Blog Post

Three Practical Pillars of AI Readiness

Banks and credit unions are entering a new phase of AI adoption. According to a recent McKinsey analysis, the industry is rapidly shifting from basic pilots to agentic AI systems capable of executing complex workflows, modernizing legacy processes, and reducing operational costs by up to 20%. For institutions still in the early stages, this brings both urgency and opportunity. The question is no longer “Should we use AI?” — it’s “How do we get ready?”

Written by

Hapax Team

Published on

December 1, 2025

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‍Why AI Readiness Matters

McKinsey warns that banks that delay modernization could lose as much as $170 billion in profits by 2030. Competitive pressure is also rising from consumer-facing “shopping agents” that can instantly move deposits to better offers — shrinking the traditional loyalty advantage many community institutions rely on.

AI-ready institutions will be able to:

Automate manual processes
Improve compliance accuracy
Respond faster to member needs
Reduce operational costs
Retain deposits through smarter, more personalized offers

You don’t need a massive budget or a full data science team to start. The leaders are focusing on simple, foundational moves that create long-term advantage.

Pillar 1: Modernize Core Knowledge & Infrastructure

Before any AI tool can help, it needs clear access to policies, procedures, documents, and data.

Start with:

Digitizing and centralizing key documents
Cleaning up outdated information
Reducing file-share sprawl
Making policies easy to find and interpret

AI cannot follow rules it can’t see.

Pillar 2: Focus on Targeted Use Cases

Skip the blank-sheet brainstorming.

Instead, identify:

Repeatable processes
High-volume tasks
Areas with compliance risk
Functions with long cycle times

Early wins often come from frontline pain points like account onboarding, loan origination documentation, reporting, or policy interpretation.

Pillar 3: Build Governance & Human Oversight

AI should make people better — not replace judgment.

Readiness includes:

Clear guardrails for sensitive decisions
Human approvals where required
Audit logging
Alignment to internal policies and regulatory frameworks

Think “human-in-the-loop” rather than “fully autonomous.”

The Bottom Line

Agentic AI isn’t science fiction; it’s already reshaping operating models, cost structures, and consumer expectations.

And readiness is the deciding factor.

Banks and credit unions that invest now in:

Clean, structured knowledge
Targeted, high-value use cases
Thoughtful oversight and governance

Will be best positioned to scale safely, serve members better, and stay competitive in an AI-driven financial ecosystem.

You don’t have to be first — but you can’t afford to be unprepared.

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