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AI Readiness Checklist

A practical self-assessment tool to evaluate your organization's preparedness for AI adoption. Use this checklist to identify gaps, prioritize actions, and build your AI transformation roadmap.

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Leadership & Strategy

Leadership team understands AI's potential and limitations
High Priority
[HIGH]
Leaders should have a realistic understanding of what AI can and cannot do. Consider organizing executive briefings or workshops to build foundational knowledge.
Score:
0
1
2
3
Clear AI vision aligned with business strategy
High Priority
[HIGH]
Your AI vision should directly support business objectives. Document how AI initiatives connect to revenue, efficiency, or customer experience goals.
Score:
0
1
2
3
Budget allocated for AI initiatives
High Priority
[HIGH]
Dedicated budget shows commitment. Start with pilot funding, then scale based on results. Consider both technology costs and training investments.
Score:
0
1
2
3
AI champion or sponsor identified
High Priority
[HIGH]
A senior sponsor helps remove barriers and provides visibility. This person should have decision-making authority and genuine interest in AI transformation.
Score:
0
1
2
3
Success metrics defined for AI projects
Medium Priority
[MEDIUM]
Define measurable outcomes before starting. Examples: time saved, error reduction, customer satisfaction scores, or revenue impact.
Score:
0
1
2
3

Team Capability

Team members have basic AI literacy
High Priority
[HIGH]
Basic literacy means understanding AI concepts, use cases, and limitations. Start with company-wide training or lunch-and-learns.
Score:
0
1
2
3
Key staff trained on AI tools (Copilot, ChatGPT, etc.)
High Priority
[HIGH]
Hands-on training is essential. Focus on tools your organization uses or plans to adopt. Provide practice time and real-world examples.
Score:
0
1
2
3
AI experimentation encouraged and supported
Medium Priority
[MEDIUM]
Create a safe space for trying AI tools. Consider a 'sandbox' environment or dedicated time for experimentation without pressure.
Score:
0
1
2
3
Knowledge sharing mechanisms in place
Medium Priority
[MEDIUM]
Set up channels for sharing AI wins, tips, and learnings. This could be Slack channels, monthly showcases, or internal wikis.
Score:
0
1
2
3
Cross-functional AI working group exists
Low Priority
[LOW]
A working group helps coordinate efforts across departments. Include representatives from IT, business units, and leadership.
Score:
0
1
2
3

Technology & Infrastructure

AI tools evaluated and selected
High Priority
[HIGH]
Evaluate tools based on your specific needs, security requirements, and integration capabilities. Start with tools that solve immediate problems.
Score:
0
1
2
3
Data quality and accessibility assessed
High Priority
[HIGH]
AI needs quality data. Assess data cleanliness, completeness, and accessibility. Identify data gaps that could limit AI effectiveness.
Score:
0
1
2
3
Security and privacy policies updated for AI
High Priority
[HIGH]
Update policies to address AI-specific risks: data handling, model outputs, third-party tools, and compliance requirements (GDPR, etc.).
Score:
0
1
2
3
Integration points with existing systems identified
Medium Priority
[MEDIUM]
Plan how AI tools will connect with your current tech stack. Consider APIs, data pipelines, and workflow integrations.
Score:
0
1
2
3
Technical support available for AI tools
Medium Priority
[MEDIUM]
Ensure users have help when they need it. This could be internal IT support, vendor support, or designated AI champions.
Score:
0
1
2
3

Governance & Risk

AI usage policies and guidelines established
High Priority
[HIGH]
Clear policies prevent misuse and set expectations. Cover acceptable use, data handling, output review, and escalation procedures.
Score:
0
1
2
3
Ethical AI principles defined
Medium Priority
[MEDIUM]
Define your organization's ethical stance on AI. Consider fairness, transparency, accountability, and human oversight.
Score:
0
1
2
3
Risk assessment framework in place
Medium Priority
[MEDIUM]
Assess risks for each AI use case: accuracy, bias, security, compliance, and business impact. Document mitigation strategies.
Score:
0
1
2
3
Compliance requirements understood
High Priority
[HIGH]
Understand industry-specific regulations (healthcare, finance, etc.) and general data protection laws that apply to your AI use cases.
Score:
0
1
2
3
Data governance aligned with AI needs
Medium Priority
[MEDIUM]
Ensure data governance processes support AI initiatives. This includes data access, quality standards, and lifecycle management.
Score:
0
1
2
3

Culture & Change Management

Change management plan for AI adoption
High Priority
[HIGH]
Plan for resistance and support. Include communication strategy, training timeline, and support mechanisms for teams adapting to AI.
Score:
0
1
2
3
Communication strategy for AI initiatives
Medium Priority
[MEDIUM]
Regular communication builds buy-in. Share progress, wins, and learnings. Address concerns transparently and celebrate early adopters.
Score:
0
1
2
3
Feedback mechanisms for AI concerns
Medium Priority
[MEDIUM]
Create channels for employees to voice concerns, ask questions, or report issues. This builds trust and helps identify problems early.
Score:
0
1
2
3
Recognition programs for AI champions
Low Priority
[LOW]
Recognize and reward employees who successfully adopt AI or help others. This encourages experimentation and knowledge sharing.
Score:
0
1
2
3
Learning culture that supports experimentation
Medium Priority
[MEDIUM]
Foster a culture where trying and learning from AI is valued. Emphasize learning over perfection and share failures as learning opportunities.
Score:
0
1
2
3

Measurement & ROI

KPIs defined for AI initiatives
High Priority
[HIGH]
Define key performance indicators before launching. Track both quantitative metrics (time saved, cost reduction) and qualitative ones (user satisfaction).
Score:
0
1
2
3
Baseline metrics established
High Priority
[HIGH]
Measure current state before implementing AI. This allows you to quantify improvements and demonstrate ROI.
Score:
0
1
2
3
Tracking mechanisms in place
Medium Priority
[MEDIUM]
Set up systems to track AI usage, outcomes, and impact. This could be dashboards, surveys, or regular reporting processes.
Score:
0
1
2
3
ROI measurement framework ready
Medium Priority
[MEDIUM]
Calculate ROI by comparing costs (tools, training, time) to benefits (efficiency gains, revenue impact, quality improvements).
Score:
0
1
2
3
Regular review cadence scheduled
Low Priority
[LOW]
Schedule regular reviews (monthly or quarterly) to assess progress, adjust strategies, and share learnings across the organization.
Score:
0
1
2
3

Next Steps

This checklist helps you build a detailed action plan. For a quick diagnostic of where your organization stands today, start with our 2-minute AI Readiness Assessment to get instant insights, then use this checklist to create your implementation roadmap.

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AI Readiness Checklist

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