The Agentic AI Revolution in Banking: Precision or Peril?

How next-generation AI will separate the precision-driven winners from the complacent giants of global banking.

Executive Summary:

Global banking has entered a historic paradox. Despite record-breaking profits in 2024, the industry’s market valuation remains stubbornly low — signalling deep investor scepticism about the sustainability of traditional, scale-driven business models. The next great test for banking lies in the rise of Agentic AI — a form of artificial intelligence capable of autonomous decision-making, collaboration, and self-learning. While it promises a new era of efficiency, it also threatens to dismantle long-standing profit structures built on customer inertia. This article explores how Agentic AI is rewriting the economics of banking, reshaping customer behaviour, and widening the gap between innovators and laggards — and presents a blueprint for survival in this fast-approaching future.

1. The Peak Before the Plateau: Banking’s Moment of Strategic Reckoning

The global banking industry stands at a decisive inflection point. After a decade of reinvention and resilience, 2024 delivered record-breaking financial results — yet investors remain unconvinced. The skepticism is palpable in market valuations that continue to trail far behind other industries.

The paradox is striking. Banks achieved historic highs:

• $1.2 trillion in net income, the largest ever recorded for any sector.
• $5.5 trillion in revenues after risk costs.
• A 20-year high in return on equity (ROE) at 10.3%, finally exceeding the cost of capital.

And yet, despite this stellar performance, banking stocks languish. As of mid-2025, the industry’s price-to-book ratio is 67% lower than the average across other sectors. The market’s verdict is clear: these profits are viewed not as the start of a sustainable upswing, but as a temporary peak — a high plateau before structural challenges set in.

Behind the scepticism lies a growing recognition that the traditional formula for success — scale, spread, and efficiency — is losing relevance. The macroeconomic tailwinds of high interest rates and robust deposit margins are fading, while digital disruption accelerates. To bridge the valuation gap, banks must move from scale-driven strategies to a new model built on surgical precision.

This emerging precision model rests on four interconnected pillars:

1. Technology: A shift from generic digitalization to targeted, Agentic AI-driven productivity and engagement.
2. The Consumer: A move from segment-based marketing to hyper-personalized experiences for a “customer segment of one.”
3. Capital Efficiency: From broad portfolio reallocations to line-by-line optimization that unlocks trapped capital.
4. Strategic M&A: From acquiring scale to acquiring specific capabilities — in data, AI, or niche product innovation.

Among these levers, Agentic AI is the most transformative. It is the fulcrum on which the next era of banking will pivot — capable of delivering exponential efficiency while simultaneously threatening the very foundations of the traditional profit model.

2. The Two Faces of Agentic AI: Engine of Efficiency or Architect of Disruption

Agentic AI introduces a profound duality. On one side, it promises to unlock vast operational efficiencies; on the other, it poses an existential threat to long-standing profit pools. This is the paradox of progress: the same technology that can make banks leaner can also make them irrelevant if deployed defensively or too slowly.

2.1. The Efficiency Dividend: Rewiring the Bank for the Low-Cost Future

Agentic AI will redefine what operational efficiency means. By automating complex workflows, self-monitoring risks, and interacting directly with customers, it will reshape the cost structure of banking. Global studies estimate a potential cost reduction of 15–20% — translating into $700–800 billion in annual savings across the industry.

This transformation will emerge through five core capabilities:

• Agent-First Customer Care: Unified AI agents will handle most customer interactions across mobile, web, and phone, seamlessly escalating complex issues to humans.
• Zero-Touch Operations: AI agents will autonomously process workflows — from onboarding to settlement — with humans supervising exceptions rather than execution.
• Autonomous Financial Crime Detection: Continuous, real-time monitoring and self-escalation of suspicious activities will dramatically reduce fraud response times.
• AI-Driven Risk Management: Automated control testing and dynamic credit assessments will provide real-time precision in managing exposures.
• Agentic Product Factories: Human-AI collaboration in product design and coding will accelerate innovation cycles, with agents writing and testing code autonomously.

However, history suggests that efficiency gains rarely remain confined to their creators. Competitive pressures often pass these savings to consumers. As Agentic AI becomes standard, the operational advantage it creates will quickly erode. Efficiency will become table stakes — essential for survival but insufficient for growth.

The real disruption lies not within the bank, but beyond it — in how customers behave when AI agents begin making their financial choices.

2.2. The Great Unbundling: When AI Dismantles Customer Inertia

For decades, banks have relied on customer inertia — the natural tendency of clients to stay put even when better options exist. Agentic AI threatens to eliminate that inertia completely by empowering customers to optimize their financial lives automatically.

Consider two of the largest profit pools in banking: deposits and credit cards.

• Deposits at Risk: Roughly $23 trillion of the world’s $70 trillion in consumer deposits sits in low or zero-interest checking accounts. An AI agent could, with a single command, move idle funds into higher-yield accounts, automatically tracking rates. If only 5–10% of deposits migrated this way, industry deposit profits could drop by 20% or more.
• Credit Card Margins Under Pressure: AI agents could analyze spending and automate debt consolidation, transferring balances from high-interest credit cards to cheaper personal loans. Even modest adoption — 5–10% of customers — could shrink global credit card profits by 30%.

If unaddressed, these shifts could erase $170 billion in annual profits — approximately 9% of global banking income — and cut average return on tangible equity (ROTE) by up to two percentage points. For banks already hovering near their cost of capital, such erosion could be existential.

3. The Widening Chasm: AI Pioneers vs. Slow Movers

The adoption of Agentic AI will not be even. The coming years will expose a widening gulf between innovators and laggards — between those who use AI to reimagine their business models and those who merely automate existing ones.

In a central scenario — regarded as the most plausible by analysts — the next five years will see banks reduce operating costs by 15–20% while consumer AI adoption triggers a 10% decline in traditional profit pools. The outcomes for banks will differ sharply based on their strategic agility.

• AI Pioneers: These banks could see ROTE rise by up to 4 percentage points, gain market share, and generate capital to reinvest in innovation. They will be positioned to defend their core businesses and explore new revenue models, such as embedded AI-driven advisory services.
• Slow Movers: Those that hesitate may experience ROTE declines of 2–4 points, suffer shrinking relevance, and become acquisition targets for more agile competitors.

This divergence will crystallize within three to five years, when the first viable “agentic business model” proves its success, triggering a cascade of imitation. Once that tipping point arrives, the laggards will find the window to catch up closing rapidly.

4. The New Rules of Engagement: The Rise of the AI-Empowered Consumer

The technological revolution coincides with a deeper behavioral shift. Today’s consumers are less loyal, more digital-native, and more AI-confident than ever before. Banks that rely on brand incumbency are losing ground fast.

Between 2018 and 2025, the proportion of checking-account customers who repurchase from their existing bank without exploring alternatives — the so-called loyalty loop — collapsed from 25% to just 4%. The implications are severe: banks must now fight to be part of a consumer’s Initial Consideration Set (ICS) — the shortlist of brands that come to mind when financial needs arise.

AI and mobile adoption are fueling this change:

• 51% of consumers now use generative AI tools.
• 23% use AI specifically for financial decisions.
• Among recent account openers, 32% used AI to choose their bank.
• Of those, 97% said AI availability would influence their future switching decisions.

In parallel, mobile has become the dominant engagement channel, used by 63% of customers in 2024, up from 41% in 2020. The digital battleground is thus both personal and portable.

For banks, the message is unmistakable: the next generation of customers will be guided by algorithms, not advertising. Winning their loyalty will require not only digital presence but deep, AI-enabled personalization.

5. The Blueprint for Action: Precision as the New Scale

To thrive in the agentic era, banks must abandon piecemeal experimentation and embrace enterprise-level transformation. The winning strategy is not about chasing every technological trend — it is about applying precision to target where AI creates defensible value. Three imperatives stand out.

1. Win Consumer Mind Share — Relentlessly

With loyalty collapsing, visibility is survival. Banks must secure a position in consumers’ Initial Consideration Set through precision marketing, data-driven referrals, and targeted brand-building. This is not about blanket spending but about focused, measurable campaigns that ensure your bank is top of mind when AI agents query “best savings account” or “lowest loan rate.”

2. Make Mobile the Hub of Engagement

Mobile is now the orchestration center of customer relationships. Banks must create seamless journeys across digital and human touchpoints — allowing customers to start a mortgage application on their phone and finalize it in-branch or via video without redundancy. Mobile-first does not mean human-less; it means human-smart.

3. Build AI Into Every Interaction

The best defense against disintermediation is to out-innovate it. Banks must embed proprietary AI directly into customer journeys — offering predictive advice, tailored products, and real-time insights. The goal: treat each client as a segment of one. This strategy echoes the analytics-driven rise of Capital One in the 1990s; today, AI makes that same hyper-personalization scalable across every product line.

6. Conclusion: Precision, Not Heft, Will Define the Future of Banking

The record profits of today may mark not the dawn of a new golden era, but the crest before a major correction. As Agentic AI reshapes the economics of finance, precision — not size — will determine survival.

Banks that harness Agentic AI to reinvent operations, reimagine engagement, and rewire strategy around the empowered consumer will define the next growth curve of global finance. Those that cling to the scale-driven playbook of the past risk being left behind — efficient, perhaps, but irrelevant.

The chasm is opening now. The time to cross it is short.
In the age of Agentic AI, the true measure of success will not be how big a bank is — but how intelligently it acts.