Forward Bank Builds a Responsible AI Adoption Program with WSI
Industry
Financial Services
Challenge
Expand AI use without overloading employees or compromising privacy, cybersecurity and compliance.
Results
Built a structured AI adoption program that helped teams test practical use cases, reduce manual work and identify where AI was delivering measurable value.
Key Service
AI Consulting
“Our relationship with Eric and the team at WSI has grown into far more than a typical consulting engagement. It is not simply tactical work, and it is not limited to strategic planning. What we have built together is a true thought partnership. Over time, that partnership has also become a friendship built on trust, curiosity, and a shared commitment to learning and improvement. We challenge one another, exchange ideas freely, and continue to grow together. Eric and the WSI team are as invested in Forward’s success as we are in building a strong and meaningful partnership with them.”
Sheri Dick
COO, Forward Bank
About Forward Bank
Forward Bank is a customer-owned community bank serving communities across Wisconsin and Minnesota. It provides personal, business and agricultural banking, along with insurance and investment services.
The Challenge
Forward Bank saw practical uses for AI across research, reporting, marketing and administrative work. Teams had ideas, but full workloads left little time to assess tools, test use cases or turn promising concepts into repeatable processes.
For a regulated financial institution, speed could not come at the expense of control. Each proposed use had to account for privacy, cybersecurity, regulatory requirements and human review. Leadership also needed evidence that AI was improving a process, rather than simply increasing tool usage.
The bank needed a way to turn AI ideas into controlled, measurable use without adding another burden to already busy teams.
The Solution
WSI helped Forward Bank build a responsible AI adoption program around those requirements. WSI Consultant Eric Cook, who spent 15+ years in community banking, worked with WSI's AI Strategy team to shape the program around banking operations and regulatory expectations.
That combination brought direct banking experience and broader AI expertise into the same engagement.
The work began with policies and review steps covering privacy, cybersecurity, compliance and human oversight. WSI then ran department-level Quick Win reviews to identify recurring work where AI could reduce manual effort and where before-and-after performance could be measured.
Role-based training connected AI to work employees already understood. Monthly champion sessions gave teams a regular place to bring operational questions, assess new use cases and share what they were learning.
Forward Bank also tracked Microsoft Copilot activity alongside estimated time savings and changes in process time. This gave leadership a clearer basis for deciding which uses were worth continuing, adjusting or expanding.
The program gave leadership a consistent way to decide whether an AI use case was worth expanding.
The Results
Forward Bank documented faster recurring workflows across risk, reporting and marketing as AI moved into day-to-day use. Process time fell by at least 75% across three measured workflows, giving leadership evidence of improvement beyond tool-usage numbers alone.
A separate compliance review identified an estimated 400–1,300 hours in potential annual savings if all identified improvements are implemented. That figure remains a projection, separate from savings already estimated or measured.
Forward Bank continues its monthly working sessions and is developing internal AI agents and larger systems, including a marketing intake platform. The program gives the bank a repeatable way to test ideas, measure results and expand the uses that earn further investment.
Forward Bank can now test AI against a business need, measure the result and make a more informed decision about what to expand.
Where Could AI Save Time in Your Business?
Talk with WSI about identifying a measurable first use case, putting the right controls around it and deciding what success should look like before you expand it.