Best AI Chatbot for Business: What I'd Actually Buy

Full disclosure: I work at Open, so I'm biased. I'll try to be fair about competitor strengths, and I'll be honest when I think we're not the right fit. Take everything with appropriate skepticism.

That said, I've evaluated pretty much every AI chatbot on the market—both as a builder and as someone who talks to support leaders every week. Here's what I actually think.

The Uncomfortable Truth About This Market

Most "AI chatbots" are not what you think they are.

When ChatGPT came out, every chatbot company slapped "AI-powered" on their marketing. Some actually rebuilt their tech. Most just added GPT to generate slightly better canned responses from the same old decision trees.

Here's what I mean:

Old-school chatbot (now called "AI"): Customer says something → system matches keywords or detects "intent" → retrieves pre-written response. Maybe GPT polishes the wording. But it's still fundamentally retrieval, not generation. These top out at 25-40% automation because they can't handle anything they weren't explicitly trained for.

Actual generative AI: Customer says something → LLM understands the meaning → generates a response using your knowledge base as context → can reason through novel questions. These achieve 60-80% automation because they can handle questions they've never seen.

The marketing all sounds the same. The results are dramatically different.

What Actually Matters When Choosing

Ignore feature checklists. Here's what actually determines whether a chatbot will work for you:

1. Resolution Rate, Not Deflection Rate

Every vendor will tell you their "deflection rate" or "containment rate." These metrics are meaningless, sometimes actively misleading.

Deflection just means "customer didn't create a ticket." Did they get their problem solved? Or did they give up, find the answer elsewhere, or just churn quietly? Deflection doesn't tell you.

Ask for resolution rate: What percentage of conversations does the AI actually resolve—verified by customer not coming back with the same issue, or explicit confirmation?

A chatbot that "deflects" 80% but only resolves 30% is worse than one that deflects 50% but resolves 50%. The first one is just frustrating customers into silence.

2. Your Specific Use Cases

"Best AI chatbot" depends entirely on what you're trying to do:

E-commerce (orders, returns, product questions): You need fast setup, Shopify/order system integration, and handling of transactional queries. Resolution rate matters more than advanced AI because most questions are simple.

SaaS (technical support, how-to, troubleshooting): You need deep knowledge base integration and ability to handle technical complexity. The AI needs to actually understand your product, not just match keywords.

Enterprise (compliance, multi-brand, complex routing): You need security certifications, audit trails, and customization. "Easy setup" matters less; "handles our complexity" matters more.

A chatbot that's perfect for a DTC brand selling t-shirts is wrong for a fintech handling sensitive financial data. There is no universal "best."

3. Total Cost of Ownership

Pricing in this market is designed to confuse you. Here's what to watch for:

Per-seat pricing: Looks cheap until you realize you're paying per agent seat PLUS per resolution. A $99/seat platform with $0.99/resolution costs way more than it appears.

Per-MAU pricing: Sounds reasonable until your marketing campaign goes viral and suddenly you're paying for thousands of "users" who never even talked to the chatbot.

Per-resolution pricing: Clearest model. You pay when AI actually resolves something. But watch the definition of "resolution"—some vendors count any ended conversation as resolved.

Enterprise custom: "Contact us for pricing" usually means $50k+ minimum. Sometimes worth it, sometimes just a sales tactic to lock you into a call before showing you can't afford it.

4. Integration Depth

A chatbot that can answer "what's your return policy" but can't actually process a return is only half-useful. The magic happens when AI can take actions:

• Check order status in Shopify
• Process refunds
• Update account details
• Create tickets with proper categorization
• Escalate to the right team with full context

Ask about integrations, but more importantly, ask: "What can the AI actually DO, not just say?"

The Platforms I'd Consider

Not an exhaustive list—just the ones I think are worth your time depending on your situation.

Open (yes, we build this)

I obviously believe in what we're building, or I wouldn't be here. What we focus on:

We built for resolution, not deflection. Our AI doesn't just answer questions—it takes actions. Process refunds, check orders, update accounts. When it can't resolve something, it hands off to humans with full context so they're not starting from scratch.

We charge per resolution ($0.99), not per seat or per MAU. You pay when we actually help your customers, not for usage that doesn't deliver value.

We work across channels—same AI for chat, email, voice, WhatsApp. Most platforms are chat-only and bolt on other channels awkwardly.

Best for: Teams wanting high automation (60-80%) with simple per-resolution pricing and true omnichannel.

Not great for: If you're already deep in another ecosystem (committed Intercom customer, Zendesk enterprise, etc.) and don't want to migrate. Also, we're still building out some enterprise features.

Intercom Fin

If you're already on Intercom, Fin is good. It's genuinely AI-native (not just bolted on) and integrates deeply with Intercom's product.

The catch: you need Intercom. Fin + Intercom seats gets expensive fast, especially for larger teams. And you're locked into the Intercom ecosystem.

Best for: B2B SaaS companies already on Intercom who want to add AI without changing platforms.

Not great for: Teams not on Intercom, or those who find Intercom pricing hard to stomach.

Zendesk AI Agents

Enterprise-proven, works if you're committed to Zendesk. But AI feels like an add-on rather than core to the product. Setup is complex, pricing is layered, and automation rates tend to be lower than dedicated AI-first platforms.

Best for: Large enterprises already invested in Zendesk who need to add AI incrementally without ripping out their stack.

Not great for: Anyone who doesn't already love Zendesk. The complexity isn't worth it if you're starting fresh.

Tidio

Good budget option for small e-commerce. Won't give you 70% automation, but it's affordable and easy to set up. Works well for simple use cases.

Best for: Small Shopify stores with limited budget who want basic automation.

Not great for: Anyone needing sophisticated AI, complex integrations, or enterprise features.

Ada

Serious enterprise platform. Good automation, handles complex multi-brand setups, proper security and compliance. But expensive and implementation takes months.

Best for: Large enterprises with complex requirements and budget to match.

Not great for: Anyone who wants quick deployment or doesn't have $100k+ budget.

How to Actually Evaluate

Don't trust demos. Demos are always perfect. Here's what to do instead:

1. Get a trial with real traffic. Send real customer conversations to the AI. See what it actually handles. Many platforms will set up a limited pilot—push for this.

2. Check the edge cases. Don't test with easy questions. Try the weird ones your team struggles with. Try angry customer scenarios. Try multi-part questions.

3. Test the handoff. When AI can't handle something, what happens? Does the human get full context? Is it seamless or jarring for the customer?

4. Calculate true cost. Get a quote based on YOUR volume, YOUR expected automation rate, YOUR team size. Don't rely on marketing pricing pages.

5. Talk to current customers. Ask the vendor for references in your industry. Ask those references: What's the real automation rate? What problems did you hit? Would you buy again?

What I'd Do in Your Shoes

If I were buying an AI chatbot today (and didn't work at Open):

Small team, simple needs, tight budget: Start with Tidio or similar. Get basic automation working. Graduate to something more sophisticated when volume justifies it.

Growing team, e-commerce or SaaS: Look at Open (obviously), Intercom Fin (if already on Intercom), or similar AI-first platforms. Prioritize resolution rate and integration depth over feature lists.

Enterprise, complex requirements: Ada, Zendesk AI, or Open (we're getting there). Plan for longer evaluation and implementation. Get procurement and security involved early.

The worst thing you can do is buy based on marketing promises and hope it works. Test with real traffic. Measure real resolution. Make decisions based on evidence, not demos.

Yes, I want you to consider Open—I believe in what we're building. But more than that, I want you to make a good decision. The right AI chatbot genuinely transforms support operations. The wrong one is expensive shelfware.