Upgrade from smart bots to smart action:
Agentic AI by ServiceNow solves problems, not just tickets
Agentic AI by ServiceNow is an autonomous, context-aware AI that works like a smart digital coworker - it doesn’t just assist, it takes action on its own. It understands what people really need, figures out the context and intent, and takes action from start to finish without needing constant human input.
Unlike basic chatbots or rule-based automations, Agentic AI can break down complex requests, make smart decisions based on company data and policies, and handle tasks across teams like IT, HR, or Field Service. It talks to your systems - like CRM, ERP, or CMDB - and connects data with workflows to make sure things move smoothly. It can prioritize what's urgent, proactively resolve issues and adapt in real time, and even learn over time to get better and faster.
In short, it’s not just answering questions - it’s actually solving problems.
Resolution by AI Agent
1: Keyword recognition
Picks up “delayed delivery” and “invoice issue.”
2: Basic responses
Replies with tracking info link: “You can check delivery status here…”, and a knowledge base article: “Most common reasons for billing mistakes …”
3: Ticket creation & routing
- Creates two separate tickets: one for Logistics (delayed delivery) and one for Billing (incorrect invoice).
- Tickets sit in queues, may get handled by different agents with no coordination.
Summary Customer Service
AI agent:
- No context or prioritization.
- Doesn’t recognize Emma as a VIP customer.
- No SLA acceleration or relationship-sensitive handling.
Agentic AI by ServiceNow:
- Multi-issue handling.
- Recognizes customer type (VIP).
- Cross-system resolution (logistics + billing).
- Personalized action plan.
- Autonomous refund & ticket escalation.
- Continuous learning and bug flagging.
Resolution by Agentic AI
Agentic AI treats this as a compound issue involving customer satisfaction, operations, and billing - all tied to one relationship.
1: Understand the full context
- Recognizes: Emma is a VIP client (pulls from CRM integration).
- There are two linked issues: shipping & billing.
- A quick, high-quality resolution is vital for retention.
Step 2: Multi-system investigation
Shipping & Logistics
- Agentic AI connects to the order management system.
- Finds: Order was marked as shipped 3 days ago. Tracking info shows package is stuck at a regional hub.
- Express shipping fee was incorrectly applied due to a default setting in the checkout process.
Billing
- Pulls the invoice data and confirms the express shipping charge.
- Verifies Emma selected standard shipping.
- Identifies the error pattern has occurred with other users too.
3: Autonomous resolution
- Initiates a refund for the express shipping charge (based on policy).
- Updates the invoice and emails a corrected copy to Emma.
- Contacts the logistics partner via API to prioritize the package release (based on VIP flag).
- Logs a defect in the checkout logic that auto-applies express shipping.
4: Proactive, personalized response
Agentic AI sends Emma a personalized message: “Hi Emma, we’ve located your package and prioritized delivery—it should arrive within 24 hours. We’ve also refunded the incorrect express shipping charge and sent you an updated invoice. Apologies for the inconvenience—we appreciate your continued business!”
5: Learning & Prevention
- Flags the express shipping bug for engineering.
- Suggests a UI improvement or logic rule to product owners.
- Marks the case as a training scenario for similar issues.
- Updates Emma’s CRM profile with this interaction for future context.
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Resolution by AI Agent
1: Keyword matching
It picks up on “laptop”, “access”, and “new hire”.
2: Siloed support
- Responds with links to knowledge base articles about onboarding policies.
- May offer: “Please submit a hardware request” or “Contact IT for access issues.”
3: Limited automation
- It might open two tickets: one for IT to handle the laptop, and another for app access.
- These tickets land in queues, and someone has to manually coordinate between HR, IT, and Security.
Summary IT Service
AI agent:
- No context awareness.
- Treated each issue (laptop, app access, and new hire onboarding) separately.
- No awareness of pending or prior requests.
- Does not monitor progress or take further action.
Agentic AI by ServiceNow:
- Multi-department coordination.
- Dynamic workflow correction.
- Automated escalation.
- End-to-end context awareness.
- Personalized updates to stakeholders.
- Feedback-based optimization.
Resolution by Agentic AI
Agentic AI interprets this as a blocker to onboarding, not just a ticket.
1: Understand the objective
- Realizes: Elena needs to be ready to work on Day 1. That includes hardware, app access, and provisioning.
- Launches a contextual investigation.
- Pulls Elena’s profile from the HR system (e.g., Workday via integration).
- Checks the onboarding journey status:
✅ Background check complete
✅ Offer accepted
❌ Laptop not provisioned
❌ App access not granted
2: Cross-departmental workflow activation
IT Operations
- Checks the asset management system (via CMDB) and finds a laptop request was submitted but stuck in approval.
- Agentic AI escalates the approval or reroutes it to a backup approver automatically.
Enterprise Applications / Security
- Detects that app access was never triggered due to a misconfigured user role in Active Directory.
- Corrects the role assignment and begins provisioning the required apps (e.g., SAP, Salesforce, Slack).
Facilities (if needed)
- If onboarding includes physical setup, Agentic AI checks space reservation and building access workflows.
- Finds no badge request was made → initiates one automatically.
3: Proactive Communication
- Responds to HR: “Thanks for your message. Elena’s laptop request was awaiting approval—we’ve escalated it. Her app access is now being provisioned based on her role, and building access is being arranged. We’ll confirm once everything is ready for her Day 1.”
- Updates Elena directly (if enabled), guiding her through what to expect on Day 1.
4: Feedback, learning, and prevention
- Logs that onboarding flow was delayed due to misconfigured roles.
- Suggests improvements to the onboarding template or triggers a policy review.
- If multiple new hires had the same issue, it could recommend automation fixes.
Resolution by AI Agent
1: Keyword-based ticketing
- Picks up “offline,” “alert,” and “urgent.”
- Suggests restarting the unit or checking the manual via KB article.
2: Creates a basic work order
- Generates a ticket for Field Service.
- Assigns it to a general technician.
- No prioritization beyond "urgent" tag.
3: No situational awareness
- Doesn’t check device logs, past incidents, or inventory.
- Doesn’t pre-validate parts needed or technician skill match.
Summary Field Service
AI agent:
- Did not assess the severity or context of the equipment failure.
- Did not coordinate notifications to key teams.
- Didn't prioritize, causing queue delays.
- Couldn't launch or track resolution workflows across teams.
Agentic AI by ServiceNow:
- Asset diagnostics from IoT (sensor data).
- Smart technician assignment.
- Part & stock pre-checks.
- Cross-department notifications.
- End-to-end mobile work order.
- Predictive maintenance update.
- Real-time customer updates.
Resolution by Agentic AI
Agentic AI treats this as a mission-critical production incident, not just a field request.
1: Contextual understanding & prioritization
- Identifies the asset involved from IoT integration + CMDB.
- Flags the impact: Production line halted = critical business loss.
- Recognizes location = remote site → extra logistics consideration.
2: Real-time diagnostics
- Pulls telemetry data from the unit via connected sensors.
- Identifies a temperature sensor failure and power fluctuation.
- Cross-checks:
- Last maintenance date: 7 months ago.
- Similar failures reported in other units using the same sensor model.
- Warranty status: Still active.
3: Smart field response planning
- Determines that a certified HVAC technician is needed (not general field support).
- Checks technician schedules, skills, and proximity → assigns most qualified tech available within 2 hours.
- Prepares a mobile work order with:
- Fault diagnosis
- Past logs
- Required replacement sensor
- Instructions
- Warranty note (for no-charge repair flag)
- Notifies the technician and reserves the required part from the closest service van stock.
4: Cross-team coordination
- Notifies manufacturing operations of the ETA and repair plan.
- Alerts procurement if sensor stock is running low.
- Flags engineering for further analysis of similar sensor failures.
5: Live updates and resolution
- Keeps the site manager informed: “A certified technician is on the way with the necessary part. Estimated fix time: 90 mins after arrival.”
- After resolution, Agentic AI logs the fix, triggers a maintenance review, and updates the predictive maintenance schedule to prevent recurrence.
