Artificial Intelligence for Ohio Credit Unions: Where Should You Start?

Not long ago, I was having a conversation with a credit union leader who asked me a question I’ve been hearing more and more.

“Rusty, everybody keeps talking about AI. Are we already behind?”

I understood the concern.

Artificial intelligence seems to have gone from something we talked about someday using to something employees can access from their phones in a matter of seconds.

ChatGPT. Microsoft Copilot. Automated meeting notes. AI-powered cybersecurity tools. Marketing applications. Data analysis.

It seems like every technology company has suddenly added the letters “AI” to its products.

And when you’re responsible for protecting member information, keeping the credit union running, answering to a board, and making smart technology investments, it’s easy to wonder whether you should be moving faster.

Here’s what I tell people.

You don’t need to rush into AI. But you shouldn’t ignore it either.

For most Ohio credit unions, the right place to start isn’t buying another piece of technology.

It’s developing a plan.

AI Should Solve a Problem, Not Create a Project

I’ve been around technology long enough to see plenty of trends come and go.

Every few years, something new arrives that everyone supposedly has to have.

AI is different in one important way.

It’s already becoming part of the technology your employees use every day.

That makes the question less about whether your credit union will encounter AI and more about how you’re going to use it responsibly.

Before buying an AI product, start with a simple question:

“What problem are we trying to solve?”

Maybe employees spend hours summarizing documents.

Maybe marketing needs help developing first drafts.

Maybe your IT team is overwhelmed with repetitive support requests.

Maybe leadership wants better ways to analyze information.

Those are problems.

“Everybody else is using AI” isn’t.

Start with These Five Steps

If I were sitting with your leadership team today, I wouldn’t begin by showing you AI products.

I’d begin with five conversations.

1. Find Out Where AI Is Already Being Used

This one may surprise you.

Your organization may already be using artificial intelligence even if leadership hasn’t officially approved it.

An employee may use an AI assistant to improve an email.

Someone may summarize meeting notes.

Marketing may use it to brainstorm ideas.

Another employee may paste information into a public AI tool because it helps them finish a task faster.

Most of these employees aren’t trying to create a security problem.

They’re trying to do their jobs.

That’s why your first step should be understanding what’s already happening.

Ask:

• Which AI tools are employees currently using?
• Which applications you already license contain AI features?
• What information are employees putting into those systems?
• Are departments purchasing AI tools without IT review?
• Do employees understand what information should never be shared?

You can’t manage something you can’t see.

2. Protect Member Information First

Here’s where the conversation becomes especially important for credit unions.

Convenience can never come at the expense of member trust.

Employees need clear guidance about what information can—and cannot—be entered into AI systems.

Think about the information your organization handles every day.

Member information.

Financial records.

Loan documentation.

Employee records.

Internal reports.

Passwords and credentials.

Confidential business information.

Before employees begin experimenting with AI, leadership needs to establish clear boundaries around sensitive data.

A good rule is simple:

If you wouldn’t send the information to an unknown third party, don’t paste it into an unapproved AI tool.

Your specific policies should be developed around your own technology, compliance, security, and legal requirements, but the principle is straightforward.

Protect the member first.

3. Create an AI Acceptable-Use Policy

Policies don’t need to be fifty pages long to be useful.

In fact, the best ones usually aren’t.

Employees need practical answers.

Can I use AI to draft an email?

Can I summarize a document?

Can I use it to analyze member information?

Can I upload an internal spreadsheet?

Can I use AI-generated content without reviewing it?

What happens if the AI gives me incorrect information?

Your policy should establish what’s permitted, what’s prohibited, and when employees need approval.

Most importantly, explain why.

People follow policies more consistently when they understand the risk behind them.

4. Start Small

I wouldn’t recommend making your first AI initiative something mission-critical.

Start where the consequences of a mistake are relatively low and a human remains in control.

Potential early uses might include:

• Brainstorming internal communications
• Creating first drafts of non-sensitive content
• Summarizing non-confidential information
• Developing meeting agendas
• Organizing project notes
• Helping employees understand complex technical concepts
• Creating training materials

Notice what’s common about those examples?

A person still reviews the work.

That’s important.

AI should help your employees make better decisions.

It shouldn’t quietly make important decisions for them.

5. Measure Whether It’s Actually Helping

This is the step I think gets forgotten most often.

Buying AI isn’t success.

Using AI isn’t success.

Creating measurable value is success.

If a tool saves an employee 20 minutes on a task they perform three times a week, that’s something you can measure.

If it helps your IT team resolve common requests faster, measure it.

If it improves the speed of an internal process, document the improvement.

After 60 or 90 days, ask:

• How much time did we save?
• Did quality improve?
• Did employees actually use the tool?
• Did we introduce new security concerns?
• What did we learn?
• Should we expand, change, or stop the pilot?

That turns AI from an experiment into a business decision.

Where Should Credit Unions Be Careful?

This is where I’d encourage leadership to slow down.

Artificial intelligence can produce answers that sound remarkably confident while still being wrong.

That’s inconvenient when you’re writing a birthday invitation.

It’s a much bigger problem when you’re dealing with financial, regulatory, security, or member decisions.

Be particularly cautious when AI touches areas involving:

• Member financial information
• Lending decisions
• Compliance interpretations
• Legal matters
• Cybersecurity configurations
• Employee decisions
• Confidential documents
• Authentication credentials

AI can assist people working in sensitive areas.

That doesn’t mean it should replace human judgment.

Don’t Forget About Your Existing Vendors

There’s another part of AI adoption that doesn’t get enough attention.

Your vendors are adopting AI too.

Your core provider may introduce AI features.

Microsoft may add AI capabilities to applications you already use.

Your cybersecurity providers may use machine learning or generative AI.

Other software vendors will introduce AI assistants.

So vendor management needs to become part of your AI strategy.

Ask vendors:

• What data does the AI feature access?
• Where is that information stored?
• Is customer information used to train models?
• Who can access the information?
• Can the AI feature be disabled?
• What controls are available to administrators?

You don’t need to become an AI engineer.

You do need to understand where your information is going.

What About Microsoft Copilot and Other Enterprise AI Tools?

This is where having a technology roadmap becomes important.

Enterprise AI platforms may provide better administrative and security controls than employees independently using consumer tools.

But buying an enterprise AI license doesn’t automatically make your organization ready.

Your permissions matter.

Your Microsoft 365 environment matters.

Your data governance matters.

Your employee training matters.

If an employee already has access to information they shouldn’t, AI may make it easier to find that information.

That’s why I prefer to fix the foundation first.

Then add the technology.

The Board Needs to Be Part of the Conversation

AI shouldn’t live entirely inside the IT department.

Leadership and the board should understand:

• Where AI is being used
• What risks have been identified
• What policies are in place
• Which projects are being tested
• How member information is protected
• What business value the organization expects

They don’t need a technical presentation.

They need a business conversation.

The question isn’t:

“Which artificial intelligence model are we using?”

It’s:

“How are we using this technology responsibly while protecting our members?”

That’s a question every board can understand.

A Situation We’re Going to See More Often

Imagine one of your best employees.

She’s been with the credit union for 15 years.

Members love her.

She’s careful, hardworking, and always looking for ways to get more done.

She discovers an AI tool that can summarize documents in seconds.

So she uploads something from work.

She isn’t trying to break a policy.

She isn’t trying to expose information.

She’s trying to be productive.

That’s why simply telling employees, “Don’t use AI,” isn’t much of a strategy.

People need education.

They need approved tools.

They need boundaries.

And they need leadership that understands both the opportunity and the risk.

The goal shouldn’t be to make employees afraid of AI.

It should be to help them use it wisely.

The Five Questions I’d Ask Before Approving an AI Project

Before your credit union invests in an AI initiative, ask these five questions:

1. What problem are we solving?

If you can’t explain it clearly, you’re probably not ready to buy anything.

2. What information will the AI access?

Know your data before you introduce the tool.

3. How will we protect member information?

Security and privacy belong at the beginning of the project—not the end.

4. Who reviews the AI’s work?

For important decisions, human oversight matters.

5. How will we measure success?

Define the outcome before starting the pilot.

Those five questions will eliminate a surprising amount of unnecessary risk.

What Could AI Look Like Five Years From Now?

Nobody knows.

And anyone who tells you they know exactly where AI will be five years from now is probably trying to sell you something.

What I do believe is that AI will increasingly become part of the technology we already use.

Employees won’t necessarily “go use AI.”

It will be built into email.

Documents.

Cybersecurity.

Banking applications.

Customer service tools.

Analytics.

Business systems.

That’s why your biggest investment today may not be an AI product.

It may be building an organization that’s prepared to evaluate new technology intelligently.

Good governance.

Strong cybersecurity.

Clean data.

Educated employees.

Thoughtful leadership.

Trusted technology partners.

Those things will matter regardless of which AI platform wins the next round of headlines.

Final Thoughts

Whenever a major technology change arrives, there’s pressure to move quickly.

I understand it.

Nobody wants their credit union to fall behind.

But I’ve learned something after more than 26 years in technology:

Moving first isn’t nearly as important as moving wisely.

Artificial intelligence has tremendous potential to help credit unions become more efficient, help employees work smarter, and improve how organizations use information.

But the technology should always serve the mission.

Not the other way around.

Start small.

Protect your data.

Educate your employees.

Measure the results.

Learn.

Then take the next step.

You don’t need to have your entire AI strategy figured out today.

You just need to make the first decision thoughtfully.

Because the goal isn’t to become an AI-powered credit union.

The goal is to become a stronger credit union that knows how to use AI wisely.

And through all of it, one thing should remain unchanged:

Protect the trust your members have placed in you.

Not Sure Where Your Credit Union Should Start With AI?

You don’t need another company trying to sell you an AI product.

You need a technology partner who can help you understand what makes sense for your organization—and what doesn’t.

At CTG, we’ve spent more than 26 years helping organizations make practical technology decisions. Our team brings more than 200 years of combined experience, with a vendor-agnostic approach that puts your organization’s needs ahead of any particular technology.

We can help your credit union evaluate its current technology environment, identify appropriate AI opportunities, strengthen the security foundation underneath them, and build an AI roadmap that fits into your broader three-to-five-year technology strategy.

Whether you’re considering Microsoft Copilot, developing an AI acceptable-use policy, evaluating AI features from existing vendors, or simply trying to answer your board’s questions, we’ll help you separate practical opportunity from hype.

Talk with CTG

Phone: 330-655-8144
Email: brett.harney@ctgusa.net
Website: ctgusa.net

Let’s have a conversation about where AI fits into your credit union’s future—before you spend money figuring it out the hard way.