AI Readiness Assessment

This quick AI Readiness Assessment evaluates how prepared your organization is to embrace AI. At the completion of the assessment, you can find out your AI readiness and next actions to help you move forward with confidence.

The results of your assessment are Confidential to you and your organization. This assessment is designed to create an understanding of current AI readiness.

Thank you for your time in completing this assessment.

Question Title

How prepared do you feel about deploying AI successfully into your business?

1 — Not Prepared at All

2 — Slightly Prepared

3 — Moderately Prepared

4 — Very Prepared

5 — Fully Prepared

Section 1 - Governance & Oversight

Question Title

Does your organization have clear, communicated guidelines or policies on AI use?

1 = None

2 = Informal

3 = Basic draft

4 = Approved policy

5 = Fully implemented policy

Question Title

Are there designated roles or committees overseeing AI implementation and risk?

1 = None

2 = Ad-hoc

3 = Emerging roles

4 = Formal oversight group

5 = Fully active AI governance committee

Question Title

Are there defined escalation channels for data, ethics, or compliance concerns?

1 = None

2 = Unclear

3 = Partially defined

4 = Defined but not used

5 = Clear and active

Question Title

How consistently are AI activities reviewed or audited for compliance?

1 = Never

2 = Occasionally

3 = Quarterly

4 = Regularly

5 = Ongoing audit framework

SECTION 2 – Data Quality & Compliance

Question Title

How would you describe the quality, structure, and accessibility of your organization’s data?

1 - Poor / Unstructured / Fragmented

2 - Basic / Partially Structured

3 - Moderate / Improving

4 - Good / Integrated

5 = Excellent / Unified

Question Title

Are data privacy and security policies (e.g., HIPAA, GDPR) actively enforced for AI use?

1 – None / Unaware - No clear data privacy policies or awareness of regulatory requirements.

2 – Low Awareness - Policies exist but rarely enforced or only applied when issues occur.

3 – Partial / Developing - Policies applied inconsistently; limited monitoring of AI-related use.

4 – Strong / Proactive - Policies actively enforced, with clear accountability for compliance.

5 – Mature / Embedded - Comprehensive privacy program integrated into AI processes with regular audits and training.

Question Title

Do teams understand where and how AI tools store or process company data?

1 – Not Aware - No understanding of where or how AI tools store or process data.

2 – Low Awareness - Some team members aware, but not documented or communicated.

3 – Partial Awareness - Awareness for major tools, but not all; unclear for third-party AI.

4 – Broad Awareness - Most teams know how AI tools manage data; oversight improving.

5 – Full Awareness - Comprehensive understanding and documentation for all AI tools in use.

Question Title

Is sensitive data segregated from general-use data before being shared with AI systems?

1 – Never - Sensitive data often shared directly with AI tools without control.

2 – Rarely - Some attempts to remove sensitive info, but inconsistent.

3 – Sometimes - Data segregation happens for certain projects, but not standardized.

4 – Usually - Regular process to separate sensitive data, with few exceptions.

5 – Always - Sensitive data always filtered or anonymized via formal policy before AI use.

Question Title

How confident are you that AI tools comply with enterprise or regulatory data requirements?

1 – Not Confident - No validation or oversight of compliance.

2 – Low Confidence - Some awareness, but no testing or vendor assurance.

3 – Moderate Confidence - Compliance checks for major tools, but informal or incomplete.

4 – High Confidence - Vendor or internal validation done regularly; minor gaps remain.

5 – Full Confidence - Formal compliance verification process for all tools, with documentation and audits.

SECTION 3 – People & Culture

Question Title

How familiar are employees with AI capabilities and limitations?

1 – Unfamiliar - Most employees have little or no understanding of AI concepts or tools.

2 - Limited Awareness - Some individuals are aware of AI, but understanding is basic and inconsistent.

3 – Moderate Awareness - General understanding exists; a few employees apply AI effectively in daily work.

4 – Broad Understanding - Majority of employees understand AI’s potential and boundaries; growing competence.

5 – Highly Knowledgeable - Employees across the organization are well-trained, aware of AI risks, and use it effectively.

Question Title

Is AI-related education or awareness training provided?

1 – None - No AI awareness or training opportunities available

2 – Informal - Occasional or voluntary sessions with no structured program

3 – Basic Program - Some structured training exists, but not mandatory or organization-wide.

4 – Regular & Structured - Regular AI training for key roles; growing inclusion in onboarding.

5 – Ongoing / Embedded - Continuous organization-wide training program integrated into employee development.

Question Title

How open are teams to experimenting with AI in their daily work?

1 – Resistant - Teams avoid using AI or view it as a threat or distraction.

2 – Hesitant - Limited experimentation; lack of confidence or leadership support.

3 – Neutral / Cautious - Some teams trying AI on small tasks, but not yet normalized.

4 – Supportive / Curious - Majority open to trying AI tools; growing interest and use cases.

5 – Proactive / Innovative - Teams actively explore, share learnings, and drive innovation with AI.

Question Title

How well do leaders communicate the purpose and value of AI adoption?

1 – Not at All - No communication or alignment from leadership regarding AI.

2 – Minimal - AI occasionally mentioned, but without clear purpose or follow-up.

3 – Moderate - Leaders discuss AI’s potential but without detailed strategy or consistent messaging.

4 – Clear and Supportive - Leaders articulate AI goals, encourage participation, and provide some guidance.

5 – Strong and Consistent - Leadership consistently communicates vision, progress, and role of AI in strategy.

SECTION 4 – Technology & Use Cases

Question Title

Which areas of the business currently use or plan to use AI?

Marketing

Operations / Supply Chain

Finance / Accounting

Human Resources

IT / Data / Security

Clinical or Service Delivery

Customer Service

Compliance / Legal

Other (please specify)

Question Title

Are current AI uses integrated into workflows or mainly individual experiments?

1 – None - No AI use currently in place.

2 – Ad Hoc - Individual experimentation; no integration into core work.

3 – Partial Integration - Some teams use AI in specific workflows, but inconsistent across departments.

4 – Departmental Integration - AI embedded into key departmental processes or tools.

5 – Enterprise Integration - AI seamlessly embedded across business systems and operations.

Question Title

Do you have defined KPIs or metrics to measure the success of AI pilots?

1 – None - No defined measures of success for AI projects

2 – Informal - Some informal or subjective measures used.

3 – Partial / Emerging - A few defined KPIs exist but applied inconsistently.

4 – Defined - Clear KPIs defined for all AI pilots with periodic review.

5 – Mature / Impact-Linked - Comprehensive KPI framework linked to business outcomes and ROI.

Question Title

Are your core systems (IT infrastructure, APIs, data sources) ready to integrate with AI tools?

1 – Not Ready - Legacy systems or fragmented infrastructure; no AI integration possible.

2 – Limited Readiness - Minimal connectivity or compatibility; pilots require heavy manual work.

3 – Moderate Readiness - Some systems can integrate with AI; APIs or data pipelines partly in place.

4 – High Readiness - Most core systems can connect to AI tools with moderate effort.

5 – Fully Ready - Modern, cloud-based, API-driven systems ready for scalable AI deployment.

Question Title

How would you describe your organization’s AI maturity stage?

1 – Early / Observing Only - Limited awareness; exploring concepts but not using AI yet.

2 – Experimenting - Small-scale pilots or informal testing underway.

3 – Emerging - Multiple departments using AI; early lessons being captured.

4 – Scaling - AI embedded in processes with measurable benefits and leadership sponsorship.

5 – Optimized / Strategic - AI central to operations, strategy, and innovation.

Question Title

Are there clear criteria for selecting or approving AI tools?

1 – None - No criteria or approval process in place for selecting AI tools.

2 – Informal - Tool selection made by individuals or teams without governance input.

3 – Partial - Some review for data security or cost, but no standardized policy.

4 – Structured - Formal approval process involving IT or Compliance review.

5 – Governed - Enterprise-wide evaluation framework (security, privacy, ethics, ROI) before deployment.

SECTION 5 – Strategy & Value Alignment

Question Title

Is AI adoption tied to measurable business objectives or outcomes?

1 – Not Linked - AI projects are run without connection to business goals or KPIs.

2 – Loose Association - Some initiatives mention business benefits but aren’t measured.

3 – Partially Aligned - Certain AI pilots track basic outcomes (e.g., time saved).

4 – Aligned and Tracked - Most AI initiatives linked to departmental KPIs with periodic review.

5 – Fully Integrated & Measured - AI adoption is embedded in enterprise strategy and performance scorecards.

Question Title

Does leadership have an AI roadmap or vision for the organization?

1 – None - No defined AI vision or leadership direction

2 – Informal Ideas - AI occasionally discussed but not documented.

3 – Emerging Plan - Draft vision or departmental roadmaps being developed.

4 – Documented Roadmap - Formal AI strategy approved by leadership and shared internally.

5 – Strategic Vision Embedded - AI vision fully integrated into corporate strategy and review processes.

Question Title

Are resources (budget, people, time) specifically allocated for AI initiatives?

1 – None - No resources or funding dedicated to AI work.

2 – Ad Hoc - Funding approved case-by-case with no ongoing commitment.

3 – Partial - Limited budget or team time allocated for AI pilots.

4 – Dedicated Line Item - AI budget and resources approved annually for key projects

5 – Sustained Investment - Ongoing funding and staff capacity for AI governance, training, and scaling.

Question Title

Do you have a plan to scale successful pilots into broader deployment?

1 – No Plan - No defined path for expanding AI pilots beyond testing.

2 – Informal Intent - Scaling discussed but not documented or resourced.

3 – Emerging Framework - Some pilots scaled within departments; no enterprise process yet.

4 – Structured Approach - Clear criteria and resources to expand successful pilots.

5 – Institutionalized Process - Formal enterprise-wide framework for replicating and monitoring scaled AI solutions.

Question Title

How well is ROI or impact from AI initiatives tracked and reported?

1 - Not Tracked - No measurement or reporting of AI impact

2 – Basic Tracking - Some outputs tracked (e.g., usage or cost savings) but not standardized

3 – Developing - ROI metrics defined for major pilots; reporting occasional. -

4 – Consistent Tracking - ROI or value metrics tracked regularly and shared with leadership.

5 – Optimized Reporting - Standardized ROI framework used organization-wide for decision-making and improvement.

Wrap up Questions

Question Title

How prepared do you feel now about deploying AI successfully into your business?

1 — Not Prepared at All

2 — Slightly Prepared

3 — Moderately Prepared

4 — Very Prepared

5 — Fully Prepared

Question Title

Please rank these objectives for implementing AI for your business by priority, with 1 being the highest priority etc.

Question Title

If you are considering implementing AI into your business, what type of initiatives you would want to implement?

SECTION 6 – Results & Follow-Up

Question Title

Would you like a personalized AI Readiness Report or follow-up discussion?

Personalized AI Readiness Report summarizing results

Discussion about AI pilot opportunities in your organization

Responsible AI and governance training for leaders or teams

Participation in an AI Organization Opportunity & Risk Survey

No follow-up at this time

Question Title

Please Provide your Contact Details (Required.)

Frist Name

Surname

email address

Phone Number

Question Title

If you have any comments or questions - we would love to hear from you!
Thank you for your time.

Page1 / 1

100% of survey complete.

AI Readiness Assessment

Question Title

* How prepared do you feel about deploying AI successfully into your business?

Question Title

* Does your organization have clear, communicated guidelines or policies on AI use?

Question Title

* Are there designated roles or committees overseeing AI implementation and risk?

Question Title

* Are there defined escalation channels for data, ethics, or compliance concerns?

Question Title

* How consistently are AI activities reviewed or audited for compliance?

Question Title

* How would you describe the quality, structure, and accessibility of your organization’s data?

Question Title

* Are data privacy and security policies (e.g., HIPAA, GDPR) actively enforced for AI use?

Question Title

* Do teams understand where and how AI tools store or process company data?

Question Title

* Is sensitive data segregated from general-use data before being shared with AI systems?

Question Title

* How confident are you that AI tools comply with enterprise or regulatory data requirements?

Question Title

* How familiar are employees with AI capabilities and limitations?

Question Title

* Is AI-related education or awareness training provided?

Question Title

* How open are teams to experimenting with AI in their daily work?

Question Title

* How well do leaders communicate the purpose and value of AI adoption?

Question Title

* Which areas of the business currently use or plan to use AI?

Question Title

* Are current AI uses integrated into workflows or mainly individual experiments?

Question Title

* Do you have defined KPIs or metrics to measure the success of AI pilots?

Question Title

* Are your core systems (IT infrastructure, APIs, data sources) ready to integrate with AI tools?

Question Title

* How would you describe your organization’s AI maturity stage?

Question Title

* Are there clear criteria for selecting or approving AI tools?

Question Title

* Is AI adoption tied to measurable business objectives or outcomes?

Question Title

* Does leadership have an AI roadmap or vision for the organization?

Question Title

* Are resources (budget, people, time) specifically allocated for AI initiatives?

Question Title

* Do you have a plan to scale successful pilots into broader deployment?

Question Title

* How well is ROI or impact from AI initiatives tracked and reported?

Question Title

* How prepared do you feel now about deploying AI successfully into your business?

Question Title

* Please rank these objectives for implementing AI for your business by priority, with 1 being the highest priority etc.

Question Title

* If you are considering implementing AI into your business, what type of initiatives you would want to implement?

Question Title

* Would you like a personalized AI Readiness Report or follow-up discussion?

Question Title

* Please Provide your Contact Details (Required.)

Question Title

* If you have any comments or questions - we would love to hear from you! Thank you for your time.

How prepared do you feel about deploying AI successfully into your business?

Does your organization have clear, communicated guidelines or policies on AI use?

Are there designated roles or committees overseeing AI implementation and risk?

Are there defined escalation channels for data, ethics, or compliance concerns?

How consistently are AI activities reviewed or audited for compliance?

How would you describe the quality, structure, and accessibility of your organization’s data?

Are data privacy and security policies (e.g., HIPAA, GDPR) actively enforced for AI use?

Do teams understand where and how AI tools store or process company data?

Is sensitive data segregated from general-use data before being shared with AI systems?

How confident are you that AI tools comply with enterprise or regulatory data requirements?

How familiar are employees with AI capabilities and limitations?

Is AI-related education or awareness training provided?

How open are teams to experimenting with AI in their daily work?

How well do leaders communicate the purpose and value of AI adoption?

Which areas of the business currently use or plan to use AI?

Are current AI uses integrated into workflows or mainly individual experiments?

Do you have defined KPIs or metrics to measure the success of AI pilots?

Are your core systems (IT infrastructure, APIs, data sources) ready to integrate with AI tools?

How would you describe your organization’s AI maturity stage?

Are there clear criteria for selecting or approving AI tools?

Is AI adoption tied to measurable business objectives or outcomes?

Does leadership have an AI roadmap or vision for the organization?

Are resources (budget, people, time) specifically allocated for AI initiatives?

Do you have a plan to scale successful pilots into broader deployment?

How well is ROI or impact from AI initiatives tracked and reported?

How prepared do you feel now about deploying AI successfully into your business?

Please rank these objectives for implementing AI for your business by priority, with 1 being the highest priority etc.

If you are considering implementing AI into your business, what type of initiatives you would want to implement?

Would you like a personalized AI Readiness Report or follow-up discussion?

Please Provide your Contact Details (Required.)

If you have any comments or questions - we would love to hear from you!
Thank you for your time.