How can financial institutions get more value from using AI?
- Financial institution leaders are increasingly looking to more advanced AI tools to help tackle complex problems like overseeing transactions and maintaining regulatory and policy compliance.
- However, an AI tool is only as effective as your implementation strategy, which should include key pillars like governance and security, education and training, a solid data foundation and targeting your AI efforts on solving specific business problems rather than just chasing the latest tech.
- To increase your odds of success, lean on an advisory firm to help you design and implement your AI strategy, and also establish an AI monitoring process that will allow you to track your efforts and outcomes to determine what’s working and whether you need to adjust your approach.
How can financial institutions more effectively leverage AI to drive growth? It’s a question that many C-suites are asking, with most of the 345 banking leaders and credit union executives surveyed by Wipfli stating that making better use of AI and advanced analytics represents a top strategic priority in 2026.
Increasingly, institutions will need to answer that question in order to keep up with competitors and navigate today’s challenges. Keep reading to learn more about the key problems financial institutions are turning to AI to solve, plus how to implement an effective AI strategy.
What key challenges are financial institutions turning to AI to solve?
Many financial institutions have already experimented with AI in the form of technology code generation or for customer service, with some institutions even investigating more advanced tools like agents or agentic AI. But there are other consequential applications to consider.
Financial institutions need to ensure that decisions around transactions and investments are financially sound, compliant with regulations and in line with the institution’s own policies and procedures. For decades, even centuries, these guardrails were maintained entirely by human beings. However, as even mid-sized institutions experience a higher volume of transactions than ever before, the torrent of information has grown beyond the ability of any human team to keep up with.
As a result, financial institution leaders are increasingly exploring how AI and related advanced analytics tools can help them manage and analyze data around transactions, operational efficiency, investing and wealth management. Whether these efforts succeed, though, can depend heavily on not just leveraging new tech, but how you implement it.
Growing internal AI use is also highlighting a policy gap
Even within financial institutions that have not implemented an organization-wide AI effort or strategy, many individual team members are turning to AI tech within the scope of their own job roles. Team members may be turning to AI assistants to take on routine tasks like summarizing documents or transcribing meetings.
But this has highlighted a problem: organizations may have high individual AI usage but no guiding policy to inform whether and how team members can safely use AI with regard to data privacy and other compliance and security issues.
At the C-suite level, executives need to understand that regardless of their current AI strategy, they need to establish clear AI policies for their teams to follow, or risk significant data security trouble. Assume your employees are using AI and decide how to properly direct that usage.
How should financial institutions implement a more effective AI strategy?
To drive results, you need to implement an effective AI strategy rather than simply adopting new technologies piecemeal. For financial institutions, a good strategy typically includes AI governance, security, education, training, choosing tools to solve specific business problems and creating a data foundation that’s useful to AI and advanced analytics tools. You’ll also likely benefit from leaning on support from an advisory firm that can help you work through the process of developing and implementing your AI strategy.
Here are five essential financial institution AI strategy prongs in more detail:
1. AI governance, security and policies
Governance is essentially the foundation upon which your AI effort is built. You need to develop a governance structure and foundational policies to guide how your organization adds new AI tools and what safety protocols you’ll put in place to manage risk and help ensure compliance.
Your governance structure should include an AI leader at the C-suite level, as well as policies around technology adoption, information security, organizational use and risk management.
2. Education and training
The market is flooded with AI tools. But which ones are fluff or hype — and which could actually help your institution? To help your team decide, you’ll want to learn more about the different options and understand what new AI models are actually capable of.
As you begin to implement new tools, you’ll also need to train your team to use them properly. Without effective training, you’ll get variable results at best, if not an outright failure of your AI efforts.
3. Focused tech decisions
Another key to AI success is carefully selecting your tools to focus on solving specific problems within your financial institution. Don’t just buy everyone on your team a ChatGPT Pro subscription, but rather identify particular challenges around transaction oversight, regulatory soundness or policy compliance that AI could help you address and then choose AI options that can help in those areas.
4. An AI-ready data foundation
Finally, without an AI-ready data foundation in place, your financial institution will struggle to generate results from even the shiniest AI tech. You need to structure your data for analysis so the AI can read it and use that information to generate insights while protecting sensitive information.
At this point, you can safely access these insights not just through dashboards but also via conversational AI agents that can answer questions and help your team members prioritize where to focus their attention.
5. Lean on advisory support
To develop and implement your AI strategy more quickly and effectively, harness advisory support. Your advisor can help you identify areas inside your financial institution where you’ll most benefit from AI solutions, provide education and training, and help you craft your overall strategy or implementation plan.
Look for an advisory firm that knows not just AI, but also the nuances of the financial services sector, as many technology advisors may not understand the complications that come from working in a regulated industry.
What are the benefits of smarter AI usage by financial institutions?
Effective AI usage offers financial institutions three major benefits: consistency, quality and productive output. CEOs and other financial institution executives should think about assessing AI ROI from the perspective of these benefits.
For example, consider the process of writing loan officer memos. These remain the largest source of regulatory write-ups in the financial services industry, in part because the process is so time-consuming that loan officers may choose to ignore necessary paperwork in favor of pursuing new business.
An AI assistant can help automate large chunks of the officer memo-writing process. Essentially, this can allow you to achieve a more consistent and timely output while maintaining quality and ultimately boosting your overall new loan volume by allowing your loan officers to devote more time to origination without risking regulatory problems.
AI monitoring helps you determine whether your strategy is paying off
C-suite executives trying to determine whether an AI investment is paying off should rely on an effective AI monitoring process. To do this, you need to know the answers to three major questions:
- Who are you giving AI tools to?
- What are you expecting them to do with them?
- Is that effort delivering a satisfactory outcome?
Being able to track and measure outcomes can help you determine whether your current AI strategy is delivering or if you need to make adjustments. Here, lean on your advisor to help you set up a monitoring process that fits your specific business needs.
Learn more about how financial institutions are adapting to meet the challenges of today
Financial institutions face a host of challenges around growth, technology adoption, risk and more. How are leaders adapting to help their institutions thrive? Wipfli surveyed 345 banking and credit union executives to find out:
Read the 2026 banking industry report
Read the 2026 credit union industry report
How Wipfli can help
We advise financial institutions on implementing new technology, managing risk and growth. Let’s talk about your goals and how new AI tools can help you achieve them. Start a conversation.
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