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3 weeks ago
Really interested in the conversations happening around Agentic AI and its potential across ServiceNow.
From an early-stage perspective in the Employee Workflow space, there’s a lot of opportunity in enabling non-developers to build and orchestrate AI agents using AI Agent Studio — especially as organisations start exploring how to move beyond basic automation.
The direction of travel seems to be shifting towards more secure, agentic workflows, particularly where cross-departmental processes and data are involved. This moves the focus from automating individual steps to thinking more about end-to-end outcomes.
Curious how others are approaching this:
- Are you seeing more interest in AI Agent Studio for custom agentic workflows?
- Or is adoption still primarily focused on out-of-the-box capabilities?
- What are the biggest technical or governance challenges you’re seeing so far?
Solved! Go to Solution.
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3 weeks ago
Hi GemainePSS
- Agentic AI is enabling a shift from traditional automation to more autonomous, outcome-driven workflows.
- Beyond ITSM/HRSD, it is being implemented in various areas like financial services, healthcare, and customer operations, where AI agents can understand context, make decisions, and orchestrate multiple steps across systems.
- For example, instead of just routing a ticket, an AI agent can take ownership of the entire lifecycle—from request intake, classification, and routing to recommending or even executing resolutions.
- The real value comes from this transition to end-to-end orchestration, where AI agents improve efficiency, reduce manual effort, and enhance user experience. However, key challenges still include ensuring data readiness, proper governance, and maintaining trust in AI-driven processes.
"Curious to hear how others are exploring cross-functional AI workflows beyond ITSM/HRSD"
Hope this helps! If it answers your question, please consider marking it as Helpful or accepting it as a solution.
Thank you!
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3 weeks ago
Hi GemainePSS
- Agentic AI is enabling a shift from traditional automation to more autonomous, outcome-driven workflows.
- Beyond ITSM/HRSD, it is being implemented in various areas like financial services, healthcare, and customer operations, where AI agents can understand context, make decisions, and orchestrate multiple steps across systems.
- For example, instead of just routing a ticket, an AI agent can take ownership of the entire lifecycle—from request intake, classification, and routing to recommending or even executing resolutions.
- The real value comes from this transition to end-to-end orchestration, where AI agents improve efficiency, reduce manual effort, and enhance user experience. However, key challenges still include ensuring data readiness, proper governance, and maintaining trust in AI-driven processes.
"Curious to hear how others are exploring cross-functional AI workflows beyond ITSM/HRSD"
Hope this helps! If it answers your question, please consider marking it as Helpful or accepting it as a solution.
Thank you!
