Most credit unions don’t choose an AI architecture. They inherit it from the automated solutions they’ve built over time. Each was a reasonable decision, but in the agentic era, it’s essential to create a unified infrastructure for managing AI agents across the organization.
There are three patterns for automating work with AI: deterministic, single-agent, and multi-agent systems. Each solves a different problem, and none can be applied to every problem. This whitepaper helps leaders make intentional architectural decisions by matching the right pattern to the task before building.
A plain-language breakdown of three automation patterns (deterministic, single-agent, and multi-agent) and the type of judgment each is designed to handle.
A four-question decision flow that maps any workflow to the right architecture before you build, plus a scenario lookup for edge cases.
A governance lens for each pattern, including what examiners expect to see.
A readiness assessment that goes beyond asset tier to cover ownership, data infrastructure, prior automation experience, and board appetite.
Four real-world credit union operational examples showing where each pattern fits.
A maturity path, designed to keep the board, exam team, and staff aligned as deployments expand.
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