AI Readiness Assessment

The problem

Most teams evaluate AI tools before they understand their own readiness. They buy on hype, implement against the grain of their operation, and stall. The gap is not ambition. It is an honest baseline.

What GT Axis does

We run a structured readiness review across five dimensions: data and systems, team and skills, process maturity, current AI usage, and leadership and budget. You get a clear picture of where you are strong, where you are exposed, and what to fix first.

What you get

• A readiness score and tier, with the reasoning behind it
• A dimension-by-dimension breakdown of strengths and gaps
• A prioritized, vendor-neutral path: what to fix, what to buy, what to leave manual

What you will understand afterward

• Where your operation is genuinely ready for AI and where it only looks ready
• Which of your workflows would produce a return first, and which would quietly fail
• What your data can actually support today, in plain language
• What to fix before spending a dollar on tooling, in what order, and why

Questions we answer

• Are we behind, or does it just feel that way?
• Our team already uses ChatGPT informally. Is that a strategy problem?
• A vendor quoted us five figures. Is that what this should cost?
• What would you do first in our seat?

Who this is wrong for

If you already have a data team, a working AI roadmap, and executive ownership, you do not need a readiness review; you need pressure-testing, and we would tell you that in the first call. If you want someone to validate a purchase you have already decided on, we are the wrong firm on purpose.