Assess and Prioritize Agentic AI Use Cases in Financial Services

Scale agentic AI across lending, payments, and customer operations without increasing regulatory and model risk exposure.
Move beyond pilots to auditable, explainable autonomous decisioning in credit, fraud, and compliance workflows.
Align AI-driven decisions with risk appetite, regulatory obligations, and customer trust.

Our Advice

Critical Insight

Agentic AI supports the ability to:

Govern autonomy to unlock enterprise value.
Align C-suite sponsorship across functions.
Prioritize value streams for risk-adjusted impact.
Redesign operating models around agent capabilities.

Impact and Result

Define where autonomy is permitted across high-risk workflows (e.g. credit decisions, fraud response, AML triage).
Build data, governance, and model risk controls to support auditable, compliant AI decisions.
Prioritize defensible use cases and scale through reusable, governed agent capabilities.

Assess and Prioritize Agentic AI Use Cases in Financial Services Research & Tools

1. Assess and Prioritize Agentic AI Use Cases in Financial Services Deck – Determine where autonomous agents can operate with regulatory constraints, can add value, and are worth scaling.

Financial Services organizations must scale agentic AI across lines of business without increasing regulatory and model risk exposure. This requires moving beyond pilots to auditable, explainable autonomous decisioning while aligning AI-driven decisions with risk appetite, regulatory obligations, and customer trust.

This storyboard guides financial services leaders through a four-phase approach:
1) Define vision and autonomy boundaries
2) Validate readiness across data, governance, and talent
3) Prioritize use cases based on value, feasibility, and risk
4) Deploy pilots and build reusable components

2. Agentic AI Use Case Tool for Financial Services – Use this structured scoring framework to evaluate and prioritize agentic AI use cases across financial services operations.

The Excel tool provides a systematic framework for financial institutions to assess value, risk, and governance readiness with 30+ pre-populated financial services industry use cases.

The tool enables teams to define custom scoring criteria, evaluate use cases across business impact and implementation feasibility dimensions, and generate a prioritized portfolio with clear tier assignments.

Determine where autonomous agents can operate with regulatory constraints, add value, and are worth scaling.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Get the help you need in this 5-phase advisory process. You'll receive multiple touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Pre-Work

Call 1: Scope objectives and key challenges.

Guided Implementation 2: Define Vision and Autonomy Boundaries

Call 1: Define AI vision and business value.
Call 2: Establish autonomy boundaries and escalations.

Guided Implementation 3: Validate Readiness

Call 1: Assess data, governance, and talent readiness.
Call 2: Strengthen foundations and define decision rights.

Guided Implementation 4: Prioritize Use Cases

Call 1: Identify and map candidate use cases.
Call 2: Evaluate and prioritize pilots based on value, feasibility, and risk.

Guided Implementation 5: Deploy Pilots

Call 1: Launch pilots with continuous evaluation.
Call 2: Refine governance, scale agents, and build reusable components.

Author

Mitchell Fong

Contributors

Four anonymous external contributors