UBIKON.ioAI Readiness Assessment
12 questions across data, process, team and use-case value — including the honest answer if you don't need AI yet.
No email required for results.
Question 1 of 12
How this is scored
Each of 12 questions scores 0-3 across four axes: data readiness, process clarity, team capability, and use-case value. A low use-case-value score triggers the honest branch — telling you a simpler, non-AI fix may solve most of the problem, which most vendors selling AI work won't say.
Straight answers
What people ask about AI readiness
What does an AI readiness assessment actually measure? +
Three things: whether you have data worth applying AI to, whether a workflow exists that AI could shorten, and whether the result would be measurable. Most businesses fail on the second — they have data but no repetitive, high-volume decision that a model would improve. The assessment is designed to tell you that plainly rather than recommend a project.
Do I need a lot of data to use AI? +
No, and this is the most common misconception. Retrieval-augmented generation works on hundreds of documents, not millions of rows — a support knowledge base, a product catalogue or a set of policy PDFs is usually enough. What genuinely needs volume is training a custom model, which almost no business actually needs; using a frontier model such as Claude against your own content does not.
What if the assessment says I am not ready? +
Then you have saved a five-figure budget, which is the point. The most common honest outcome is that a specific workflow should be fixed or instrumented before any AI is added, because AI applied to a broken process makes it fail faster. If that is the finding, you will get it here rather than after a discovery phase.
How long does an AI project take once we start? +
AI integration into an existing product runs 3-8 weeks and $8k-$35k. A full RAG pipeline over your own data or a multi-step agent workflow runs 4-16 weeks and $10k-$70k depending on retrieval complexity and how many tools the agent needs. Both figures come from delivered projects, not estimates.