Comprehensive market map of AI support vendors in 2026 — funding, pricing, ideal customers, and key differentiators for each.
Honest analysis of AI support implementation timelines — what determines speed and how to plan for your team's deployment.
Data-driven analysis of AI escalation failures — what good handoffs look like and how to evaluate escalation quality across vendors.
How the AI support market is bifurcating — enterprise platforms at $95K+ and a new wave serving the 90% of teams priced out.
The definitive buyer's checklist for AI support — 15 questions on pricing, quality, escalation, and security with good/bad benchmarks.
Deep dive into AI quality assurance — self-evaluation, post-hoc QA, multi-model validation, and what 'good' looks like for accuracy.
Practical guide to AI support integration — native apps, APIs, browser extensions, and whether you need to switch helpdesks.
Framework for choosing between managed and self-serve AI support deployment — staffing, time-to-value, and maintenance tradeoffs.
A CX leader's guide to AI support pricing models — per-ticket, outcome-based, seat-based, and hybrid — with real cost comparisons.
Beyond license fees — implementation, engineering, training data, integration, and QA costs that inflate your AI support budget.
Why most AI support vendors hide pricing, what typical contract ranges look like, and 7 questions to ask during procurement.