fast in the wrong areas, and the bank creates unacceptable risk. The future belongs to institutions that can do both.
What banking leaders should do now
Here are five practical recommendations:
- Treat customer ownership as the central strategic issue.
The main battle is not technology itself. It is who owns the customer relationship. - Build AI around customer outcomes, not internal efficiency only.
Cost reduction matters, but the bigger opportunity is helping customers make better financial decisions. - Redesign journeys before competitors or AI agents do it for you.
If your mortgage, savings, credit card, or investment journey is too complex, someone else will simplify it. - Create amulti-speedoperating model.
Separate core resilience from high-speed experimentation. Both are needed. - Measureloyalty. Honestly.
A customer who has not switched is not necessarily loyal. They may simply be inactive — until AI makes switching effortless.
The uncomfortable conclusion
The strongest message from McKinsey’s review is this: banks are not failing. They are profitable, capitalized, and still trusted. The danger is not weakness — it is complacency. And that may be exactly why the risk is so easy to underestimate.
The next wave of competition will not only come from other banks. It will come from artificial intelligence agents, neobanks, stablecoins, embedded finance, and customer expectations shaped outside banking. The winners will not be the institutions that simply add AI to old processes. They will be the ones that redesign banking around a faster, more informed, less passive customer.
The key question for every bank is no longer: “How do we protect our current model?”
It is: “If customers had perfect information, intelligent agents, and zero switching friction, why would they still choose us?”
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