There was a time when large-scale disasters or disruptions like a hurricane or a high-profile security incident were relatively few and far between.
When they did come up, large companies across industries – from communications to manufacturing – would respond by establishing temporary “war rooms” to deal with the potential fallout and plot their next moves. Today, however, these types of once-rare incidents – now often tied to tech glitches or outages – are happening with far greater frequency, and those war rooms are dedicated spaces.
Banks can certainly relate to this trajectory, as they too have seen a dramatic rise in the number of risks and threats facing their industry. From unexpected rate spikes to shifting GDP forecasts to natural disasters, the heightened possibility of an event that could significantly impact their workflow, stability, or future growth demands the ability to respond quickly and decisively.
That, in turn, makes agility one of banks’ best potential strategic weapons. And one of the most effective ways to become more agile is by harnessing the power of tools and processes powered by generative artificial intelligence (gen AI).
A recent IBM study found that only 8% of banks were developing gen AI systematically in 2024, but that number was expected to soar in 2025.
Why? Because agility stands as a differentiator in banking – one that could prove to be the key difference between those institutions that pull ahead and those that fall behind.
Understand the opportunities for gen AI in banking
Gen AI can help foster agility for banks by allowing them to better respond to dynamic changes in the marketplace. And its impact can be widespread throughout a bank, automating areas such as…
Workflow and task management to allow the institution to respond quickly to market-induced surges, such as a drop in interest rates that results in a sudden uptick in mortgage or auto loan demand.
Customer service to handle the inevitable spike in volume that might result from a natural disaster or other unusual event.
Risk and fraud monitoring to respond more quickly to the ever-evolving threat landscape.
But gen AI’s greatest potential impact in any bank is likely in the software development and delivery process. Banks looking to be more agile will find that gen AI can help speed up everything from code analysis to product design to backlog management, giving them the agility to quickly launch and roll out new features and applications. And that adds up to a significant competitive advantage.
Know what it takes to be an agile bank
But if agility is such a winning trait of gen AI, why isn’t every bank already building gen AI into its processes? The answer is that not all banks realize that agility in 2025 depends on this technology.
And the truth is that not every bank is ready to fully embrace gen AI. Some may try to tack AI onto their existing systems or ideas. That, however, is not really a path to agility. A truly agile bank will be focused on three things:
- An AI-first or AI-forward culture: Gen AI should be so ingrained in the DNA of the bank that any new project will automatically have it as a foundation. It’s not a question of “how do we add AI to this or that process?” Gen AI should be the starting point, not an afterthought.
- A commitment to change management: Gen AI implementation is about more than just rolling out new tools. It demands a fundamental shift in how the bank approaches problems. To that end, it’s important to have a solid understanding of how gen AI will impact different roles and functions going forward – and how the bank is going to communicate that to staff.
- The right infrastructure to support gen AI: Like any other technology in the bank, gen AI requires scrutiny around issues such as data security and governance. Beyond that, there should also be built-in logic and understanding throughout the organization of how gen AI fits into what the bank is trying to do.
These are the table stakes for gen AI. Without them, it is unlikely a bank will be able to successfully use the technology to become more agile.
Find the right pace
Even with the right mindset and culture in place, agility isn’t the type of shift that generally happens overnight. Not every bank can go all-in with gen AI right away. Instead, it’s important to try and find a pace of change that matches both the bank’s technological maturity and financial resources.
Figuring into this conversation should also be the understanding that gen AI requires a combination of both top-down and bottom-up transformation. Gen AI is difficult to force on people – especially staff who may be concerned about their jobs being replaced. This is where training and education can help ease fears about how roles will be impacted or changed.
Getting these things right is worth the time and effort they require. It’s about finding what works. After all, not every bank has to work toward agility with the same speed, but every bank probably needs to start working toward it.
Make agility your differentiator
As the pace of change in the industry has risen exponentially, many banks have started to discover that a measured, slower way of doing things won’t work any longer. Success these days demands the ability to not only react quickly and decisively to the shifting competitive tides, but also to proactively get out in front of the next big disruption.
That’s agility, which can be a true differentiator for banks in a mostly commoditized industry. But getting there requires a willingness and an ability to do things differently, using the power of gen AI to modernize the development process and stay on the cutting edge of what comes next.
Young Pham is Chief Strategy Officer at CI&T.
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