The article argues that many businesses rush to adopt AI — deploying models or tools without first checking if they are truly ready. It proposes an “AI‑Readiness Audit” as a necessary first step: a systematic evaluation of a company’s infrastructure, data practices, governance and organizational culture to see whether AI adoption is realistic (and likely to succeed) or premature.
According to the article, an AI‑Readiness Audit examines multiple dimensions — including the clarity of business goals, the availability and quality of data, technical infrastructure (cloud, compute, pipelines), workforce skills and digital literacy, and organizational readiness to adapt workflows and governance for AI. Without this audit, companies risk building on shaky foundations: data silos, outdated systems, lack of alignment between teams — which often leads to failed implementations, wasted investment, or underwhelming returns.
The essay warns that the value of AI is not in the tools themselves, but in combining AI with sound processes, clean data and strategic vision. It argues that companies should first treat AI as a long‑term transformation project — not a quick add‑on — and invest in “readiness” before starting pilot projects. In that sense, the audit serves as a diagnostic and planning tool, helping organizations avoid hype‑driven mistakes and focus on where AI can genuinely add value.
Finally — in line with broader industry advice — the piece suggests that once readiness is assessed, businesses should create an actionable roadmap: define which use cases to pursue, upgrade data and infrastructure where needed, train or hire skills, and establish governance & compliance mechanisms. This foundational work, it argues, maximizes the chances of successful, sustainable AI adoption instead of superficial or risky experiments.
