AI exposure, role by role.
Pick a role to see its operational AI cost, per-task substitution distribution, and where the work stays human — each number carrying its methodology version and confidence band.
Every role we've modeled in depth
These roles have a full capability-matrix read published today. More arrive as the matrix is recalibrated each month.
Customer Support Agent
operationsFront-line support IC. Handles tickets, live chat, account actions, and escalations, and de-escalates upset customers. The role where AI substitution pressure runs highest.
See the read →Data Analyst
analyticsTranslates business questions into SQL and visualizations. Owns dashboards, ad-hoc analyses, and the data definitions stakeholders cite in decisions.
See the read →Data Engineer
techDesigns and maintains data pipelines, warehouses, and infrastructure. Owns reliability, schema design, and orchestration for the data platform that analytics and ML teams depend on.
See the read →Financial Analyst
financeBuilds financial models, runs variance analysis, and partners with department leaders on budgets and forecasts. Owns the monthly close narrative for their domain.
See the read →Machine Learning Engineer
techBuilds, trains, evaluates, and ships ML models to production. Owns feature engineering, model serving infrastructure, and ongoing model performance monitoring.
See the read →Product Designer
designDesigns the end-to-end product experience. Bridges user research, interaction design, visual systems, and engineering handoff.
See the read →Product Manager
productOwns product direction, prioritization, and cross-functional execution. Translates research, data, and strategy into shipped product decisions.
See the read →Software Engineer
techDesigns, builds, and maintains software systems. Combines coding with system design, code review, and operational responsibility.
See the read →
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