Could Gen AI Actually Lead To More Bank Jobs? – Forbes

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The question I get all the time is will generative AI lead to a vast reduction of bank jobs. It’s easy for bankers to be nervous. Recent Bloomberg Intelligence research estimates that Wall Street banks will eliminate up to 200,000 jobs over the next three to five years due to AI. Meanwhile, a Citigroup report published last year said that more than half (54%) of bank jobs will be displaced. Our own research shows that 67% of working hours in the industry could be transformed by the technology.

But what if, instead, gen AI will do just the opposite and actually lead to more banking jobs. We’ve seen this movie before. In the 1980s, it was spreadsheets that were going to eliminate every finance job. Then in the early 2000s, it was digital that was going to replace every bank teller. Neither happened.

I’ve never met a bank CEO, board or executive team that has told me we have all the people we need to get all the work we have done. So what if gen AI, instead of being a pure productivity play, allows banks to take waste out, while putting value in.

In that case, the nature of the work will change.

We are already seeing this play out in the financial services world. For example, in commercial insurance, underwriters get thousands of RFPs, but they are limited in how many they can review because it requires poring over contracts. Some insurers are already using gen AI to help scan through documents, allowing them to review more applications, underwrite more policies and drive more value. For example, QBE Insurance Group, a multinational insurance company headquartered in Sydney, can now process 100% of the submissions they receive from brokers with gen AI solutions replicated across multiple lines of business.

This is a perfect example of taking waste out of the system. Instead of using precious high value underwriting time to look at documents, underwriters can spend more time generating revenue. Arguably, because you’ve taken waste out and you can now respond to more applications, you actually need more underwriters, not less.

We are seeing this scenario play out in commercial banking, wealth management, mortgages, call centers and more. And it’s just beginning.

So if the greater impact of gen AI is actually changing the nature of work versus eliminating it, how should banks think differently about their talent pool. Here are a few things I’ve noticed in my travels and conversations with banks recently:

1. Winning in gen AI is no longer about having an army of PhDs in AI. It’s about having the equivalent of a high school diploma or undergraduate degree in AI. Banks should enlist and enable all their employees to understand how to leverage the tech. It should be no different than a tool like Excel, where everyone has access and it’s enabled for the masses.
2. Banks have to make the right investments in their people. With almost three quarters of the work in banking likely to change, banks can’t hire their way into the answer. There are parallels here to the late 1970s and early 80s when few people had computer science degrees. To bridge the gap, some corporations actually trained their own talent to become tech programmers. IBM developed the Intellectual Programmers Aptitude Test where they figured out which employees had the aptitude to learn programming and then they taught staff how to do it. The same approach could be applied to gen AI.
3. A culture of curiosity tempered with strong execution is critical. Culture may be the ultimate differentiator as banks look to adopt AI. Banks need to develop a culture that embraces collaboration, innovation and continuous learning and pair this with execution – driving adoption of AI beyond proofs of concept to scale it for value. I’d argue it’s just as important to have this culture of curiosity as it to deploy the technology itself.
4. Crawl, walk, run. Banks don’t have to blow up their whole business model overnight to embrace AI and adopting it fully will take time. But they do have to get started, applying the technology where they can internally at first, focusing on high-value use cases and working closely with risk and compliance teams to ensure they aren’t running afoul of regulations. From there, banks can expand further before scaling gen AI across the organization.

Accenture’s recent Pulse of Change research, which surveyed c-suite leaders and non c-suite level employees from the world’s largest organizations in November and December, found that two-thirds (66%) of bank employees surveyed already use gen AI-based tools at work and slightly fewer (60%) feel their workforce has the foundational training needed to use gen AI effectively. Interestingly, when bank executives were asked the same question, 90% thought their employees had the foundational training needed, which suggests that banks could do more to get employees up to speed on AI.

What will ultimately separate the winners and losers is how they approach gen AI. Do they see the technology purely as a cost-takeout play or do they use it to go after revenue? Some of the best banks in the world have told me they don’t care about using AI to tackle cost. They recognize that its real power lies in its ability to help banks and its talent do more.