Assess
Start with a baseline readiness score and role-specific gap map.
AIducation learning paths sequence the whole readiness loop for each role: baseline assessment, workflow practice, simulation, tool mission, mobile reinforcement, exit assessment, portfolio proof, and credential evidence.
Paths are the learner-facing sequence that turns platform primitives into a coherent readiness journey.
Start with a baseline readiness score and role-specific gap map.
Move through workflow labs, simulations, tool missions, and mobile micro-practice.
Attach artifacts, rubric evidence, and exit assessment results to a portfolio.
Turn completion into manager review, certification, and export-ready evidence.
Every path uses shared platform primitives while staying specific to the role workflow, tool stack, proof outputs, and manager evidence.
Practice customer conversations, verification, refund judgment, escalation, and policy-safe AI replies before agents use AI in live queues.
Establish a starting AI readiness score for support, cx, qa, and support operations teams.
Practice the core support workflow with AI in the loop.
Practice prospect research, outreach, discovery, CRM updates, negotiation prep, and follow-up workflows with AI coaching and sales-specific rubrics.
Establish a starting AI readiness score for sales, revenue, sdr, ae, and customer growth teams.
Practice the core sales workflow with AI in the loop.
Practice copy, content, campaigns, SEO, creative testing, brand review, and AI-assisted marketing workflows with measurable quality evidence.
Establish a starting AI readiness score for marketing, content, growth, lifecycle, brand, and creative teams.
Practice the core marketing workflow with AI in the loop.
Practice policy communication, recruiting workflows, performance review support, employee questions, and people analytics with privacy-aware AI rubrics.
Establish a starting AI readiness score for hr, people operations, recruiting, l&d, and managers.
Practice the core hr workflow with AI in the loop.
Practice AI-assisted analysis, forecasting, expense review, variance commentary, reporting, and spreadsheet workflows with calculation checks.
Establish a starting AI readiness score for finance, fp&a, accounting, revenue, and operations teams.
Practice the core finance workflow with AI in the loop.
Practice coding-agent use, code review, debugging, architecture critique, test generation, and verification habits with engineering-grade rubrics.
Establish a starting AI readiness score for engineering, platform, security, qa, and developer productivity teams.
Practice the core engineering workflow with AI in the loop.
Practice PRDs, research synthesis, roadmap planning, experiment design, launch review, and AI product risk assessment.
Establish a starting AI readiness score for product managers, product ops, research, and design partners.
Practice the core product workflow with AI in the loop.
Practice AI strategy, governance, rollout decisions, risk tradeoffs, operating model design, and ROI review for organization-wide adoption.
Establish a starting AI readiness score for executives, transformation leaders, cios, coos, and business unit leaders.
Practice the core executives workflow with AI in the loop.
Practice workflow automation, SOP generation, reporting, process analysis, and AI-assisted operating rhythms with role-specific quality checks.
Establish a starting AI readiness score for operations, process excellence, business ops, and service delivery teams.
Practice the core operations workflow with AI in the loop.