Everything you need to know about ServiceNow GenAI

If you work in support or IT, you know the drill. The pressure is always on to resolve issues faster, boost productivity, and keep everyone happy, all while keeping a close eye on the budget. Generative AI is being talked about as the answer to everything, and honestly, for good reason. It promises to take over the repetitive work that bogs teams down, freeing them up for more important stuff.

ServiceNow, a huge name in enterprise workflows, is jumping on the GenAI train in a big way. But what does that actually mean for you and your team? Let's cut through the buzzwords and get a clear, practical look at what ServiceNow's GenAI can do, what works well, where the sticky points are, and what you really need to know before diving in.

What is ServiceNow GenAI?

First off, ServiceNow GenAI isn't a single product you can just buy and install. It’s better to think of it as a layer of AI that's woven directly into the main ServiceNow Platform. The whole idea is to automate tasks, generate helpful content, and offer up insights across ServiceNow’s big applications, like ITSM (IT Service Management), CSM (Customer Service Management), and HRSD (HR Service Delivery).

The star of the show here is Now Assist, which is ServiceNow’s brand for all its user-facing GenAI features. It runs on a mix of ServiceNow's own large language models (LLMs), trained on their specific data, plus integrations with outside models like Azure OpenAI. For those who want more technical control, there’s a Generative AI Controller that lets companies plug in their own AI models.

The entire approach is built to feel native, embedding AI right into the workflows your teams are already using every day. It’s a powerful concept, but it comes with a pretty big catch: its intelligence is often stuck with the data that lives inside ServiceNow. For companies where knowledge is spread out across different tools, this can be a real roadblock to getting genuinely helpful AI responses.

Key features and capabilities of ServiceNow GenAI

So, what can this thing actually do for you? Let's break down the main features and see how they work in the real world.

Now Assist: The hands-on ServiceNow GenAI experience

Now Assist is how most people on your team will actually use GenAI on the platform. It's not just one feature, but a whole toolkit of skills designed to make work a bit easier.

Here’s a quick rundown of what it does:

• Summarization: Now Assist can read through long ticket histories, dense case notes, and chat transcripts to give you a quick summary. This helps agents get the gist of an issue in seconds instead of piecing it all together manually.

• Content Generation: It can draft knowledge base (KB) articles from tickets that have been solved or write up resolution notes for agents. The goal is to capture solutions as they happen and make them easy to find later.

• Virtual Agent Boost: It gives the chatbots used for employee and customer self-service a boost, making conversations feel more natural and less like you're talking to a robot.

• Code Generation: For the developers, "text-to-code" features can help write scripts and build apps on the ServiceNow platform using simple, plain-English prompts.

Generating KB articles from tickets is a great idea for plugging knowledge gaps. The problem is, the process usually needs a lot of manual review, and it’s completely limited to data that's already in ServiceNow. A more flexible way to do this is with tools like eesel AI, which can also draft articles from successful tickets but can be trained on knowledge from outside ServiceNow. By connecting to sources like Confluence or Google Docs, you end up with a much more complete and useful knowledge base.

AI search and natural language queries

ServiceNow has also made its search a lot smarter. AI Search tries to understand what a user is actually looking for (their intent) and give them a direct, summarized answer instead of just a list of links to KB articles.

Natural Language Query (NLQ) takes this a step further, letting users ask for data and reports just by typing a normal sentence. Instead of building a complicated report, a manager could just ask, "Show me all high-priority incidents from last month," and get an answer.

Automation and workflow building

GenAI is also being added to ServiceNow’s low-code development tools like Flow Designer and App Engine. The idea is to let users describe a workflow they want in plain English, and have the platform generate the basic structure for them. This makes it easier for more people to build their own custom automations without needing deep technical skills.

While these low-code tools are powerful, they still require a solid understanding of the ServiceNow platform and a decent amount of setup. This is a pretty different philosophy from a tool like eesel AI, which is all about getting you live in minutes. Integrations with help desks like Zendesk, Freshdesk, or Jira Service Management are just one click, making the whole setup incredibly simple and delivering results almost right away.

Common use cases for ServiceNow GenAI

Now that we’ve gone over the features, let's see how businesses are actually using them.

Improving IT service management (ITSM)

For IT teams, GenAI is all about working smarter and getting agents away from tedious tasks.

• Ticket Routing & Triage: Incoming IT tickets can be automatically sorted and sent to the right team based on their content, saving service desk managers a ton of time.

• Incident Resolution: Now Assist can show agents summaries of similar past incidents and suggest possible fixes, which can speed up troubleshooting.

• Self-Service: A smart Virtual Agent can walk employees through solving their own IT problems by pulling answers from the knowledge base, which means fewer tickets get created in the first place.

Improving customer service management (CSM)

In the customer support world, the focus is on delivering faster, more consistent help.

• Faster Responses: Now Assist can draft replies to common customer questions in emails and chats. This keeps the tone consistent and lets agents focus on trickier cases.

• Proactive Support: By spotting trends in customer chats and tickets, GenAI can help teams identify widespread issues before they blow up.

• 24/7 Support: You can put Virtual Agents on your website or in your app to handle common questions anytime, so customers can get help even when your team is asleep.

Good customer support automation, however, depends entirely on having access to the right knowledge. While ServiceNow is great at analyzing its own ticket data, many answers live in other systems. An AI platform like eesel AI was built specifically to fix this. It shines by bringing together knowledge from everywhere, past tickets, help centers, Shopify product pages, and internal wikis. This gives the AI the full story, allowing it to provide answers that are actually complete, something that often requires a difficult and expensive custom integration in ServiceNow.

Limitations and considerations for ServiceNow GenAI

ServiceNow GenAI is a powerful tool, but it's not going to solve all your problems with the flip of a switch. Before you commit, it’s worth understanding its limits and what it really takes to get it working well.

Implementing ServiceNow GenAI: It's a big project

Despite the "low-code" talk, getting GenAI up and running in ServiceNow is a full-blown enterprise project. It means careful planning, cleaning up your data, running pilot programs, and having a real strategy for helping your team adapt. "Starting small" in the ServiceNow universe can often mean a project that takes weeks or even months and requires dedicated staff or pricey implementation partners.

This is a very different world from eesel AI's self-serve approach. You can sign up, connect your helpdesk in a few minutes, and run a simulation on thousands of your past tickets before you even go live. This lets you see an accurate forecast of your resolution rates and cost savings, so you can roll out automation with confidence, one queue at a time.

The challenge of scattered knowledge

This is probably the biggest hurdle. ServiceNow GenAI is at its best when all your company's knowledge is already on the platform. But let's be realistic, that's almost never how it works. Most companies have important information scattered across dozens of tools: technical docs in Confluence, project plans in Google Docs, internal chats in Slack, and product updates in Notion.

Pulling all that external knowledge into ServiceNow can be a complicated and expensive integration project, and it rarely stays in sync in real-time, which is what you need for an AI to give consistently accurate answers.

This is the exact problem eesel AI was built to solve. It was designed from day one to unify knowledge from all over the place. With over 100 one-click integrations, it instantly and securely connects to all your sources, making sure your AI has a complete, up-to-date picture without a painful, months-long IT project.

The mystery of ServiceNow GenAI pricing

ServiceNow doesn't publicly list its prices for GenAI features. To get access, you typically need an enterprise-level contract and a long chat with a sales team. This makes the whole process a bit of a black box and can make it hard to guess the total cost or run a small pilot without a huge financial commitment.

In contrast, you can find eesel AI's pricing right on their website. The plans are transparent, predictable, and based on usage, with no hidden fees that punish you for doing well. You can start with a monthly plan and cancel anytime, letting you test things out and scale up when you're ready, without being locked into a long-term contract.

This video covers five key GenAI features in ServiceNow that you should know about, providing a great overview of its capabilities.

Is ServiceNow GenAI right for you?

So, what's the final verdict? ServiceNow GenAI is a serious solution for large companies that are already all-in on the ServiceNow ecosystem. If all your data, workflows, and teams are already living on the platform, it offers a deep, native integration that can really improve how you work.

For most businesses, though, the complexity of setting it up, the reality of scattered knowledge, and the unclear pricing model can be major drawbacks. For teams looking for a quicker, more flexible path to AI-powered support, the cost and time involved can be tough to justify.

If you want to see real results from support automation in minutes, not months, and connect all your knowledge sources without a massive IT project, eesel AI is a great alternative. It works smoothly with the tools you already use, giving you a powerful, self-serve AI layer that works with your entire tech stack.

Why not start a free trial today and see for yourself?