Assessment

AI Readiness Assessment for Financial Institutions

Evaluate organisational readiness for AI across data, governance, talent, and use cases.

AIStrategyGovernance

About This Resource

A structured assessment that scores your institution across four dimensions: data infrastructure, governance and risk controls, talent and capability, and use-case pipeline maturity. Produces a readiness score per dimension and an overall rating.

When to Use

Before committing budget to an AI programme, or when preparing a board presentation on AI strategy.

Audience

CIO, CDO, CTO, Strategy Lead

What You Bring
  • Data infrastructure quality
  • Governance frameworks in place
  • Talent availability
  • Identified use cases
What You Get
  • Dimension-level readiness scores
  • Overall AI readiness rating
  • Priority action areas

Complete the Assessment

0 of 12 questions answered0% complete

1. Data Infrastructure

How would you describe the overall quality of your institution's data?

How accessible is your data to analytics and AI teams?

How mature is your data labelling and feature engineering capability?

2. Governance & Risk Controls

Does your institution have an AI governance policy or framework?

How are AI model risks (bias, explainability, drift) managed?

How prepared is your institution for AI-related regulatory requirements?

3. Talent & Capability

What AI and data science talent does your institution have in-house?

How AI-literate is your senior leadership team?

How well does your institution manage AI vendor and partner relationships?

4. Use Case Pipeline Maturity

How many validated AI use cases does your institution have in its pipeline?

How are AI use cases prioritised and approved?

How many AI use cases are currently in production?