Does Zendesk use OpenAI? The full 2025 story

With all the buzz around AI, it’s a question we hear all the time: are the big players like Zendesk actually using tools like OpenAI? The short answer is yes, they are. But that’s really just the beginning of the story, and it’s one that comes with a fair share of limitations.

This guide will break down exactly how Zendesk uses OpenAI, walk through the good and the bad of its built-in approach, and touch on the surprisingly messy path of trying to build your own integration. Most importantly, we’ll show you a much more flexible way to bring powerful AI into your Zendesk workflow without getting boxed in.

How Zendesk uses OpenAI: The official partnership

Zendesk has an official partnership with OpenAI that they announced to beef up their AI features for customer support. But before you assume "Zendesk AI" is just ChatGPT with a different logo, you should know it’s actually a hybrid model.

They combine their own in-house models, trained on a massive amount of their own customer service data, with powerful language models from partners, including OpenAI. This setup lets Zendesk bake some pretty advanced generative AI features right into its platform.

Here are a few of the key things they highlight from this partnership:

• Summarizing tickets: Quickly getting the gist of long, complicated support tickets to save agents from having to read every single word.

• Creating knowledge base content: Helping admins draft new help center articles or create macros.

• Expanding replies: Letting an agent type a few quick words and having the AI flesh it out into a complete, well-written response.

• Smarter AI agents: Powering their newer AI agents that can actually understand context and handle tasks on their own.

Zendesk is also quick to mention security, noting they use endpoints with OpenAI that don’t retain data and offering data storage options in the EU. This gives a nice baseline of trust, but as we’ll see, the way the whole thing is structured creates a different kind of problem.

How Zendesk uses OpenAI within its platform

Zendesk weaves AI directly into its products, like AI Agents and Copilot. This gives you a smooth experience if your team lives and breathes Zendesk all day, but it’s worth taking a second to understand the trade-offs.

The perks of a built-in AI solution

The biggest selling point of a native tool is pure convenience. The AI is already there in the agent workspace, so there’s no need to jump between different tabs or apps. Everything from tickets to AI settings is handled in one place. It’s made to work with Zendesk data from the get-go, offering features like smart ticket routing and self-service tools right away.

The drawbacks of a closed-off system

While a built-in solution sounds great on paper, it often traps you in what’s known as a "walled garden."

• Information gets trapped. Zendesk AI works best when it’s using information that’s already stored inside Zendesk, like your help center articles. But what about all the other knowledge your company runs on? Most teams have vital info scattered across Google Docs, Confluence pages, or old Slack threads. Getting Zendesk’s native AI to learn from these outside sources is a huge headache, if not impossible. This leaves your AI with massive blind spots.

• You don’t have much control. At the end of the day, you’re stuck with Zendesk’s pre-set workflows. Want to tweak the AI’s personality, set up detailed rules for when to escalate a ticket, or create special actions that connect to your other tools? You’re probably going to hit a dead end. In contrast, solutions like eesel AI give you a complete workflow editor so you can have total control.

• It’s an all-or-nothing approach. Zendesk’s AI provides the most value when you’ve fully bought into their entire product suite. It isn’t a flexible layer you can just add on top of a mix of different tools. If your team’s information and processes are spread out, a native solution can feel more like a cage than a tool.

The headache of building your own integration

After seeing the limits of native tools, some tech-savvy teams start thinking, "Why don’t we just build our own?" <quote text="One developer on Reddit shared how they built a custom solution because the existing options were "expensive...and less flexible."" sourceIcon="https://www.iconpacks.net/icons/2/free-reddit-logo-icon-2436-thumb.png" sourceName="Reddit" sourceLink="https://danielsodkiewicz.github.io/zendesk-openai-integration.html">

And while that route gives you ultimate freedom, it’s full of some serious hurdles that make it a non-starter for most companies.

The typical ways people try to build it

There are generally two paths teams take when trying to connect Zendesk and OpenAI themselves:

1. Using middleware tools: Platforms like Make.com or n8n.io let you visually connect Zendesk and OpenAI’s APIs without needing to be a coding wizard. You can drag and drop to set up rules like "When a new Zendesk ticket comes in, send it to OpenAI to get a draft response."

2. Coding it from scratch: This means writing your own code (usually Python or JavaScript) to directly interact with the Zendesk and OpenAI APIs. It’s the most powerful option but requires developers to build it and, more importantly, keep it running.

Why going custom is usually a bad idea

Building your own integration can feel like the perfect answer, but it almost always turns into a resource-draining nightmare.

• It’s complicated and breaks easily. These custom builds are fragile. One tiny update to an API on either Zendesk’s or OpenAI’s side can bring your whole system down, forcing your developers to drop everything to put out the fire. It becomes a never-ending maintenance job.

• It doesn’t scale well. As one Redditor smartly asked, "How do you handle things like new knowledge articles or updates?" Manually feeding new files to your custom model every time a document changes just isn’t realistic. A good AI needs to sync with your knowledge sources automatically.

• It introduces security risks. When you start passing sensitive customer data through your own scripts or other middleware tools, you open up new security holes. <quote text="Another Reddit user pointed out that security and data policies are "a main concern for a lot of companies."" sourceIcon="https://www.iconpacks.net/icons/2/free-reddit-logo-icon-2436-thumb.png" sourceName="Reddit" sourceLink="https://www.reddit.com/r/Zendesk/comments/1i0mxpc/i_connected_zendesk_to_openaichatgpt_assistant/">

It’s incredibly difficult for a homegrown solution to match the security standards of a dedicated platform.

• You miss out on advanced features. You might get a basic connection working, but what about the features that make an AI solution genuinely useful? Things like a simulation engine to test performance, helpful reports, or automatically generating help articles from conversations are massive software projects in themselves. This is where a dedicated platform like eesel AI comes in, giving you all of that right away.

A better approach with a plug-and-play AI layer

What if you could have the power of a custom OpenAI setup without the technical headaches, and the simplicity of a native tool without being locked in? That’s the idea behind a plug-and-play AI layer. It sits on top of the tools you already use, like Zendesk, bringing all your knowledge together to automate support where you need it most.

Go live in minutes, not months

Instead of a multi-week custom project, eesel AI offers a one-click integration with Zendesk. You can sign up, connect your help desk, and start seeing how the AI would perform on your past tickets in a matter of minutes. No mandatory sales demos, no waiting for developers. This self-serve approach means you can see if it’s a good fit almost immediately.

Instantly connect all your knowledge

eesel AI was specifically designed to fix the "trapped information" problem. It doesn’t just learn from your Zendesk help center. It connects to all your company’s sources of truth, from past ticket history to documents in Google Docs, Confluence, and Notion. This gives the AI the full story, allowing it to provide accurate, context-rich answers that siloed, native tools just can’t match.

Get full control and test everything first

With eesel AI’s powerful simulation mode, you can test your setup on thousands of your real historical tickets before it ever talks to a single customer. This lets you see exactly how the AI will behave and forecast things like resolution rates and cost savings with real data.

Plus, you get fine-grained control with a customizable workflow engine. You can decide exactly which tickets the AI should touch, what its tone of voice should be, and what special actions it can take, whether that’s looking up an order in Shopify or automatically tagging and escalating a ticket.

When you stack it all up, the difference is pretty clear. Native Zendesk AI is fast to set up but very limited. A custom DIY project is flexible but slow, risky, and a pain to maintain. A plug-and-play tool like eesel AI gives you the best of both: it’s incredibly fast to get started, connects to all your knowledge, and gives you deep, self-serve customization without needing to write a line of code.

This video demonstrates an AI assistant inside Zendesk that offers a powerful alternative to the native Zendesk AI.

What’s the bottom line?

Yes, Zendesk uses OpenAI. But the more important question to ask is whether its built-in AI solution gives your team the flexibility and intelligence you actually need to provide great customer support. For a lot of teams, the answer is no.

The native tool creates information silos and locks you into one ecosystem, while trying to build your own is a slow, complex, and risky path.

A plug-and-play AI layer like eesel AI offers a much better alternative. It connects with Zendesk in minutes, pulls in all of your scattered company knowledge, and gives you the power to automate support on your own terms.

Don’t settle for a bundled AI that doesn’t quite fit. See what a dedicated, flexible AI platform can do for your team.

Start your eesel AI setup for free and see how it performs on your real ticket data in minutes.