I love how much time and effort ServiceNow AI Agents save, saving us tremendous amounts of money on service desk employees and improved user satisfaction internally at our company. Additionally, the initial setup was very easy. I'm very likely to recommend ServiceNow AI Agents to a friend or colleague, rating it a 10 out of 10. Review collected by and hosted on G2.com.

It is VERY EXPENSIVE. Each 'assist' costs money. The licensing costs are very prohibitive for us to expand our implementation and use the capabilities to their full abilities. Please have a sliding scale costs for the assists. We are a small company and can barely justify the current cost structure to our board. It simply costs more money than it saves us, at our scale. Review collected by and hosted on G2.com.

What I like best about ServiceNow Agent is how much it simplifies day-to-day work without feeling clunky or over-engineered. It gives a clear, central place to manage requests, automate routine tasks, and keep everything moving without constant manual chasing. I especially value how it improves visibility across teams—nothing gets lost, and it’s easier to stay on top of priorities. Overall, it just makes service delivery feel more controlled and efficient. Review collected by and hosted on G2.com.

What I dislike about ServiceNow Agent is that it can sometimes feel overly complex for what should be straightforward tasks. There’s a bit of a learning curve, and not everything is as intuitive as you’d expect, especially for new users. I’ve also found that customisation, while powerful, can become messy over time and make processes harder to follow. At times it can feel like you’re working around the tool rather than the tool working for you. Review collected by and hosted on G2.com.

ServiceNow AI Agents stand out because they’re deeply embedded in the platform rather than feeling bolted on. They can take action across workflows using Flow Designer, IntegrationHub, and CMDB context, which makes them much more than simple conversational tools. The ability to orchestrate tasks, summarize records, and guide users or agents in real time translates into measurable efficiency gains. I also value the governance controls, auditability, and role-based access, which are especially important in regulated environments. Overall, they align well with enterprise architecture principles while remaining flexible enough to scale across a wide range of use cases. Review collected by and hosted on G2.com.

The biggest challenge today is maturity and consistency across capabilities. Some features feel more production-ready than others, and there are still gaps in the explainability and transparency of AI-driven decisions. Implementation also requires thoughtful design and tuning, particularly around data quality, knowledge sources, and guardrails. Licensing terms and overall cost clarity can be a concern as you scale beyond initial use cases. Review collected by and hosted on G2.com.

What I like best about ServiceNow AI Agents is how intuitive and enterprise-ready they feel. The platform makes it easy to automate repetitive work, surface the right information quickly, and improve employee experiences without requiring complex development for every use case. I especially appreciate how the AI capabilities integrate directly into existing workflows instead of feeling like a separate tool. Review collected by and hosted on G2.com.

One downside is that successful implementation still depends heavily on strong governance, clean data, and well-designed workflows. AI Agents can surface inconsistencies in existing processes very quickly, so organizations that are not operationally mature may struggle to get the full value. There is also a learning curve around trust, change management, and understanding where human oversight is still necessary. Review collected by and hosted on G2.com.

I use ServiceNow AI Agents to streamline service operations by automatically triaging requests and guiding users. I appreciate how it solves the issues of slow response during peak request volumes, as the AI handles repetitive queries instantly, reducing pressure on support teams. What I value most is how it balances automation with control, streamlining processes while still allowing flexibility. Automation handles routine requests efficiently, while giving us the option to step in for complex cases. We use it alongside collaboration platforms and monitoring systems to help centralize information and respond to issues more quickly. ServiceNow AI Agents made our workflows more automated and easier to manage, significantly improving operational efficiency. Review collected by and hosted on G2.com.

The platform is powerful, but the learning curve can be a bit steep for new users. It can feel complex at the beginning. More simplified templates and ready-to-use workflows would help users get started quickly. Review collected by and hosted on G2.com.

ServiceNow AI Agents have made it easier to manage routine tasks and user requests. They help automate repetitive work, provide quick responses, and improve the overall experience for both employees and support teams. I particularly like how they fit into existing ServiceNow workflows, making automation feel seamless.

The performance is efficient, and the time saved on automation rather than manual tasks is a great ROI on the investment in ServiceNow agents. Review collected by and hosted on G2.com.

One area that could be improved is the learning curve for new users. ServiceNow comes with many features and configuration options, which can feel overwhelming at first. More guided onboarding, tutorials, and real-world examples could help users get value from the platform more quickly. Review collected by and hosted on G2.com.

Using ServiceNow AI Agents has been a game changer for me as a Java Spring Boot Developer. I appreciate Now Assist for Code, which bridges the gap between my traditional IDE experience like IntelliJ and the ServiceNow environment with its context-aware inline code completion. It helps me avoid syntax errors without constantly checking the documentation. The 'Code Explain' feature is fantastic for maintaining legacy scripts or complex Business Rules, giving me instant summaries of logic, which cuts down on ramp-up time. I'm also a fan of the Integration Hub ‘Spoke’ generation because it makes connecting our Spring Boot microservices to ServiceNow workflows quicker by reducing repetitive boilerplate code. ServiceNow AI Agents allow me to focus on high-level architecture by handling the 'Boilerplate Tax' through natural language prompts for GlideScript and Flow Designer logic generation. Its capability to summarize complex logs into actionable insights has also reduced our Mean Time to Resolution during production incidents. Review collected by and hosted on G2.com.

While the AI is powerful, it isn't perfect. First, it occasionally suffers from 'API Hallucinations,' where it suggests deprecated GlideScript methods that don't align with modern ServiceNow best practices. As a Java dev, I have to double-check the output to ensure it’s not using legacy code. Second, the debugging experience needs improvement. When an agentic workflow fails, the logs can be a bit cryptic compared to a standard Java stack trace, making it hard to see exactly where the LLM lost the context. Lastly, the dependency on 'Data Hygiene' is real. If your Knowledge Base or CMDB isn't perfectly maintained, the AI Agent's effectiveness drops significantly. It’s a great tool, but it requires a lot of foundational 'grunt work' to get it running at 100%. Review collected by and hosted on G2.com.

I really appreciate the shift from simple chatbots to Agentic AI in ServiceNow AI Agents. It's impressive how these agents can autonomously navigate the AI Agent Fabric to execute cross-departmental workflows. The ability for an HR agent to trigger an IT provisioning flow without manual handoffs is a game changer, taking the platform from 'assistance' to actual 'execution.' I also value how the AI Agent Fabric manages governance effectively, ensuring that autonomy doesn't spiral into disorder. Additionally, the integration with Microsoft Copilot has been useful, allowing the ServiceNow agents to act as the 'execution' arm and handle tasks like a password reset or asset check in the background. The initial setup was smooth, with data being easily exported into a CSV file and imported to ServiceNow AI. Review collected by and hosted on G2.com.

I find the dependency on perfect data hygiene a real challenge with ServiceNow AI Agents. If your CMDB is a mess, it could lead to 'automated chaos' by executing wrong workflows. The AI can make confident but incorrect decisions because it doesn't spot bad data like humans can. Plus, the Plus-tier licensing and consumption-based pricing make it quite a heavy lift for organizations that aren't already highly digitally mature. Review collected by and hosted on G2.com.

ServiceNow AI Agents enable smart, automated workflows using natural language and integrations across tools. They boost efficiency and reduce manual work, but require proper setup and data quality to deliver consistent results. Review collected by and hosted on G2.com.

ServiceNow AI Agents still have a few drawbacks. They require significant setup and fine-tuning to work effectively, and outcomes can vary if the underlying data or workflows aren’t well-structured. There’s also limited transparency in how some decisions are made, and complex use cases may still need custom development, reducing the “out-of-the-box” advantage. Review collected by and hosted on G2.com.

It feels like they take a good amount of the effort to complete tickets away from the user. Review collected by and hosted on G2.com.

Sometimes they shift the meaning or emphasis of my original query and steer it toward a different subject. Review collected by and hosted on G2.com.