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Tool · Benchmark

What is a realistic AI benchmark for your industry and where do you stand?

Pick your industry to see the realistic AI resolution rate and CSAT range — with the median and the top-10% world-class mark. Then see the four factors that decide where a given deployment actually lands.

Complexity
Low

Highest-volume intents — order status, returns, shipping — are structured and data-rich, so genuine resolution runs high.

Compare your numbers

Enter a value to place it on the scale.

Ecommerce & Retail

Genuine resolution and AI-handled CSAT, on a 0–100 scale.

AI resolution rate
0255075100
Range 7084%Median 76%Top 10% · world-class 93%
AI-handled CSAT
0255075100
Range 9095Median 92

Directional ranges synthesized from independent 2026 cross-program aggregates and field deployments — definitions of “resolution” vary by source, so treat these as a realistic target band, not an audited figure. See the full AI Customer Service Benchmark 2026.

See where your operation could land.

Book a working session — we will map these factors onto your real traffic and show you an achievable resolution and CSAT target.

What determines the benchmark

Industry sets the range. Three things decide where you land.

Your industry fixes the ceiling and the shape of the range above. Whether a specific deployment sits near the median or pushes toward the world-class mark is decided by the next three factors — all within your control.

01

Industry — complexity

The intrinsic difficulty of your intents — how ambiguous, regulated, emotional, or multi-step they are. This sets the ceiling: structured, data-rich intents resolve high; ambiguous or regulated ones resolve far lower, no matter the vendor.

02

System capability

How capable the AI platform is — multi-agent reasoning, backend actions, retrieval, and guardrails. A stronger system reaches higher within the same industry band and holds quality as complexity rises.

03

Maturity of assets & playbooks

The quality of your knowledge base, SOPs, and escalation rules. New deployments launch near 40–50% and climb past 60% over 6–12 months as assets and playbooks mature.

04

Transparency of data

How accessible the data and systems needed to resolve a ticket are. When the AI can see orders, accounts, and history, it resolves; when data is siloed or missing, even simple intents stall.