BOULDER CITY, Nev. — Artificial intelligence could eliminate much of the routine data gathering, manual processing and administrative “dead space” inside credit unions while allowing employees to focus on decisions, relationships and growth, according to two executives who said institutions should be redesigning workflows rather than simply adding AI to existing processes.
Raj Bandaru, CTO with Kinecta Credit Union in California, and Stephen Bohanan, founder and chief strategy officer with Alkami, discussed the issue during “The AI Imperative: AI for Operations: Redesigning Work, Workforce and Workflow,” the fifth installment of a seven-part AI Imperative webinar series hosted by The CU Daily and Mitchell Stankovic and Associates.
Bandaru described AI as an “intelligence augmentation” tool and a “force multiplier” that has dramatically shortened research and analysis.
During recent strategic planning, he said competitive analysis that previously might have required weeks, months or outside vendors could be completed in hours.
“Things that would have taken us weeks and months to do from a research standpoint, you’re able to get done in a few hours,” Bandaru said.
Eliminating the ‘Tax’ on Work
Bohanan said organizations effectively pay a “tax” throughout operational processes as employees gather background information, route work between departments, research previous cases and wait for others to respond.
AI can eliminate much of that lost time without necessarily eliminating humans from the process.
He cited Alkami’s use of AI agents to manage support tickets. The technology can analyze an incoming request, gather information about the customer and product, review previous tickets and determine which employee is best qualified and available to respond.
What once required multiple handoffs can occur within seconds, he said.
For credit unions, a similar approach could quickly route a member issue to the appropriate mortgage, lending or other specialist rather than leaving the member waiting while employees determine where it belongs.
Humans Remain in the Loop
Both executives said AI’s growth doesn’t mean humans disappear from credit union operations.
Bandaru said employees remain essential whenever decisions involve judgment, accountability, relationships, empathy, risk, fraud or exceptions.
“The human has to be in the loop when there is a judgment involved,” he said.
The objective should be automating repetitive, low-value work and allowing employees to “move up the value chain,” Bandaru said.
Bohanan compared the transition to construction workers moving from shovels to backhoes. Employees shouldn’t assume the arrival of more powerful technology makes them obsolete, he said, but they do need to learn how to operate the new equipment.
Where Credit Unions Should Start
Bandaru said Kinecta began with employee education, making AI tools available and requiring training in prompt and context engineering.
The next step is teaching employees how to embed AI into their daily workflows while management identifies inefficient processes that could become specific use cases.
Credit unions need to demonstrate that AI is intended to help employees rather than replace them, he said.
Bohanan recommended first identifying the 10 to 20 activities consuming the most time and money, such as opening accounts, booking loans, resolving fraud disputes and handling member service requests.
Institutions should then apply what he called a “blank sheet test” rather than simply automating existing processes.
“What information is genuinely required, and what decision must be made, and which rules are mandatory, and when is human judgment truly valuable?” Bohanan said.
Productivity Gains Emerging
Bandaru said Kinecta expects AI literacy and adoption to produce productivity improvements of 10% to 20% in office work.
In payments operations, he said automation of previously manual tasks is already producing productivity gains of approximately 20% to 40%.
But Bandaru said he ultimately wants AI measurement to shift beyond back-office efficiency toward growth and member experience.
Kinecta recently launched its first hyper-personalized marketing campaign using several AI models and existing member behavioral and transaction data.
Instead of traditional “spray-and-pray” marketing, Bandaru said the goal is one-to-one offers relevant to individual members.
Bohanan said AI’s workforce impact could depend heavily on whether an organization is growing. Fast-growing institutions could use AI to increase business without adding employees at the same rate, while organizations experiencing little or no growth could face pressure to reduce headcount as productivity increases.
Within two years, both executives predicted many routine back-office practices will appear antiquated.
Manual data entry, moving documents, assembling reports and gathering information before making decisions increasingly will be automated, they said.
Employees instead will receive synthesized information and AI-generated recommendations almost immediately, leaving humans responsible for what remains most important: applying judgment and making the final decision.
For more information on the AI Imperative series, go here.
