The best AI chatbot for customer service is one that resolves tickets - not one that deflects them to your human team. Only 14% of customer service issues are fully resolved by self-service tools today, per Gartner. Most chatbots are expensive FAQ pages. This guide compares what actually works.
Intercom Fin resolves 51-66% of queries on average at $0.99 per resolution - strong for mid-market
Zendesk AI charges $1.50-2.00 per resolution and fits best inside existing Zendesk environments
Ada starts around $30,000/year and targets enterprise volume with custom models
Lorikeet handles complex multi-step workflows across backend systems other tools escalate
If you manage support, you have seen the same vendor demo 15 times. The chatbot nails the easy ticket - shipping status, password reset. Then you deploy it, and 60-80% of real tickets hit a wall because they need order data, policy checks, and actions across 3 systems. We compare 6 platforms on resolution capability, pricing, and honest trade-offs.
What Should You Measure When Comparing AI Chatbots?
Measure resolution rate, not deflection rate. A resolved ticket means the customer's problem is fixed without a human stepping in. A deflected ticket means the bot answered something, but the customer still needs help. Most vendor dashboards blur this line.
Ask 2 questions: what percentage of conversations end with the issue fully resolved, and how do you define "resolved"? Intercom counts a resolution when the customer confirms or stops replying after 72 hours. Zendesk uses a similar inactivity window. A customer who gives up and calls your phone line still counts as "resolved" in many systems.
How Do the Top 6 AI Chatbots Compare on Price?
Pricing models vary wildly - per resolution, per conversation, per seat, or annual contracts. The sticker price almost never matches what you actually pay. Here is how 6 options break down.
Intercom Fin. $0.99/resolution on top of plans starting at $29/month. Average resolution rate around 51-66% across its customer base. Transparent, but costs scale linearly with volume.
Zendesk AI. $1.50/resolution (committed) or $2.00 (pay-as-you-go), on top of Suite plans from $115/agent/month. Best for existing Zendesk shops.
Ada. No public pricing. Starts around $30,000/year per their Salesforce AppExchange listing, but median buyers pay roughly $70,000/year per Vendr data.
Forethought. Quote-based. Blends platform fees with per-deflection costs. Best for teams wanting AI triage alongside resolution.
Tidio (Lyro AI). $29/month plus $39/month for AI add-on. Built for SMBs and Shopify - not designed for complex backend workflows.
Lorikeet. Purpose-built for multi-step CX workflows. Connects to backend systems to execute refunds, account changes, and policy lookups autonomously.
Which AI Chatbot Handles Complex Tickets Best?
Complex tickets require reading from and writing to backend systems - order management, billing, CRM. Most chatbots fail here because they were built for FAQ lookups, not workflow execution.
Intercom Fin and Zendesk AI handle moderate complexity well - knowledge base answers, product questions, basic account lookups. But when a ticket needs checking refund policy, verifying eligibility, processing the return, and confirming - that multi-step chain is where general-purpose tools escalate.
Lorikeet is built for this layer. It connects to your systems, follows your business logic, and executes full workflows. For CX teams in fintech or e-commerce where tickets touch 3-5 systems, that architectural difference determines whether AI handles 30% or 70% of volume.
What Resolution Rates Should You Realistically Expect?
Vendor marketing shows 80%+ resolution rates from cherry-picked case studies. Real-world averages are lower. Here is what the data shows without the outliers.
Intercom reports Fin's average resolution at 51-66% across 6,000+ customers, with the top 20% above 80%. Your results depend on knowledge source quality and ticket complexity. Tidio's Lyro works for scripted FAQ flows but drops off on anything requiring backend access. McKinsey research shows generative AI improves agent productivity by 14% in issue resolution per hour - but that depends on whether the AI resolves or merely assists.
How Do You Avoid Overpaying for AI That Underdelivers?
The biggest cost trap is paying per resolution for tickets that would have self-resolved anyway. If your bot "resolves" a password reset your help center already covers, you are paying $0.99-2.00 for zero incremental value.
Run a 30-day audit first. Categorize tickets into 3 buckets: simple FAQ, moderate (data lookup), and complex (multi-step actions). If 60%+ is simple, a better help center might be the right move. If complex tickets dominate, you need workflow execution - and pricing that reflects genuine resolution, not FAQ redirection.
What Questions Should You Ask in Every Vendor Demo?
Go beyond the polished script. These questions separate tools that resolve from tools that deflect - regardless of platform.
Show me a ticket that required 3+ system lookups and an action - not just an answer
What is your median resolution rate across all customers, not just top performers?
How do you define "resolution" - customer confirmation, timeout, or something else?
What happens when the AI is not confident - clean escalation or guessing?
Any vendor that dodges these is selling deflection. Tools built for complex tickets - like AI agents for customer service - welcome the scrutiny.
Key Takeaways
Only 14% of service issues are fully resolved by self-service today - most chatbots deflect, not resolve (Gartner)
Intercom Fin costs $0.99/resolution at 51-66% average; Zendesk AI charges $1.50-2.00/resolution
Complex multi-step tickets require backend system access most general-purpose chatbots lack
Audit your ticket mix before buying - 60%+ simple volume may not need an AI agent
Ask for median resolution rates across all customers, not cherry-picked case studies
The AI chatbot market is noisy and full of inflated metrics. If your team handles straightforward queries, a lighter tool or well-configured help center does the job. If tickets require multi-step actions across billing, orders, and account systems, you need workflow depth. Evaluate vendors against your hardest tickets, not your easiest. Run a 30-day audit, know your complexity mix, and demand median resolution data - not best-case showcases.
See how Lorikeet resolves complex multi-step tickets across backend systems. Explore Lorikeet's AI agent built for CX teams that need resolution, not deflection.
