Businesses have long talked about VUCA – volatility, uncertainty, complexity and ambiguity.
But in recent months, uncertainty has become front and center.
The trade war has prompted wild gyrations in equities markets, rattled the bond market in a way not seen since 2008, inverted yield curves and dampened demand for the Treasury auction.
Talk about the potential for a recession continues. There’s sticky inflation. Interest rates are high, and the Federal Reserve Chair in May indicated that very low rates are not a sure thing.
Global political conflicts can also disrupt markets and make financial planning and risk management harder. And, as if all of that weren’t enough, cryptocurrency’s move into mainstream investing is adding more uncertainty to the mix for the financial services sector.
In this environment, planning has become extremely difficult, which may cause banks and other businesses to adopt a retrenchment mindset. But that could trigger the dangerous mass psychology to turn recession fears into reality, and it won’t move individual businesses forward.
Here is a strategic roadmap to help credit unions and other financial services organizations advance their IT initiatives, move their AI efforts forward and build their businesses in an increasingly uncertain world.
Gain Market Share While Others Pull Back
Some of the “most exciting and generation-defining companies” – such as Facebook, Google, Square and Stripe – were founded during challenging economic times, as WIRED has reported.
Well-established companies – such as JPMorgan Chase – have used difficult environments to their advantage as well. Jamie Dimon’s decisiveness, continued investment and commitment to innovation enabled the financial services firm to emerge stronger from the 2008 financial crisis.
The lesson? When everybody is investing in their businesses, it’s tough to make market gains. But when you are the only one who is building your business, you can pass your competitors.
It’s akin to how Tour de France cyclists take the lead by passing other riders on the uphill climbs. And now, Dimon is poised to break away again. During a recent earnings call, the CEO said that JPMorgan Chase would be investing in AI and IT technology “regardless of the environment.”
Credit unions can take a page from this playbook. As other financial institutions scale back, credit unions that continue to invest in AI, and deliver smarter service to their members can gain share, deepen member loyalty and emerge as community leaders.
Innovate in a Way That Delivers a ROI
Executives at many leading companies have already greenlit AI investments. But because businesses have spent a great deal of money on AI, leaders are now focused on getting value from their AI investments. That’s even more critical in the face of economic uncertainty.
AI has been driven not by IT but by a line of business leaders wanting to embed AI capabilities into their business units. But not every idea is a good idea, and many businesses today are looking at potential AI use cases with a more critical eye to figure out if there’s a ROI. Take the time and effort to do upfront AI discovery and conduct sprints. Engage with a partner that has a defined AI discovery practice and can provide an impartial assessment on your ROI calculations.
That’s especially critical for credit unions, where accountability and member trust are deeply embedded in the mission.
At the start of 2025, Filene Research Institute surveyed 110 credit union leaders across 78 institutions and found that most are still in the early stages of AI adoption, but eager to move forward with use cases like automation, fraud detection and member service efficiency.
If you’re unsure what use cases to start with, consider whether AI can add value by identifying potential black swan events. Spotting deviations early could allow you to reorganize your loan portfolios, advise financial services clients to rebalance their investments and take other steps to limit risk. Also consider applying AI to infuse your know your customer (KYC) process with impartiality. This will free your KYC effort from having to rely on associates who have strong incentives to onboard new clients. KYC done incorrectly can lead to a gamut of unhappy outcomes, including legal liability, regulatory fallout, reputational damage and lost business.
Tame the Data Chaos Before Scaling AI
AI has led to a dramatic increase in the amount of data storage businesses require, and the amount of data is expected to increase 122% by 2026, according to Hitachi Vantara’s recent research.
Yet many financial services and other organizations continue to struggle with fragmented data silos, sprawling data environments and overextended IT teams. That puts enterprise data and businesses at risk. Without the proper data approach, AI may blurt out the wrong answers or include nonpublic personal information in a conversation.
That’s never good, but it is especially problematic amid economic uncertainty, when people are hypersensitive and businesses just can’t afford to make mistakes. Whether you're a credit union or a regional bank, strong data architecture and AI governance are essential. When you lose that trust, your bottom line is going to be impacted.
As your organization continues to innovate with AI, make sure you have the infrastructure and processes in place to unify, control, observe and govern your data. Visibility into the enterprise data you have and the ability to set and enforce data policy will enable you to identify and protect NPI, personally identifiable information (PII) and other data wherever it resides.
Be Selective: Feed AI the Right Data, Not All Data
AI will consume any data you feed it, but that doesn’t mean you need to give AI all your data.
Lower your risk and increase your efficiency and efficacy by employing small language models as opposed to large language models. Explore whether a pre-trained model from an open- source library will work for you. Pre-trained models, which focus on specific use cases, are often good options and allow you to use much smaller data sets of proprietary information.
Credit unions should prioritize smaller, focused models or retrieval-augmented systems rather than blanket adoption of large language models. The same holds true for any financial services provider looking to reduce risk while accelerating innovation. This helps financial services and other firms prevent AI from delivering incorrect answers.
Also, keep in mind that data no longer lives solely in orderly databases. Estimates suggest 80% of enterprise data is unstructured, according to Gartner. Emerging tools enable companies to assess their data and figure out if data sets contain NPI or PII data. Consider employing these tools to organize your data and lower your risk by allowing you to understand what you're feeding into AI engines.
Prepare for AI That Doesn’t Just Advise – It Acts
Since ChatGPT’s debut in late 2022, financial services firms have rushed to implement AI –buying GPUs, cobbling them together with other piece parts and launching chatbots.
But that was just the first step, and it was the easy part.
Financial institutions are increasingly building AI into their business-critical applications and systems and moving from chatbots that make suggestions to agentic AI that acts. The PYMNTS Innovation Readiness Index reports that 57% of credit unions with over $5B in assets have deployed AI chatbots or virtual assistants.
As AI evolves from generating content to driving actions, it’s crucial to ensure you are doing things in a responsible way. That means you’ll need to run a quality service and be ready to explain what AI did after the fact.
That can be challenging since AI is brand new for everyone. But an impartial partner can help you find the way. Seek a partner that simplifies enterprise AI and accelerates business outcomes. Look for a partner that aligns with best practices, is a clear innovator and delivers everything you need to make your AI initiatives a success. That way, you can move from transactional buying of boxes to investing in outcomes. Engage with a partner with a proven history of IT excellence, deep sector-specific experience and operational technology capabilities.
In times of uncertainty, hesitation can feel like the safest move, but it rarely is.
Credit unions and financial services firms that embrace innovation with discipline, invest strategically in AI and maintain rigorous data practices will not only weather volatility but position themselves to lead.
Now is not the time to pull back; it’s the time to lead.
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