How Community Banks Can Turn Data Chaos Into AI Excellence

How Community Banks Can Turn Data Chaos Into AI Excellence

After spending several incredible days in New Orleans with New Jersey Bankers Association, I came away with valuable insights about the future of community banking, artificial intelligence, data strategy, and leadership in an industry experiencing rapid transformation.

Before the trip, I already considered New Orleans one of the top five cities to visit in the United States. After returning home, I still stand by that opinion. While my weekends in New Orleans look much different than they did 15 years ago, the city’s culture, food, and energy continue to make it a destination worth experiencing.

This trip was my first opportunity to participate in a parade down Bourbon Street — complete with a live band leading us out of the hotel. Fortunately, most evenings were spent enjoying outstanding meals across the city rather than revisiting my younger Bourbon Street habits.

Beyond the incredible atmosphere, the NJ Bankers event itself delivered meaningful conversations, professional development, and important discussions about the future of banking technology and AI adoption.

Emerging Leaders and the Value of Community Banking Collaboration

One of the highlights of the conference was connecting with fellow Emerging Leaders during a fantastic event hosted by NJ Bankers. Chef Eric led an unforgettable hands-on culinary experience where attendees learned to make gumbo, jambalaya, bananas foster, and pralines.

More importantly, the event reinforced something Andrea Ganzman, Director Digital Marketing & Creative for NJ Bankers. stated during the conference: this community exists for professionals who still feel they have room to grow in their careers. That mindset of continuous learning became a common theme throughout the conference.

Banking Regulation, Stablecoins, and Industry Change

Another valuable session featured Rob Nichols, President and CEO of the American Bankers Association (ABA). His presentation focused on several major topics currently shaping the banking industry, including:

• Payment stablecoins
• Consumer demand for interest-bearing products
• Cross-industry fraud prevention partnerships
• Regulatory changes affecting community banks

Nichols emphasized the importance of “baking into the cake” some of the recent regulatory changes impacting banking institutions. As compliance requirements evolve, banks must adapt proactively rather than reactively.

I also appreciated the discussion around the concept of the “Zen Banker” — the need for balance, simplicity, and adaptability in an industry facing constant operational, technological, and regulatory change.

Brittany Wheeler, NJ Bankers' Director of Government Affairs, also provided strong insight into New Jersey’s evolving political environment and NJ Bankers’ strategy for remaining competitive and influential in the years ahead.

Turning “Data Chaos Into AI Excellence” in Community Banking

One of the most impactful presentations came from John Kowal, SVP/Chief Technology Officer & Head of Analytics of Peapack Private Bank & Trust, and Steve Fusco, EVP/Chief Financial Officer of Spencer Savings Bank, during their packed session titled:

“Turning Data Chaos into AI Excellence”

The session highlighted a reality many community banks currently face: fragmented data environments and incomplete data warehouses.

A simple show of hands revealed that many banks are still working to centralize and validate their data before meaningful AI adoption can occur. Very few institutions currently possess what could truly be called a fully developed banking data warehouse.

This challenge is critical because the future of AI in banking depends entirely on trusted, accessible, and validated data.

Why AI Success in Banking Depends on Better Data

A particularly thought-provoking question from John Kowal stood out to me:

“What happens if you lock a newly hired data analyst in a room with all the bank’s data and ask them to produce a complete and valid balance sheet?”

My literal interpretation initially went somewhere involving HR and law enforcement, but the underlying message was powerful.

Even a talented data analyst could not produce accurate financial reporting without institutional knowledge, guidance, and structured data. So why would we expect general AI tools to succeed without those same foundations?

This perfectly illustrates where many community banks currently stand with AI adoption.

While AI presents tremendous opportunity, most community banks are still in the early stages of building the data infrastructure necessary to support meaningful AI-driven outcomes.

Small AI Wins Will Matter for Community Banks

One of the most realistic and encouraging themes from the conference was the idea that community banks do not need to solve every AI challenge immediately.

Instead, banks should focus on identifying:

• Broken processes
• Time-consuming manual tasks
• Inefficient reporting workflows
• Operational friction points

From there, institutions can evaluate how AI may simplify or improve those functions incrementally.

The future of banking AI likely will not arrive through one massive technology implementation. Instead, success will come through continuous iteration, evolving metrics, and ongoing refinement.

Traditional project management success criteria may no longer apply in an AI-driven environment.

Frictionless Data: The Foundation of Banking AI

Steve Fusco emphasized the importance of creating “frictionless data” environments where employees can easily access, analyze, and act on information as part of daily operations.

According to Fusco, leadership teams must stop treating only the symptoms of poor data management and instead address the foundational problems underneath them.

For some banks, that may mean:

• Building centralized data warehouses
• Improving data governance
• Enhancing reporting capabilities
• Investing in visualization tools
• Standardizing operational processes

Most importantly, banks must avoid simply layering AI tools onto broken or inefficient systems.

Strong AI outcomes require strong operational foundations.

Banking Cybersecurity and AI Risk Management

Cybersecurity also emerged as a major topic throughout the conference.

Bill Hickey of Piper Sandler & Co. discussed the increasing competitiveness of New Jersey banks and the pressure institutions face to differentiate themselves in a rapidly evolving financial landscape.

Meanwhile, Major General Anthony Genatempo reinforced the connection between:

• Banking strategy
• Cybersecurity
• AI implementation
• Data privacy

One particularly important concept discussed was the idea of “bank it for later” cyberattacks, where attackers quietly collect sensitive information over time before exploiting it later.

The message was clear: data security and privacy are no longer theoretical concerns. They represent active operational and reputational risks for both institutions and customers.

The Future of AI in Community Banking

The biggest takeaway from the NJ Bankers conference is that community banks have enormous opportunity ahead — but success with AI will depend on discipline, strategy, and strong data practices.

The institutions that succeed will combine:

• Trusted and validated data
• Frictionless access to information
• Strong cybersecurity practices
• Deep banking expertise
• Practical AI implementation strategies

AI alone is not the solution.

But when paired with strong operational foundations and thoughtful leadership, AI has the potential to fundamentally reshape how community banks serve customers, improve efficiency, and create long-term value.

And if nothing else, New Orleans remains one of the best places in America to have those conversations.

Want to explore what practical AI implementation could look like for your institution? Let’s start the conversation.