Eqwitty AI ReadinessAI readiness assessment for technology companies
Technology companies often assume they are AI-ready because their engineers use AI tools. The diagnostic separates that from the harder questions: is AI inside the product customers pay for, is there a repeatable path from prototype to a reliable feature, and is the organization measuring the return on AI investment or just the activity.
The technology version of the diagnostic frames use-case, model-management and infrastructure questions around product and engineering realities rather than back-office ones.
Where AI value shows up first in technology
Returns in this sector show up first in AI-assisted engineering, AI features that lift retention or expansion revenue, support deflection, and internal knowledge and workflow automation.
How the questions change for technology
These questions are asked in the technology edition instead of the standard wording. The pillar, section and scoring are pinned, so your score stays comparable with organizations in other industries.
- Organization & CultureHow much of your software team uses an AI coding assistant every day — and do you actually track whether it helps?An AI coding assistant (like GitHub Copilot) suggests and writes code as engineers type. This asks about tracked, real usage — not how many licences you bought.Answer options are rewritten for this industry, from “Not rolled out yet” to “Everyone, with usage and a measured impact on output”.
- Organization & CultureIn the last year, how many of your senior AI specialists left?"Senior" = someone whose departure stalled, slowed, or shrank an AI project. For tech firms, keeping these people is often the number-one bottleneck.Answer options are rewritten for this industry, from “Three or more” to “None”.
- AI Strategy & ExperienceIn the last year, has AI noticeably changed any of your products — and is AI part of how you sell them?Tech firms that build AI features but never mention AI in their sales pitch tend to leave money on the table.Answer options are rewritten for this industry, from “No” to “AI is the main reason customers choose us, and it shapes our pricing”.
- AI Strategy & ExperienceHow well does your organization use generative AI — both inside the company (helping staff work faster) and in the product customers use?Generative AI creates new content — text, images, code — like ChatGPT. Tech firms often use it heavily inside the company; the real test is whether it also shows up in what customers use.Answer options are rewritten for this industry, from “We're not using it” to “A company-wide setup, with our own tailored models powering several products”.
Pillars this edition emphasizes
All nine pillars are scored for every organization. These are the ones where the technology edition changes what is asked.
One scoring model, comparable across industries
The industry edition changes wording, examples and answer options, never the maths. Every organization is scored on the same nine weighted pillars and lands in one of the same five levels, which is what makes peer benchmarks meaningful. The full method is on the methodology page.
Other industry editions
Find out where you stand
A 15-minute diagnostic, then your nine-pillar score, peer benchmarks and a 90-day plan you can act on Monday. One-time payment of CA$19.80 per report.