Stop Guessing Who's
AI-Ready,
Start Verifying it
Most enterprise AI programs measure logins and course completions, not capability. The iMocha AI Readiness Index replaces self-reported confidence with performance-based evidence, benchmarked role by role across your entire workforce.
Trusted by enterprise talent teams
Five Personas,
From Frontline to C-Suite
Course completions are a proxy. A conversation is proof. Every track below is validated through iMocha's AI Fluency Conversational Assessment engine and scored against anchored, task-specific rubrics, not self-reported checklists.
Adopter
Everyday, non-technical AI users
SIGNATURE CAPABILITIES
Generative AI Fluency · Responsible AI Use at Work
TARGET ROLES
Recruiters · Sellers · Marketers · Customer Ops · Finance · HR · Frontline Staff
Operator
Hands-on users applying AI to workflows
SIGNATURE CAPABILITIES
Applied Prompting for Business · AI-Assisted Workflow Design
TARGET ROLES
Product Managers · Project Managers · Business Analysts · Team Leads · Ops Managers
Builder
Technical creators building with AI
SIGNATURE CAPABILITIES
AI-Assisted Coding · Prompt Engineering for Developers
TARGET ROLES
Software Engineers · Solutions Architects · QA Engineers · Forward-Deployed Engineers
Architect
Advanced model & agent builders
SIGNATURE CAPABILITIES
Applied ML & Agentic Engineering · LLM Evaluation & Orchestration
TARGET ROLES
Data Scientists · ML Engineers · AI Platform Engineers · AI Modelers
Strategist
Executive, accountable AI leadership
SIGNATURE CAPABILITIES
AI Adoption for Leaders · AI Risk & Governance Stewardship
TARGET ROLES
Executives · Department Heads · CAIOs · CTOs · Compliance & Risk Leaders
Proof, Not Proxies
Real AI Tasks, Evaluated in Real Time
Two of the signature assessments behind the index, watch how candidates are put through actual AI work and not multiple-choice questions.
AI-Assisted Coding
Watch engineers build alongside AI in a live coding environment, scored on how well they direct, review, and refine what the model produces.
AI-Prompt Simulator
See candidates work through fixed workplace scenarios, scored across six prompt-writing dimensions on a 0-5 fluency scale.
See it in Action
See how the AI Readiness Index benchmarks AI fluency across all five personas. From frontline Adopter to executive Strategist, and turns a single assessment wave into a company-wide capability map.
Frequently Asked Questions
1. What is AI-readiness?
AI readiness is whether your workforce can actually apply AI to the work their roles require, not whether they've been trained or given access. It's a capability question, measured role by role, rather than a usage or logins question.
2. How is AI-readiness different from AI adoption?
Adoption measures activity like licenses, logins, course completions. Readiness measures demonstrated capability: can this person do the AI-related tasks their role actually demands.
3. Why aren't course completions enough to measure AI readiness?
Course completions confirm exposure, not competence. Someone can finish every module and still be unable to prompt well, spot a flawed output, or apply AI safely to real work.
4. Why measure AI-readiness by role instead of one company-wide test?
A recruiter, a product manager, and an ML engineer don't need the same AI fluency. A single test is either too shallow for technical roles or irrelevant for frontline staff, so readiness is scoped to what each role performs.
5. How does iMocha actually measure AI-readiness?
Through iMocha's AI Fluency Assessment engine, scored against anchored, task-specific rubrics - real task performance evaluated the way an expert reviewer would, not a multiple-choice quiz.
6. How quickly can we baseline AI-readiness across the organization?
It deploys as a single enterprise assessment wave, so a company-wide baseline comes back in weeks, then you drill into function, team, or geography with no heavy administrative lift.
7. What do we do once we know where the gaps are?
Readiness data feeds a closed loop: benchmark capability, close verified gaps with targeted upskilling through the learning tools you already use, then prove progress with scheduled re-assessment against the original baseline.