“Think of digital transformation less as a technology project to be finished than as a state of perpetual agility, always ready to evolve for whatever customers want next, and you’ll be pointed down the right path.”
— Amit Zavery | President, Chief Product Officer, and Chief Operating Officer| ServiceNow
Enterprises are prioritizing digital transformation and agility, yet most lack the structural readiness for what's next. When 95% of financial services professionals believe there's little to no risk in delaying system modernization, even as the UK's FCA issued over £319 million in fines for non-compliance in just six months, it's clear many are mistaking surface upgrades for true adaptability.
The problem isn't technology adoption. Companies have modernized customer-facing systems like CRM (96%), ERP (97%), and marketing automation (96%), yet 32% of CIOs still cite legacy integration as their primary obstacle. Systems exist in isolation, and coordination between them has become its own form of technical debt.
No matter how modern your ERP or flexible your CRM, if decisions still wait in queues you’re orchestrating manually and de-evolving the satisfaction of your customer’s experience.
This is where agentic AI finds usefulness. It integrates a new operational design layer that enables systems to recognize each other, aligns actions with context, and helps enterprises proactively manage complexity.
Identifying Ideal Entry Points for Agentic AI Use Cases
Below are four verticals where enterprise-ready adoption can begin meaningfully:
Telecom – Anomaly Detection and Configuration Updates
Where the agentic AI use case fits: An agent identifies irregular patterns, isolates affected nodes, and either remediates directly (e.g., config reset) or initiates a controlled escalation, before customers even report the issue.
Ideal for: Telecom operations needing proactive service assurance and fast, autonomous incident containment.
iOPEX’s Anomaly Detection and Config Management Command Agents work autonomously to deliver smart remediation and configuration compliance across telecom stacks
IT Operations – Detection-to-Action Pipelines
Example: SOC or TAC teams handling relentless alert volumes.
Traditional SecOps platforms flag cybersecurity threats. Analysts then correlate signals, prioritize threats, and manually initiate response workflows. This creates bottlenecks, especially when the response logic is repetitive but spread across tools.
Where agentic AI use case fits: Agentic agents monitor logs across tools, detect anomalies that signal emerging issues, and autonomously trigger remediation scripts, user alerts, or ticket creation within policy-defined thresholds.
Ideal for: Reducing mean time to detection (MTTD) and mean time to resolution (MTTR) in always-on environments.
iOPEX’s IT Incident Management Command Agent analyzes logs in context, classifies anomalies, and initiates real-time resolution, minimizing manual triage and ticket volume.
Media – Campaign Performance and Creative Optimization
Example: Marketing teams juggling ad campaign performance across platforms while coordinating creative development and approvals. Data exists from clicks, conversions, and audience signals, but drawing insight fast enough to adapt creatives or optimize spend is often delayed.
Where Agentic AI use case fits: Agents track campaign metrics in real time, flag performance dips or outliers, and recommend creative shifts based on historical outcomes or audience behavior.
Ideal for: Agile media teams needing rapid feedback loops between data, creative, and spend decisions.
iOPEX’s Creative Intelligence Command Agent analyzes performance data and orchestrates campaign responses, from copy tweaks to spend redistribution, at machine speed.
Finance – Contract Assurance and Accounts Payable Automation
Example: Procurement or payment flows where discrepancies between documents (POs, invoices, delivery receipts) are common. Here, volume isn’t the issue; exception handling is. Traditional automation flags mismatches. Then a human reconciles, reaches out, or holds payment.
Where Agentic AI use case fits: Agentic systems monitor data streams across platforms, detect mismatches, and initiate next steps autonomously, like requesting clarification, triggering a policy pause, or updating internal systems.
Ideal for: High-volume finance operations where accuracy, traceability, and speed must coexist.
iOPEX’s Contract Assurance Command Agent and A/P Automation Command Agent work across ERP, procurement, and accounting systems to ensure intelligent exception handling and real-time policy enforcement.
Other verticals like healthcare and retail also have avenues for increased operational edge of agentic AI. For example, with Agentic AI in healthcare, you can have command agents that can auto-trigger lab orders based on EHR thresholds, verify drug availability across pharmacy systems, and escalate clinical edge cases without delays.
For Agentic AI in retail and e-commerce use cases, command agents continuously monitor stock levels, infer intent from abandoned carts, and autonomously launch restock or promotional workflows.
Designing For The Right Kind Of Autonomy
Autonomy doesn’t mean invisibility, and it is important that every action taken must carry with it a rationale that’s audit-ready (summarized, traceable, and aligned with policy).
This is precisely why priority must be placed on governance-first frameworks. iOPEX, as ServiceNow’s launch partner for Creator Workflow Solutions, helps organizations adopt agentic systems not just technically, but responsibly. Our ElevAIte platform, built atop ServiceNow Creator Workflows, allows enterprises to design agentic pipelines with embedded policies for:
- Scoped permissions
- Escalation thresholds
- Cost containment
- Compliance enforcement
iOPEX’s ElevAIte platform has been instrumental in helping cybersecurity vendors turn policy into intelligent automation. In one such case, our agentic system enabled a seamless threat response pipeline, parsing firewall logs, prioritizing vulnerabilities, and auto-generating response plans, all while aligning each action to scoped permissions and audit-ready logic.
The result led to 60% of incidents remediated without human touch, a 75% drop in TAC workload, and faster resolutions, all proof that when autonomy is designed right, it scales both trust and impact. To see any of these agentic AI use cases in action, book a demo with our expert team today.
