Most failed AI projects fail before they start — not because the technology fell short, but because the business wasn't ready to absorb it. Five dimensions predict success.
Data: is the information your AI needs accessible and reasonably clean? Perfect data isn't required, but an agent grounded in outdated policy documents will confidently give outdated answers.
Process: are the workflows you want to automate actually defined? AI amplifies whatever exists — clarity or chaos. Documenting a process is often 40% of automating it.
Tooling: do your systems have APIs or integration paths? Modern SaaS stacks connect easily; legacy systems can too, but the blueprint must account for it.
Team and governance: is someone accountable for the outcome, and are the rules clear — what AI may access, what requires human approval, how performance is measured? Guardrails aren't bureaucracy; they're what lets you delegate confidently.
Score yourself honestly on all five. Strong on three or more? You're ready for a first project. Weaker? The audit that reveals your gaps is the same one that produces your roadmap.