Is ServiceNow AI really AI?

ServiceNow is painting a pretty ambitious picture of the future. They call themselves the "AI platform for business transformation," envisioning a world where smart agents run just about every workflow in your company. The idea is to have one single, smart platform that connects everything and automates the whole business.

It sounds great, but there seems to be a growing gap between that big vision and what people are actually experiencing. If you browse through technical communities or read what industry analysts are saying, you’ll find a common theme: getting started is tough. Companies are running into major roadblocks with messy data, confusing setups, and high costs that can stop an AI project in its tracks.

This all leads to a question that a lot of IT and support leaders are quietly asking: "Is ServiceNow AI really AI"? Or is it just a very fancy automation tool that demands a massive, upfront effort to even get off the ground?

In this post, we’ll get into what ServiceNow AI is, the real-world headaches of its "one platform to rule them all" approach, and how a nimbler strategy that focuses on integration can give you powerful automation without needing to rebuild your entire tech stack.

What is ServiceNow AI?

ServiceNow’s AI isn’t just one thing; it’s a collection of AI tools baked right into their main Now Platform. Their goal is to create a system where AI is the main way you interact with software, moving past simple chatbots to what they call "agentic AI." This just means AI agents that can handle complex, multi-step jobs on their own, across different departments.

The main pieces of their offering are:

• Now Assist: This is a generative AI helper that does things like summarizing incident reports, writing code, or drafting knowledge base articles.

• AI Agents: These are the systems designed to run workflows by themselves, handling everything from simple requests to tricky problems, as long as it’s within the ServiceNow world.

• AI Control Tower: Think of this as a central dashboard where you can manage and keep an eye on all the AI agents running on the platform.

The promise is definitely compelling: one place for all your data and one engine to power automation across the company. But making that happen hinges on your organization being ready to go all-in on the ServiceNow ecosystem, and frankly, that’s a huge commitment.

Common challenges with the ServiceNow AI approach

While the vision is impressive, user feedback and expert reviews tell a story of practical problems that can slow things down and hurt your return on investment. For a lot of teams, ServiceNow’s AI feels less like a ready-to-use solution and more like a long, expensive project.

The clean data problem

The first and most common wall people hit is data. Any AI is only as good as the data it’s trained on, and ServiceNow’s is no exception. People on forums like Reddit are quick to point out that most companies "lack the proper foundational data," like a clean configuration management database (CMDB) or a well-kept knowledge base.

This isn’t just frustrated users talking. An EY executive mentioned in a CIO.com article that their biggest hurdle was cleaning up old, useless information in their knowledge bases before the AI could do its job. What that means for you is that before you see any benefit, you could be looking at a huge, manual data cleanup project that drags on for months.

But what if you didn’t have to do all that? Modern tools like eesel AI are built to work with the knowledge you already have, mess and all. By training directly on your past support tickets, scattered Confluence pages, and disorganized Google Docs, the AI learns your business context from day one, cutting out most of that painful upfront work.

An infographic showing how eesel AI connects to various existing knowledge sources to power its AI, avoiding a massive data cleanup project.

The cost and complexity of a single platform

ServiceNow’s whole strategy is to become the central hub for your entire company. As analyst Josh Bersin notes, this means you’re "buying another complex enterprise platform on top of your existing complex enterprise platforms." This approach creates a couple of big problems.

First, it’s expensive. You’re not just adding a feature; you’re buying into an entire ecosystem. This usually means a long sales process, pricing that isn’t clear, and a major financial commitment before you’ve even proven it works for you.

Second, it’s complicated to set up. Getting ServiceNow AI running isn’t something you can do yourself over a weekend. It requires specialized developers and a dedicated project team to get it working with your existing processes. It’s a project that takes months, not minutes.

The alternative is a tool that just plugs into what you already use. An integration-first tool like eesel AI offers a much simpler way forward. With a self-serve setup and one-click connections for help desks like Zendesk and Jira Service Management, you can be up and running in minutes. No sales call or mandatory demo required. It fits into your current workflow instead of making you rebuild it.

A workflow diagram illustrating the simple, self-serve implementation process of an integration-first AI tool like eesel AI.

Marketing hype vs. agent reality

Let’s be real, many users feel that what ServiceNow calls AI is currently closer to "augmented search and workflows" than true, thinking intelligence. The AI can still make stuff up (hallucinate) or make mistakes, which naturally makes teams hesitant to rely on it. If the system can’t grasp the finer points of a request, it’s hard to trust it.

This is where being able to test an AI safely is so important. Without a way to check how an AI agent will behave, you’re basically experimenting on your live customers, and that’s a risk most support teams aren’t willing to take.

That’s why the ability to simulate performance is so valuable. With eesel AI’s simulation mode, you can test your AI agent on thousands of your past tickets in a completely safe environment. You get a clear report card on its potential resolution rate and can tweak its behavior with a simple prompt editor before it ever talks to a customer. This way, you can roll it out knowing exactly what to expect.

A screenshot of eesel AI's simulation mode, which allows users to test AI performance on past tickets before deployment.

A closer look at ServiceNow AI features

To figure out if ServiceNow AI is the real deal, it helps to look at its main features and what they mean in practice. The technology is definitely sophisticated, but its design creates some real constraints for businesses that aren’t ready to bet the farm on one platform.

AI agents and the walled garden

ServiceNow’s AI Agents are built to be powerful workflow managers, but they work best when they stay inside the ServiceNow ecosystem. They can connect to outside systems, sure, but it often involves complicated setups and forces you to use the Now Platform as the central command center for everything.

This creates a "walled garden." If your goal is just to add a smart AI layer to the tools you already use and like, such as Slack, Freshdesk, and Confluence, ServiceNow’s approach forces you to pipe everything through their system. For teams just looking to solve a specific problem, like deflecting common IT support questions, that can be total overkill.

AI Control Tower as a necessary complexity

The AI Control Tower is ServiceNow’s answer for AI governance. It gives you a single screen to manage all the AI agents you’ve built. The thing is, this is a solution for a problem that ServiceNow’s platform approach creates in the first place: managing all the different agents you had to build within their system. If your team just needs one reliable bot to handle a specific task, building and managing a "control tower" is an extra layer of work you just don’t need.

Now Assist and the data dependency loop

Now Assist offers some cool generative AI features for summarizing tickets and creating content. But its output is completely tied to the quality of the data inside ServiceNow. If your knowledge articles are old or your incident reports are a mess, Now Assist will just reflect those problems, spitting out summaries or suggestions that are useless or flat-out wrong. This brings you right back to the first problem: your AI is only as good as your data, and ServiceNow needs your data to be nearly perfect from the start.

ServiceNow AI pricing

One of the first questions on anyone’s mind is, "What’s this going to cost me?" With ServiceNow, the answer is… complicated.

ServiceNow doesn’t have simple, public pricing for its AI products. The features are usually bundled into their pricier enterprise packages, like ITSM Pro, CSM Pro, or HRSD Pro. To get access, you have to go through a custom quote process with their sales team.

This quote-based model means a few things for you as a buyer:

• No Transparency: It’s impossible to guess what your budget should be without getting on a long sales call.

• High Barrier to Entry: The cost is aimed at large companies, which can shut out smaller teams or departments that just want to try a pilot project.

• Long-Term Lock-in: The deals are often multi-year contracts, meaning you’re locked in before you even know if you’re getting value from it.

This is a world away from modern software tools that offer clear, public pricing and flexible monthly plans, letting you start small and grow at your own pace.

A more agile alternative to ServiceNow AI

For companies not quite ready for a massive platform change, there’s a much more practical way to get started with AI automation. The alternative is to use a lightweight but powerful AI layer that plugs right into the tools your team already knows and uses every day.

This is the whole idea behind eesel AI. Instead of making you switch to a new system, it makes your current one smarter. It works by pulling knowledge from all your existing sources to power AI agents right where your team works.

Unify knowledge, don’t just clean it

The best part of this approach is speed. You can instantly connect sources like old tickets from Zendesk, internal wikis in Confluence, and your help center articles to make your AI smart from day one. eesel AI is designed to find answers in your existing content, turning all that institutional knowledge into an asset right away, without a painful cleanup project.

Maintain control with transparent tools

A more agile approach puts you in the driver’s seat. With eesel AI, you decide exactly which tickets the AI should handle using simple automation rules. You can define its personality and the specific things it’s allowed to do, from escalating a ticket to a human to looking up order information in Shopify using an API. And with clear, predictable pricing, you don’t have to worry about surprise costs that punish you for growing.

A screenshot showing the simple automation rules and customization options in eesel AI, which puts the user in control.

Is ServiceNow AI really AI? It’s about the approach

So, "Is ServiceNow AI really AI"? Yes, the technology behind it is legitimate. But the real question is whether its all-or-nothing platform approach is the right fit for your business. For many, the high cost, long setup time, and need for perfect data make it an impractical choice for solving today’s problems.

A better path for most teams is to adopt an agile AI layer that improves the tools you already have instead of replacing them. By choosing a solution that you can set up yourself, that instantly connects to your knowledge, and that lets you test with confidence, you can reduce the risk and start seeing real results in days, not years.

Ready to see what a practical AI solution can do? Try eesel AI for free and build an AI agent trained on your own data in minutes.