The banking sector has spent the past decade experimenting with automation, machine learning, and chatbots. But Agentic AI, a new technological shift, is reshaping the conversation entirely. Unlike standard AI tools that simply respond to prompts or classify information, agentic AI refers to autonomous digital agents capable of making decisions, executing tasks, and acting independently. It’s not just another tool; it’s a new kind of workforce.
In both the United Arab Emirates and the United States, two financial ecosystems known for aggressive digital transformation, the arrival of agentic AI signals a disruptive inflection point. The question is not whether banks will adopt it, but whether they are truly prepared for it and the underlying consequences attached to it.
The evolution of AI in banking and financial sector – from predictive analysis to autonomous decision makers
The difference between the traditional AI models and the agentic AI is significant. Traditional AI models assist humans, whereas Agentic AI can replace entire workflows. 
In finance, autonomous agents can do beyond just extracting reports or analysing gaps; they can manage customer queries, execute trades, perform risk scoring, monitor fraud, process loan applications, or run compliance checks end-to-end without any human intervention. They don’t wait for instructions; they act based on goals, constraints, and real-time data.
This creates unprecedented speed and scale. In markets like the UAE, where institutions are racing to become global leaders in financial innovation, and in the U.S., where fintech competition is fierce, the technology promises efficiency levels humans simply cannot match.
But with autonomy comes a new problem: control.
Why are banks not ready for a full-scale agentic AI deployment?
Despite their technological ambitions, most banks in the GCC and the U.S. alike are structured around legacy models, legacy hierarchies, and legacy technology. Agentic AI challenges all three.
1. Legacy infrastructure slows everything down
Many banks still operate on decades-old software that wasn’t designed for autonomous decision-making systems. Integrating agentic AI into these environments is like plugging a self-driving system into a 1980s engine.
In a recent survey, 46% of U.S. banking executives said “integration with legacy systems” is a top concern for adopting agentic AI.
In 2024, 10x Banking released a research report stating the facts: For 55% of banks, outdated core systems remain the single biggest barrier to digital transformation.
2. Compliance models assume human oversight
Regulators in both the U.S. and the GCC are still determining how to classify actions made by autonomous agents. Who is liable for an AI-driven loan denial, mispriced trade, or false AML alert? Until governance frameworks mature, banks risk regulatory exposure.
In a recent EY-Parthenon 2025 survey of retail and commercial banks, 67% cited data privacy and security concerns, and 61% said lack of trust in AI decision-making is a barrier.
3. Cultural readiness is lagging behind technological readiness
Leadership teams often misunderstand AI’s capabilities. They view it as “automation software,” not a semi-independent actor that can transform the structure of entire departments.
4. Workforce displacement fears remain unresolved.
Agentic AI doesn’t assist employees, it competes with them. That introduces social, ethical, and economic tensions that banks have yet to address independently and transparently.
According to the PwC Global Workforce Hopes & Fears Survey 2024, 62% of banking employees globally fear that AI (including agentic AI) will replace their roles within five years.
Gallop Workplace and AI Sentiment Index highlights that in the U.S., 48% of financial services workers say AI will make their current role obsolete.
Oliver Wyman Middle East Workforce Sentiment Report 2024 highlighted numbers exclusively for the GCC, 52% of UAE employees fear displacement due to autonomous AI systems and digital agents.
The GCC advantage and the U.S. pressure
The UAE, Saudi Arabia, and Qatar are pushing national AI visions backed by state-level investment, regulatory sandboxing, and aggressive digitization targets. This gives GCC banks an agility advantage: fewer legacy systems, faster regulatory adaptation, and leadership willing to rethink institutional design.
In contrast, the U.S. banking sector—though technologically advanced—faces heavier regulatory constraints, shareholder pressure, and entrenched workflows. The result: powerful innovation, slower adoption.
An inside look on the GCC and the US banks deploying agentic AI
- Emirates NBD / Liv.
Emirates NBD’s digital-only bank launched Liv, a fully operational autonomous AI agent with a ‘zero-human-touch’ model for underwriting. The AI ingests bureau scores, salary flows, and behavioral data and then autonomously approves or declines personal loans.
1. Mashreq Bank
Mashreq has adopted an agentic AI solution for customer onboarding and e-KYC, where AI pre-fills manual fields from client documents to reduce turnaround time.
2. JPMorgan Chase (USA)
JPMorgan is listed as one of the banks transitioning to “DX 2.0” with AI-native models, using agentic AI in back-office workflows
3. HDFC Bank (India, for global context)
While not GCC or U.S., this is a real-world bank deploying agentic agents for onboarding, compliance tasks, and cybersecurity operations.
4. BNY Mellon (USA)
According to reporting, BNY Mellon has rolled out AI-powered agents as “digital workers” with their own logins to perform tasks such as validating payment instructions.
The future is autonomous and uncomfortable
Agentic AI is on track to become the silent backbone of tomorrow’s financial systems — an invisible workforce executing decisions, processing transactions, and managing critical operations at speeds no human team can match. It won’t wait for instructions. It won’t ask permission. It will simply deliver—faster, cheaper, and with a level of precision that transforms the economics of banking.
But this transformation comes with weight. Even in early pilot stages, agentic AI introduces entirely new risk surfaces across security, compliance, and governance. These systems don’t just automate tasks; they make decisions. And without robust guardrails — human-in-the-loop oversight, transparent audit trails, and enforceable safety boundaries — autonomous agents can act in ways that are difficult to trace, predict, or control.
Banks are attracted to the promise of hands-off automation, lower costs, and near-instant decision cycles. And the pressure to adopt is rising quickly across both the GCC and U.S. markets. But the risks are just as strong. Until accountability frameworks mature, regulatory expectations become clearer, and governance structures evolve to match the autonomy of these systems, full-scale agentic AI deployment remains as dangerous as it is promising.
