How Organizations are Leveraging ServiceNow AI Agents in Customer Support?

Do you still believe that customer support is merely a back-office function? It is not.
It is a vital frontline differentiator that significantly impacts your brand’s reputation and customer loyalty. When users are struggling with password resets or have billing inquiries, they expect to receive immediate, contextually relevant, and reliable assistance. Unfortunately, not all customers receive the support they seek. Support teams are often overwhelmed by multiple queries, increasing ticket volumes, and staff shortages. As a result, customers experience inconsistent service and delayed resolutions.

While many modern businesses have turned to chatbots for assistance, they often provide rigid and scripted answers, leaving customers frustrated. What they need is more than just basic chatbots. They require smart, enterprise-ready systems designed to learn, adapt, and act effectively. This is where ServiceNow AI Agents come into play. These AI-powered agents can triage requests, retrieve data, suggest solutions, automate multi-step resolutions, and escalate issues seamlessly. Their purpose is to assist the human agents to enhance support capacity, reduce resolution times, and free support teams to focus on complex or sensitive cases.

Let us take a closer look at the ways organizations are leveraging AI agents for customer support and success.

Ways organizations use ServiceNow AI Agents in customer support

Here are several ways in which the capabilities of AI agents can be utilized:

• Automating high-volume support requests: AI Agents can classify and route incoming tickets accurately, whether it’s a failed transaction, a product bug, or a user access issue. They resolve routine cases independently and escalate the rest with full context.
• Troubleshooting recurring technical issues: With access to historical data and integrated knowledge bases, AI Agents can identify known issues and walk customers through resolution steps, like configuring devices, reinstalling apps, or clearing caches.
• Coordinating multi-team support workflows: Support tickets that involve finance, engineering, and operations can be orchestrated through the agent. This ensures faster, coordinated actions across departments.
• Offering omnichannel technical support: Customers often shift from email to chat or phone for resolution. Agents ensure consistent support across these channels, maintaining context to avoid redundant explanations.
• Learn and adapt to emerging issues: The AI Agents analyze feedback and ticket trends to identify new support gaps. This allows businesses to update their resolution flows, knowledge articles, and training programs.
• Ensuring support, compliance, and control: With AI Control Tower integration, organizations can enforce audit trails, control access to sensitive data, and ensure that AI-driven resolutions meet data privacy and compliance standards like GDPR.

Example of ServiceNow Customer Support AI Agent in Action

With the help of this hypothetical example of a telecom customer support environment, let us shed light on how ServiceNow AI Agents operate in action:

Scenario: Billing Error Resolution

There’s a regular telecom user, Sarah, who tried to contact customer support via chat after noticing an unexpected charge on her mobile bill. Now that she has initiated the conversation with the agent, this is how the agent would help her find a resolution.

• Identifying the intent: The AI Agent welcomes her and classifies the message as a billing error inquiry.
• Fetching contextual data: The agent retrieves Sarah’s billing records and detects that a discount plan expired in the current cycle.
• Providing a resolution: It explains the overage charge and suggests an updated plan that better suits her recent usage.
• Escalation to human resources: Sarah requests human assistance. The case, with all relevant context, is passed to a live agent without repetition.
• Case management: The case gets logged and follows up on the ticket status while capturing Sarah’s feedback.

Understanding industry-specific support use cases

Telecom

Telecom companies manage massive volumes of customer queries daily, from SIM activations to poor network coverage. AI Agents can help by automatically validating user accounts, identifying the cause of network complaints using backend data, and offering guided resolution steps. Moreover, after analyzing the user behavior, they can also upsell and recommend better plans that lead to better customer service. Such as Bell and BT Group, which unified multiple systems on ServiceNow AI Platform to automate service.

IT Services

IT support teams deal with a continuous flow of tickets like password resets, software provisioning, and system access requests. The agents can automate ticket classification and resolution, enforce SLA tracking, and handle escalation paths efficiently, freeing up IT staff for higher-priority issues. Like Teleperformance, CANCOM, and Kainos, who used ServiceNow AI agents to streamline global IT support.

Healthcare

Patient portals, insurance approvals, and appointment scheduling are common pain points in digital health environments. The patients can be assisted by the agent and walk through troubleshooting login issues, guide them through scheduling flows, and resolve common insurance-related queries while adhering to HIPAA-compliant data protocols.

Retail

Retailers experience spikes in support requests during peak shopping seasons. This is where customers require more guidance with order status updates, initiate refunds for damaged items, and automate responses for out-of-stock issues. Here, agents ensure consistency of communication across email, app chat, and website, improving customer satisfaction and reducing cart abandonment.

Best practices and considerations for support teams

Consider these best practices for the implementation of customer support agents:

• When you deploy your agents, start by assigning them high-volume support scenarios, such as access issues or billing errors. This approach will help you understand how the agents respond to these situations. Since these queries are unlikely to escalate into larger grievances, your human agents can step in if necessary and resolve any issues that arise.
• While the ServiceNow AI platform supports any kind of data from any source, it is advisable to ensure that support knowledge bases are well-structured and up-to-date. This will help the agent learn and understand the context better.
• Clearly map solution escalation paths and workflows across departments for seamless operations.
• While you have your intelligent AI-powered workforce ready to serve, make sure to train your human agents to work alongside them.
• Lastly, monitor ticket data to evaluate agent performance and response, and adjust automation flows at regular intervals.

Conclusion

To conclude, building a strong, AI-backed customer support system is no longer optional; it’s essential. AI agents powered by ServiceNow enable not just intelligent troubleshooting but also proactive maintenance through automation, real-time data access, and seamless workflow integration.

If you’re still on the fence, now is the time to make the shift. Cyntexa, a ServiceNow Consulting & Implementation partner is here to guide you. With deep expertise, a forward-looking approach, and hands-on experience with the latest AI agent capabilities, we’ll help you deploy AI solutions tailored to your business. So free your support teams to focus on what truly matters, that is, creating memorable customer experiences and fostering long-term loyalty.

Schedule a call with our experts today.

AUTHOR

Shruti

ServiceNow, Sales Cloud

Shruti is a ServiceNow Consultant with 5+ years of experience across ServiceNow ITSM, AWS, Salesforce Loyalty Management, and managed services. She blends technical expertise with strategic insights to deliver transformative IT services and CRM solutions that enhance efficiency and customer satisfaction.