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Agentic AI in ServiceNow: The next generation of AI automation

10. February 2025· 3 Min. read Copy link Share on LinkedIn

Why Agentic AI is essential for businesses

Strategic advantage: How Agentic AI revolutionizes automation

Agentic AI features in ServiceNow

  • AI Agent Orchestrator: Connects multiple AI agents and ensures smooth workflows between departments.
  • AI Agent Studio: Enables the development of custom AI agents tailored to business needs.
  • Now Assist: Supports employees with proactive suggestions and automated workflows.

Hybrid model: Combining rule-based and agent-based automation

Use cases for Agentic AI in business operations

Example Benefit
IT Service Management: Automated support ticket handling AI agents automatically classify and prioritize tickets.

Faster issue resolution, reduced IT support workload.
IT Operations Management: Proactive error detection AI agents detect anomalies early and take action.

Reduced downtime, improved system availability.
IT Asset Management: Efficient resource utilization AI agents analyze software and hardware usage to identify optimization opportunities.

Cost savings, optimized IT resources.
Customer Service Management: Smart customer interaction Agentic AI enhances customer service with fast and targeted responses.

Immediate and personalized customer service.
Field Service Management: Dynamic scheduling Field service employees benefit from intelligent scheduling.

Faster customer service, better resource utilization.
Strategic Portfolio Management: Dynamic project control Agentic AI enhances project planning through data-driven analysis.

More agile project management, optimized resource allocation.
HR Service Delivery: Efficient onboarding AI agents automate onboarding processes for new employees.

Faster integration of new employees, reduced HR workload.
Operational Technology Management: Optimized industrial maintenance Production systems and machines require regular maintenance. Agentic AI optimizes maintenance schedules.

Reduced downtime, optimized maintenance processes.
Business Process Automation: Intelligent approval processes Many business processes require manual approvals. AI agents can accelerate these decisions.

Faster approval processes, reduced bureaucracy.
Workload Automation: Dynamic task allocation IT and business teams handle large volumes of tasks daily. AI agents optimize resource utilization and task assignment.

Improved task organization, increased efficiency.

Future outlook: Competitive advantages and innovation potential with ServiceNow Agentic AI

Traditional automation vs. Agentic AI

  • Operates based on predefined workflows
  • Responds only to fixed inputs
  • No autonomous optimization
  • Continuously learns from data
  • Adapts dynamically to new situations
  • Seamlessly integrates with existing systems

How businesses benefit from Agentic AI

  • Competitive advantage: Faster response times and more efficient processes than competitors.
  • Fewer manual processes: AI-driven workflows reduce operational workload.
  • Dynamic adaptability: AI agents flexibly respond to new business demands.
  • Enhanced customer experience: Faster, more personalized interactions.
  • Cost savings: Optimized resource utilization.
  • Seamless system integration: AI agents collaborate across multiple platforms.

Frequently asked questions:

What are AI agents?
AI agents are AI-powered software components that can do more than analyze or answer tasks; they can execute them in a goal-oriented way. They understand requests, evaluate information, make rule-based or AI-supported decisions, and then trigger specific actions in processes, workflows, or systems. Unlike traditional chatbots, AI agents do not simply respond to individual questions. They can plan multiple steps, consider context, use data from different sources, and independently handle tasks within defined guardrails.
What is the difference between GenAI and AI agents?
Generative AI creates content such as text, summaries, answers, code, or recommendations. AI agents go one step further: They use generative AI, decision logic, data, and integrations to actively execute tasks. Example: GenAI can summarize a support ticket. An AI agent can also check which category fits, analyze similar cases, prepare solution recommendations, start a workflow, or route the ticket to the right team.
What is the difference between a chatbot and an AI agent?
A chatbot typically answers questions or conducts simple dialogs. An AI agent can also plan tasks, evaluate information, support decisions, and trigger actions in connected systems or workflows. While a chatbot is often focused on communication, an AI agent combines communication, contextual understanding, automation, and process execution.
What benefits do AI agents offer companies?
AI agents can reduce repetitive tasks, shorten processing times, and relieve employees in their day-to-day work. They help teams find information faster, execute processes more consistently, and handle service requests more efficiently. AI agents are especially valuable wherever many similar tasks, large volumes of data, or complex process chains come together. Examples include IT Service Management, Customer Service, HR, Finance, Field Service, Operations, and Enterprise Service Management.
Where can AI agents be used?
AI agents are suitable for many areas of the enterprise where requests, decisions, data, and workflows are interconnected. Typical use cases include IT service, customer service, HR processes, knowledge management, process automation, incident management, request fulfillment, change management, AIOps, and case management. For example, they can classify tickets, suggest knowledge articles, process service requests, prepare approvals, analyze incidents, or guide employees through complex processes.
Do AI agents replace employees?
AI agents are primarily intended to support and relieve employees. They take over repetitive, time-consuming, or highly standardized tasks so that specialists have more time for complex decisions, customer interaction, and value-adding activities. In many scenarios, AI agents therefore do not work fully autonomously, but rather act as assistance systems with clear responsibilities, escalation rules, and human oversight.
How do companies get started with AI agents?
The best way to get started is with clearly defined use cases that deliver measurable value while remaining easy to control. Suitable examples include frequent support requests, ticket classification, knowledge management, summaries, simple approval processes, or standardized service requests. It is important not to focus on technology alone, but to consider processes, data, roles, responsibilities, and governance from the very beginning.

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Personal advice on ServiceNow

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Manuel Röttele

Senior Account Executive and specialist for service management and the ServiceNow platform

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