Guide
Are you ready for AI? Part 1 of 2
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In this guide we cover
The failure is usually organizational, not technical.
Roughly 80% of AI projects fail by some estimates, about twice the rate of comparable non-AI IT work. What is specific to AI is the content it reads from, the process it plugs into and the expectations set before it arrived. All three are within your control to assess before you buy.
Four pillars decide whether your data is ready.
Content integrity, accessibility, process maturity, and governance and ownership. Your lowest pillar governs, because automation scales whatever you give it, weaknesses included.
Your readiness diagnosis is your leverage in an evaluation.
It turns a vague feature comparison into pointed vendor questions, and in regulated environments the hard constraints, authorization level, flowdown, model and data handling terms, decide the shortlist before fit ever enters the conversation.
Score yourself before you shop.
Appendix A is a 25-statement assessment across the four pillars, plus an expectations gate that works as a pass or fail rather than a gradient. The output is not a grade. It is a decision about what to do next and in what order, and it becomes your measurement baseline for Part 2.
