The Best AI Strategies Automate Tasks, Not Relationships
By Troy Coggiola, Chief Product & Strategy Officer at MeridianLink
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For years, the conversation around AI in financial services has focused on efficiency: faster decisions, lower costs, and greater automation. But its greatest impact comes from what it gives back: time. By simplifying complex back-office work, AI helps employees focus less on processes and more on people.
The industry is already moving quickly in that direction. A recent Experian study found that 89% of banking and lending respondents expect AI to play a critical role across the lending lifecycle, 84% rank it as a strategic priority over the next two years, and 51% are already implementing AI solutions.
Key insight: As adoption accelerates, the opportunity is expanding beyond institutions with large technology teams or extensive internal resources. With the right partner, financial institutions of all sizes can begin implementing AI solutions that align with their goals and capabilities, helping them reduce friction, improve efficiency, and create better experiences for customers and members. That accessibility matters because it allows more institutions to harness AI in service of what has always defined financial services: relationships.
Whether bank customers or credit union members are applying for a loan, opening an account, buying a home, or navigating a major life change, they expect convenience and speed. They also want trust, guidance, and empathy.
That’s why the driving goal of AI isn’t to just automate relationships; it’s to enable better ones. By removing friction and streamlining everyday work, AI gives employees more time to focus on meaningful conversations, personalized guidance, and the moments that build trust.
Financial institutions that embrace this distinction have an opportunity to use AI as a tool that makes every interaction more relevant, efficient, and meaningful. The institutions that get AI right won’t simply operate faster. They’ll create better experiences and stronger relationships.
Automate Tasks, Not Relationships
One advisor recently shared that before meeting with a small business customer, nearly an hour was spent gathering account information from multiple systems, reviewing notes, and preparing documentation. None of that work deepened the customer relationship, but it significantly reduced the time available to focus on the conversation itself.
Reality check: One of the biggest misconceptions about AI is that more automation means less human engagement. The challenge facing banks and credit unions isn’t that employees spend too much time building relationships. It’s that they spend too much time on administrative work, repetitive processes, and manual tasks that pull their attention away from customers and members.
Customers may appreciate requests being resolved instantly, but they still want access to a trusted advisor when making a major financial decision. The most effective AI strategies recognize this difference and use technology to amplify human expertise — not replace it.
What Human-Centered AI Looks Like in Practice
Lending and account opening are some of the most clear-cut examples of how AI can improve both operational efficiency and customer experience.
For many people, applying for a loan can be a frustrating process. There’s the extensive documentation, repeated requests for information, and delays from lengthy review cycles. Similarly, account opening experiences often require cumbersome data entry and complicated onboarding processes that create unnecessary friction.
AI can simplify both journeys.
By assisting with document collection, validating information, identifying missing data, and streamlining workflows, AI can accelerate processes that have traditionally required significant manual effort and time. Customers benefit from faster, more intuitive experiences, while employees spend less time managing paperwork and handling tedious administrative tasks.
But speed alone isn’t the goalpost for a successful AI use case. Loan officers can spend less time chasing documentation and more time helping borrowers understand their options. Customer-facing employees can focus on complex questions, personalized recommendations, and financial guidance instead of routine processing.
This becomes especially important when customers face situations that require context and experienced judgment. A first-time homebuyer, for example, may need reassurance and education throughout the lending process. A new member opening multiple accounts may benefit from personal guidance that no automated workflow can fully replicate.
Key insight: The goal isn’t to remove people from the process. It’s to ensure employees are available when guidance, expertise, and empathy matter most.
The Real Opportunity: More Personalized Engagement
Perhaps the most powerful opportunity for AI lies in customer or member insights.
Financial institutions possess a tremendous amount of data yet turning that information into meaningful action remains a persistent challenge. AI can help identify patterns, surface hidden needs, and highlight opportunities for proactive engagement that might otherwise go unnoticed.
A member carrying high-interest debt may be a strong candidate for refinancing or debt consolidation with their community FI. A customer who recently welcomed a child may benefit from conversations about savings or financial planning. A borrower approaching the end of a loan term may appreciate timely guidance on next steps.
Historically, identifying these opportunities required extensive manual analysis. Today, AI can help surface them more efficiently, allowing financial institutions to engage customers at the right time with relevant support and advice.
Key insight: This doesn’t mean relying on algorithms to manage customer relationships. It means equipping employees with better information so they can have better conversations.
In this way, AI becomes a catalyst for relationship banking rather than a replacement for it. It enables institutions to be more responsive, proactive, and personalized — qualities customers increasingly expect from their financial partners.
Trust Must Remain the Foundation
As AI adoption accelerates, reinforcing trust must remain central to every strategy.
Customers expect their financial institutions to handle data responsibly, use technology ethically, and make decisions fairly. They also expect transparency around how information is used and that important decisions are made by humans, not machines.
This is why human-centered AI requires governance. Human oversight remains essential, particularly in areas involving credit decisions, risk assessment, and customer outcomes that can have a meaningful impact on people’s financial lives. Financial institutions must establish strong data practices, maintain clear accountability, address potential bias, and ensure compliance with evolving regulatory expectations. They must regularly evaluate AI-driven outcomes and confirm that technology is supporting decision making, not overriding sound judgment.
Who is Positioned to Win?
Credit unions and community banks may be uniquely positioned to succeed in this new era.
These organizations have long competed on service, trust, and deeply personal customer relationships rather than scale alone. AI gives them an opportunity to amplify those strengths by helping employees operate more effectively and engage customers more proactively.
When routine activities become more efficient, employees have more time to focus on what matters most — their customers.
Bottom line: The institutions that win in the years ahead won’t be those that replace people with technology. They’ll be the ones that use technology to make every customer interaction more timely, relevant, and human. That’s the promise of human-centered AI.
