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C4 AI Maturity & Readiness Survey

Welcome! Let’s assess your organization’s AI Journey

This assessment will help you understand your AI maturity and readiness across key dimensions. All responses are confidential. (*) indicates required.

About You

Full Name *

Company Name / Industry *

Your Role / Function *

Company Email *

Section 1 - Organization Readiness

How clearly defined and operational is your AI strategy? *Fully defined, funded, and actively executed.Defined, but execution is inconsistent.Early-stage exploration, not yet formalized.No formal strategy.

Who currently owns AI strategy and execution? *Dedicated AI Centre of Excellence or Office of AI.Dedicated leader or team within a function.Decentralized ownership.No formal dedicated ownership.

Who champions or advocates for AI in your company?Select all that applyCEO/BoardCIO/CTOBusiness unitsInnovation/Data teamOther

Section 2 - Buy-in, Prioritization & Risk

How would you rate executive and business unit support for AI? *Actively supporting with budget and resourcesLeadership interest but limited fundingDepartment-level onlyMinimal or skeptical

What is the organization's timeline and urgency for AI adoption? *Immediate (0-3 months)Near-term (next 4-12 months)Long-term (>12 months)No defined timeline

What is your organization’s risk tolerance for AI adoption? *High: Willing to experiment, accepts moderate riskMedium: Cautious, only proven use casesLow: Reluctant, concerned about risks and compliance implicationsUndefined: No stance yet

How are AI initiatives currently prioritized and resourced? *Formal prioritization with budget, staffing, and governancePrioritized but inconsistently resourcedAd hoc prioritizationNo prioritization framework

Section 3 - Data & Technical Foundations

How are AI tools used today? *Embedded into workflowsUsed for experimentation and prototypingIndividual use for productivity onlyNot in use

How would you rate your organization’s data quality/readiness for AI? *High quality, accessible, integrated, well-governedModerate, gaps in consistency/integrityFragmented or siloedLittle usable data

How easily can AI tools integrate with your existing systems and workflows? *Mature integration architecture and APIsModerate; some integration possible with effortLimited; systems are siloedVery difficult; legacy or fragmented systems

What is your status on data governance and privacy? *Consistent policies, dedicated oversight, regular auditsPartial/growing attentionAd hoc or informal processesNo data policies in place

How mature is your process for deploying and managing AI models in production? *Fully Automated (MLOps): Automated pipelines for deployment, performance monitoring, and model rollback are standard.Managed Process: Models are deployed manually but are continuously monitored for performance, drift, and bias.Manual/Ad-Hoc: Deployment is manual and monitoring is limited to basic performance checks at launch.Not Applicable: We do not have any AI models in production.

Do you have formal data stewardship and ownership assigned to key data assets used for AI? *Fully Implemented: Data owners, stewards, and documented data lineage are formally established for all AI data.In Progress: Stewardship roles are being defined, and data cataloging efforts are underway.Ad-Hoc: Data is accessed based on project needs; ownership and lineage are undocumented.No Formal Program: Data ownership is not defined or tracked.

Section 4 - AI Use Cases & Value

How clearly defined are your AI use cases? *Clear, prioritized, and aligned with measurable business outcomesSome ideas but not yet prioritizedConceptual onlyNo defined use cases

How do you expect AI to deliver value?(select up to 2)Revenue growthCost reductionCustomer experience and satisfactionProductivity/automationRisk reduction and increased complianceOther

Section 5 - People, Skills & Culture

How would you rate your staff’s AI literacy and use overall? *Advanced – designing, deploying, and adapting custom AI/LLM solutions with automation, integrations, or self-built modelsIntermediate – integrating AI tools into core workflows, customizing with advanced prompts or scriptsCompetent – confident, regular users of AI tools; modifying out-of-the-box solutions to fit needsNovice – basic use of LLMs with minimal prompt engineeringNone – little to no exposure or practical use of AI tools

What AI education/training is provided to your employees?Structured, ongoing with learning pathsOccasional/introductory onlyPeer-to-peer/informalNone at present

How would you describe your organization’s culture toward AI-driven change?Embraces experimentation and continuous improvementGenerally supportive but change fatiguedMixed attitudes; pockets of resistanceResistant to change / skeptical of AI

How integrated is systematic change management into your AI adoption plans?Fully Integrated: A formal change management plan, dedicated resources, and upskilling are mandated for all AI rollouts.Partially Integrated: Change is addressed mainly through internal communication and basic training, but without a formal plan.Ad-Hoc/None: Adoption is left to individual teams; no standardized organizational change management framework for AI.

Section 6 - Ethics, Governance, & Accountability

Do you have an organizational policy regarding the use of public/external GenAI tools (e.g., ChatGPT, Gemini, Claude) by employees?Approved for internal use with corporate-licensed, secured versions (e.g., Copilot, enterprise LLMs).Permitted for some uses but strictly forbidden from inputting proprietary or sensitive data.Officially discouraged or banned due to security/privacy concerns.No official policy or guidance has been issued.

Does your organization have clear AI policies for ethics, fairness, and bias?Yes, formal policy and oversightDeveloping formal policiesInformal guidelinesNo guidelines

Section 7 - AI Maturity Benchmarking

Self-assess your organization's overall AI maturity: *Level 5 – Leading (AI as core capability, strategic advantage, industry benchmark)Level 4 – Optimizing (enterprise-wide, measured outcomes, continuous improvement)Level 3 – Scaling (proven use cases, expanding adoption, addressing governance)Level 2 – Developing (isolated use, some cross-team interest)Level 1 – Exploring (early awareness, pilots only)

Final Reflections

What is the single need for your AI efforts in the next 3–6 months? (Clarity, Skills, Momentum, Scale)

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