Industry benchmarks by workflow type
Across industries, the best candidates for automation tend to be repetitive, cross-system workflows with delays, handoffs, and exceptions. Here is what the data says - and where to start.
Cross-functional benchmarks
Cross-industry data on time saved, error reduction, and ROI speed. Use these to set expectations with finance - then scope one workflow to test the thesis.
171%
average ROI companies expect from autonomous agents that reach production
Expectation from a buyer survey, not a realized average - US firms expect ~192%
Source: PagerDuty, 2025
66%
of organizations report productivity and efficiency gains from enterprise agents
Deloitte, State of AI in the Enterprise, 2026 (3,235 leaders surveyed)
Source: Deloitte, 2026
30%+
of activities across roughly 60% of occupations could be automated with current technology
McKinsey Global Institute estimate of technical automation potential
Source: McKinsey Global Institute
Workflow types we deploy most often
The best candidates share a pattern: repetitive work, multiple systems, exceptions that need a human, and a clear owner who can sign for production.
Accounts payable / invoice exceptions
Invoice mismatches, duplicate detection, approval routing, and reconciliation status updates.
Support triage / ticket routing
Classification, enrichment, escalation, and routine request resolution inside your helpdesk.
Claims / approvals
Triage, document handling, policy context, and approval routing with human review.
Document processing
Intake, data extraction, completeness validation, and routing of documents that pile up.
Operations handoffs
Work that spans ERP, CRM, ticketing, and email - where the handoffs are the bottleneck.
Back-office workflows
Vendor onboarding, PO matching, employee onboarding, and reporting across systems.
The same pattern shows up in every industry
Repetitive work, multiple systems, exceptions that need a human, and a clear owner. If your workflow matches this, it is a strong candidate - whatever industry you are in.