# Is there an AI readiness checklist you can use yourself? URL: https://ergostrat.com/en/ai-readiness-assessment/ai-readiness-checklist.html Language: [Български](https://ergostrat.com/ai-readiness-assessment/ai-readiness-checklist.html) · [English](https://ergostrat.com/en/ai-readiness-assessment/ai-readiness-checklist.html) · [Français](https://ergostrat.com/fr/ai-readiness-assessment/ai-readiness-checklist.html) · [Deutsch](https://ergostrat.com/de/ai-readiness-assessment/ai-readiness-checklist.html) Yes. Public checklists can organise questions about data, processes, tools and people. Checkmarks record your answers; they do not by themselves certify technical or legal readiness for a particular task. ## Which categories can you check yourself? Pro-How’s GitHub repository organises questions into five areas. You can start with these, recording evidence or missing information alongside the answers: - Data and information: where is current information and who maintains it? - Processes and documentation: are steps and exceptions described? - Tools and software: what do you use and how can it connect if needed? - Team and culture: who will use the change and what help do they need? - Goals and expectations: which task do you want to improve and how will you check the outcome? Pro-How defines its own percentage categories: 90–100% for starting implementation, 70–89% for closing gaps, 50–69% for groundwork and below 50% for basic conditions. These are provider definitions, not independently confirmed readiness thresholds or certification. A high overall score does not remove a particular problem with access, quality or data use. ## What are Amazon Web Services’ five steps? AWS’s guide for small and medium businesses proposes these steps, briefly paraphrased here: - Data: record sources, owners, updating and access rights. - Use: choose a bounded task with a checkable outcome and human review. - Technology: check necessary connections, permissions and current systems’ limits. - Governance: record rules for privacy, protection and output review. - Measurement: define a baseline, metric and quality check. AWS suggests a 30–60 day pilot and an illustrative 6–8 week readiness sprint. This is a provider plan, not a measured standard for every business or a deadline for the AI Opportunity Map. All data does not have to move into one system. APIs or webhooks concern necessary integration; they are not a condition of every possible AI use. ## Which nine topics offer a closer look? RTS Labs covers nine dimensions. Use these as discussion topics suited to your size and task: - Strategy: connection to a particular business objective. - Data: availability, quality and context. - Infrastructure: resources and protection needed. - Skills: knowledge and people responsible. - Governance: applicable rules, accountability and controls. - Change: learning, adoption and ways of working. - Finance: budget, costs and a benefit criterion. - Process: AI’s place in daily work. - Maintenance: monitoring, changes and expansion. These topics do not mean every small business must hire a machine learning team or buy a new cloud environment. Check what the chosen use needs. A list of desired conditions is not evidence that those conditions have been met. ## What needs checking beyond the boxes? A checklist can also help with priorities. For a decision in your business, however, connect answers to particular work: - Is the data sufficient for this task, including difficult cases? - Which tasks cost time, what benefit do you seek and what constrains delivery? - Are there undocumented workarounds to discuss with the people doing the work? Record what is established by an example and what is assumed. A conversation may clarify gaps; it does not find them automatically just because someone external is involved. You need a checkable method and evidence appropriate to the scope. ## Questions ### Is a checklist useful before speaking to a consultant? Yes. Mark what is known, what is unclear and the source of important answers. The conversation can then start with particular questions. Completing a checklist does not oblige you to buy consulting or implementation. ### Which of the three checklists should we choose? You can use AWS’s five steps for a short start. Pro-How organises questions by operational area, while RTS Labs offers a broader set of topics. Choose for the task and the people answering; no one option is established as best for every small business. ### Does a checklist replace a professional assessment? Self-assessment and independent checking are different. Ask what evidence is reviewed, what limits the method has and what falls outside scope. Neither an overall percentage nor a paid conversation alone establishes readiness. ## Sources - [AWS — AI readiness checklist for small and medium businesses.](https://aws.amazon.com/smart-business/resources-for-smb/ai-readiness-checklist/) - [Pro-How — small business readiness questions on GitHub.](https://github.com/pro-how-ai/small-business-ai-readiness-checklist) - [RTS Labs — nine dimensions of AI readiness.](https://rtslabs.com/ai-readiness-checklist) ## Related reading - [Is your data good enough for AI?](https://ergostrat.com/en/ai-readiness-assessment/data-ready-for-ai.html) - [Readiness assessment through European Digital Innovation Hubs.](https://ergostrat.com/en/ai-readiness-assessment/edih-free-assessment.html) - [Can you trust free online readiness tests?](https://ergostrat.com/en/ai-readiness-assessment/free-ai-readiness-tests.html) ## Connect the gaps identified to the order of tasks. The AI Opportunity Map orders tasks by the hours they cost you today; for the first three it gives a proposed tool, requirements, an owner and a build-effort range in hours, without a build price. A completed checklist can prepare you for the conversation. The result is a prioritised task list, not readiness certification or a promise of implementation. [Ask about the AI Opportunity Map](mailto:contact@ergostrat.com?subject=AI%20readiness%20checklist%20and%20Opportunity%20Map%20question)