AI and the banking workforce: Which jobs are safe, and which aren’t?

Until the mid-1980s, bank messengers were a fixture at every bank. Ferrying checks between departments was an important role — one with a 100-year history. But everything changes, and following the advent of magnetic ink character recognition in the late 1950s, automated clearinghouses in the 1970s and check imaging in the 1980s, the role eventually became obsolete.

This isn’t an unusual story. As technology advances, some roles evolve and others disappear altogether. It’s a pattern seen across industries, but nowhere more clearly than in banking, where innovation has a long history of reshaping workforces.

According to an IBM report, half of banking and financial markets CEOs are hiring for roles that didn’t exist a year before, clearly indicating how quickly AI is reshaping the financial workforce.

While every technological innovation has changed how people in banks work, this one is moving more quickly than most. So, what can we expect from the latest shift?

Which banking jobs are most at risk of going obsolete?

AI agents can now reason, plan and act on their own. They are completing tasks faster, more accurately and at far less cost than people can. This makes AI perfectly suited to rule-based, repetitive work — the kind that once filled entire job descriptions.

The first roles to feel the effects will therefore be those that are defined by rules and repetition. For example, compliance analysts could be phased out as AI models excel at learning regulations and spotting outliers in patterns. The same goes for junior analysts, as gathering data, completing research and producing documentation are AI’s bread and butter.

Looking at different departments in the banking industry, we can identify the various roles that AI models can be programmed to perform. As AI-enabled automation expands, roles where rule-based tasks account for a large share of the expected output are the most likely to be rethought or reduced.

Which roles is AI reshaping in banking?

From retail branches to risk operations, AI is gaining a foothold in every corner of the banking industry.

Looking at different departments, we can identify the roles that an AI model can be programmed to complete.

Retail banking

• Tier 1 customer support: AI bots can triage initial enquiries and handle many common questions and tasks.
• Branch Teller: Physical branches are on the decline as customers opt for the convenience of digital banking.
• Account Opening Officer: This process can be automated easily with digital onboarding and electronic “Know Your Customer”.

Lending and credit

• Loan Underwriter (retail or small and medium-sized enterprises): Creditworthiness relies on data points. AI can pull the data together and make the call.
• Loan Application Processor: Loan applications are already being taken into the online world. With AI document validation, there’s not much need for human input.
• Collections Agent (Tier 1): The repetitive process of repayment reminders can easily be automated while maintaining personalization at scale.

Risk and compliance

• “Know Your Customer” Analyst (initial review): When it comes to checking whether everything is as it should be, AI can lead the way in verifying documents and flagging mismatches.
• Anti-money-laundering Transaction Monitor: The complex capabilities of AI enable it to detect suspicious activity with fewer false positives.
• Regulatory Reporting Analyst: By transforming raw data into ready-to-read reports, AI can ensure and provide proof of compliance.

Wealth and advisory

• Junior Investment Advisor: Robo-advisors will provide portfolio guidance at scale.
• Back-Office Portfolio Analyst: Responsibilities such as stress tests and scenario simulations can be taken care of by AI.

New roles for human employees

According to Gartner®, “By 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention, leading to a 30% reduction in operational costs.”*

But while AI can carry out repetitive tasks and review data faster and more accurately than human employees, human oversight remains crucial for context, empathy and final decision-making. Employees’ roles are evolving from doing the work to directing the systems that do it.

This means some people might find themselves working alongside digital colleagues — for example, in customer service, where agentic AI is already powering highly responsive chatbots.

Empathetic AI is taking contact-center interactions a step further by combining customers’ personal data with sentiment and prosody (speech patterns) analysis to triage customer intent and direct complex complaints to human agents when necessary.

This hybrid approach will extend beyond marketing and compliance into much of the wider workforce, requiring most banking employees to strengthen their AI skills.

Partnering to power the next generation of banking

The rise of AI in banking isn’t just evolving existing jobs; it’s also creating entirely new ones. Banks need AI developers to train, implement and maintain AI technology, data scientists to feed their AI solutions high-quality information to learn from, and governance experts to keep these solutions in line with regulations.

However, the demand for the skills needed to make AI-powered banks a reality is outpacing the supply. In the IBM study, 53% of the CEOs who were interviewed said they were struggling to fill technology roles.

The right strategic partnerships can make all the difference. At NTT DATA, we’re already helping banks navigate AI-powered transformation by bringing together the people, processes and leading-edge technologies to make it a success.

Let us guide your organization through this major transition to a new era of human–AI collaboration.