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Evaluate your organization's readiness to adopt AI across five dimensions before investing in tools, vendors, or implementation.
Work through each dimension and check the items that accurately describe your organization today — not where you aspire to be. Items marked critical are the most important indicators of readiness. After completing each section, read the scoring note to understand what your results mean. Use the results to prioritize your AI readiness work before selecting tools or vendors.
AI systems are only as good as the data they run on. Before investing in AI tools, organizations need to understand the quality, accessibility, and governance of their data.
If you checked fewer than 4 items, data infrastructure is likely your most important readiness gap. AI tools will underperform or produce unreliable outputs without a solid data foundation.
AI works best when it automates or augments well-defined processes. Organizations with undocumented, inconsistent, or highly variable processes will struggle to get value from AI.
If you checked fewer than 4 items, process documentation should precede AI adoption. Automating a broken or undocumented process with AI typically amplifies the problem rather than solving it.
AI tools need to integrate with your existing technology. Understanding your current stack — and its limitations — prevents costly integration failures.
If you checked fewer than 4 items, a technology audit should be part of your AI readiness work. Many AI adoption failures stem from integration problems that were not identified until after vendor contracts were signed.
Technology adoption is a people problem as much as a technology problem. Organizations with low change readiness, AI skepticism, or poor internal communication will struggle to implement AI successfully.
If you checked fewer than 4 items, change management and internal communication should be prioritized alongside any technical AI work. The most common reason AI implementations fail is not the technology — it is the people.
AI adoption without strategic clarity leads to scattered investments, conflicting priorities, and difficulty measuring success. Organizations need to know why they are adopting AI before deciding how.
If you checked fewer than 4 items, strategy development should precede tool selection. Organizations that start with "what AI tools should we buy?" before answering "what problems are we trying to solve?" consistently underperform those that invest in strategy first.
Your checklist results point to where to focus before beginning AI adoption.
Your organization has a solid foundation for AI adoption. Focus on use case prioritization, governance framework development, and selecting the right tools for your highest-value opportunities.
Start with AI strategy developmentYour organization has meaningful gaps in one or more dimensions. Address the critical items in your lowest-scoring dimensions before investing in AI tools. A structured AI readiness assessment can help prioritize the work.
Start with an AI readiness assessmentYour organization has significant foundational work to do before AI adoption will deliver results. This is not a failure — it is a realistic starting point. Focus on data, process, and culture before technology.
Start with a discovery conversationThis checklist was developed by Melissa Barton, AI consultant and marketing strategist, based on her AI readiness assessment work with Florida businesses, nonprofits, and government agencies. It reflects the five-dimension framework she uses in formal AI readiness assessments.
For a formal AI readiness assessment with stakeholder interviews, technology audit, and a written report, contact Melissa directly.
A self-assessment checklist is a useful starting point. A formal assessment includes stakeholder interviews, technology audit, competitive benchmarking, and a written report with a prioritized roadmap.