What's actually automatable today across common business roles, no hype.
120 business roles analyzed across 10 departments · Refreshed June 2026
Data-driven insights from comprehensive role analysis
AI agents now plan and execute multi-step workflows across systems
62% of organizations are experimenting with AI agents and 23% are scaling one in at least one function (McKinsey, Nov 2025).
Tier-1 support, chat, voice, and QA roles all sit in the High Automation tier
Intercom Fin reports 67% average resolution; Agentforce claims 85%; voice agents now handle 60-87% of calls per vendor data.
Roughly two-thirds remain stuck in pilot mode (McKinsey, Nov 2025)
High performers rework their processes at almost 3x the rate of others. Capability is no longer the bottleneck — workflow redesign and governance are.
81 of 120 roles (2 in 3) have 40%+ of their tasks executable by AI agents today. Success depends more on workflow redesign, governance, and process standardization than on advanced AI capabilities.
Department-specific automation opportunities and recommended starting points
Transparent analysis framework for automation potential assessment
Breaking down each role into discrete, measurable tasks with complexity and frequency scoring.
Assessment of structured data inputs, decision rules, and outcome measurability for each task.
Regulatory, compliance, and risk factors that limit or require human oversight.
ROI = (Labor Time Saved + Error Reduction + Efficiency Gains) ÷ (Software + Implementation + Training Costs)
All estimates use conservative automation percentages and include full implementation costs.
Validation against McKinsey (2025), Gartner, WEF, and Ardent Partners research and real implementation data. Estimates are flagged separately from cited benchmarks.
Use our AI Readiness Scorecard and ROI Calculator to apply this methodology to your specific organization.
After download, get invited to a short briefing session to discuss implementation for your organization