AI Readiness Assessment

This helps us understand where you're starting from

This helps us tailor recommendations to your sector

Understanding where time and money are wasted is critical for AI success

These are the highest-ROI opportunities for AI

Leadership buy-in is critical for successful AI implementation

Prior experience indicates organizational learning and readiness

A structured approach ensures you pursue high-value initiatives

Describe your key success metrics, for example: reduce processing time by 50%, improve customer satisfaction, automate invoice handling.

Select all that apply

Consider completeness, accuracy, and consistency

Centralized documentation enables faster AI deployment

Measuring baseline metrics is essential to prove AI ROI

Experimentation capability determines how quickly you can deploy AI

Replicating wins is how AI scales across your business

List tasks that consume significant time. Separate each task with a comma.

Cultural readiness is often the biggest barrier to adoption

Structured change management improves success rates significantly

Select all that apply

Select all that apply

Continuous learning is essential for sustainable AI adoption

External expertise can accelerate adoption

Select all that apply. This does not increase your readiness score by itself; it helps identify the level of control needed before AI is used safely.

Enter any other compliance requirements, such as ISO 27001, SOC 2, client confidentiality obligations, sector rules, or internal audit requirements.

This is especially important for client data, regulated data, payroll, trust records, medical data, financial data, and confidential documents.

Governance ensures ethical, compliant, and responsible AI use

Ongoing monitoring prevents unintended consequences

A practical policy should explain what staff can use AI for, what data must not be entered, and when human approval is required.

This matters when client, regulated, or confidential business data may pass through a third-party AI platform.

This covers advice, client responses, compliance decisions, financial outputs, HR decisions, and anything that could create legal or reputational risk.

Auditability is critical when AI supports regulated work, client decisions, due diligence, compliance, or financial operations.

Comfort only scores well when governance exists. High confidence without controls is treated as a risk, not readiness.