There’s no other way to put it; Agentic AI is revolutionising Enterprise Service Management.

Agentic AI are AI systems that can act autonomously with intent, make decisions and execute tasks to achieve specific goals, with minimal human intervention.  Agentic AI can operate autonomously to perceive, plan, and make decisions. It understands context, applies logic and can carry out tasks from start to finish.

Unlike Generative AI, including tools you may be familiar with like ChatGPT, Agentic AI doesn’t need constant prompting to perform tasks for you, and this is why it’s transforming service management as we know it. Agentic AI becomes a team of service agents added to the strength of your human service agents, that work around the clock to identify issues, resolve end-user incidents and provide context-aware information.

Here’s how agentic AI is creating real impact in service management across IT, HR, finance, and beyond.

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IT Service Management (ITSM): Autonomous Incident Resolution and Proactive Problem Management

While IT Service Management (ITSM) platforms provide a single system of record and action for your IT tickets, in systems without AI, there is a great deal of manual work involved in completing tickets. Users log tickets that go to a centralised inbox, agents classify and triage them, diagnosing the issue and researching how to fix it before bringing the ticket to a resolution (hopefully without escalation). Each step requires manual inputs, research and switching to different applications to carry out remediation steps.

With Agentic AI working across your ITSM, many of these manual tasks can be automated, and you can go even further, with the AI able to detect incident patterns to identify problems, provide context-aware support to end-users, and even hand off tasks to other specialised AI agents.

This frees up your service agents to focus on higher value work and ensures that tickets are closed as quickly as possible, with AI offering 24/7 support.

Use Case: Autonomous Incident Resolution

Instead of a user logging an incident for an issue they’re experiencing, you can deflect this from hitting your service desk through the use of AI virtual agents. An AI virtual agent can act as the first layer of support, asking the user about their issue, checking to see what is wrong and performing fixes all without agent intervention.

What does this look like?

1. An end user has an issue with logging into their SAP instance
2. They go to the ITSM platform and engage with a conversational AI
3. The AI checks SAP and can see that the user’s session is locked, and unlocks the session for them
4. The user checks and can now log in; issue resolved!

This speeds up the resolution time as the user was able to get instant support, and has reduced the impact on the IT service team.

Use Case: Proactive Problem Identification

Identifying the underlying problems causing incidents can be tricky, especially with a multi-agent support team that may miss patterns if different agents work on the same types of incidents. Agentic AI can work proactively across your ITSM, assessing incidents and looking for patterns that point to an underlying problem.

What does this looks like?

1. AI agent is deployed across ITSM platform with the specific goal of identifying problems
2. A number of incidents share similar details and point to an underlying problem
3. AI creates a problem record for this and attempts to diagnose
4. If the AI is confident of the remediation, it will carry out the fix autonomously. Otherwise, it is triaged to a human service agent for action.

This accelerates the speed in which problems are identified and reduces the number of problems that slip through the cracks, resulting in fewer incidents logged.

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HR Service Delivery: Seamless Employee Onboarding and Policy Management

While HR teams would love to focus their time on high-value projects and face-to-face time with employees, they’re often saddled with repetitive manual processes that are document-intensive and require a great deal of manual input, like onboarding new employees, managing policy adherence or fulfilling employee requests. Implementing Agentic AI into HR Service Delivery processes can turn these processes into a hands-off experience and give HR back time to focus directly on the human element of their role.

Use Case: Employee Onboarding

Setting up a new employee isn’t as simple as it should be, and with some managers putting through last-minute onboarding requests, it can be difficult to turn around the required work on time to ensure you give a good first impression to your new starter. Using an Agentic AI multi-agent orchestration, you can coordinate onboarding setup by allocating all of the relevant tasks to specialised AI agents.

What does this look like?

1. A new employee onboarding request is submitted
2. The HR agent completes the setup of new starter documents and creates a new employee in your HRIS before allocating tasks to different agents
3. The IT agent provisions the relevant accounts and creates a request for a new laptop to be set up, assigning this to a member of the IT team
4. A Facilities Agent coordinates the provision of a new access key and set up any relevant access
5. The HR agent checks off these tasks as they’re done and collates all the information into a new starter pack, ready for the new employee, their manager and the HR representative to use.

This massively accelerates the speed in which an onboarding request is fulfilled, while simultaneously cutting down the number of paper-based forms that need to be completed and any running around the office asking for these actions to be completed. Best of all, the onboarding process becomes more consistent and you won’t get stuck in the situation of having incomplete steps on the new starter’s first day.

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Risk Management: Patch Management & Control Testing

Risk management and compliance requires constant oversight to ensure you’re staying ahead of threats and maintaining your compliance obligations. Traditional risk management tools provide the framework for maintaining compliance and help you stay on top of tasks, but stop short of resolving them.

A risk management platform that is integrated with your security and maintenance systems and is equipped with Agentic AI can help fill this gap and reduce manual work to mitigate risks. This allows you to deploy AI Agents that constantly scan for risky behaviour and vulnerabilities and remediate or escalate them before they are realised.

Use Case: Patch Management

Patch management is a painful exercise. If you don’t have the right tools in place, it can become very manual or reliant on users, which carries its own risks. But proper patch management is crucial in keeping software vulnerabilities to a minimum. Agentic AI can be used to speed up and automate this process in conjunction with your patch management software.

What does this look like?

1. An AI Agent continuously monitors CVE databases and vendor software updates for new patches and vulnerabilities
2. New release patches are cross-referenced against your Configuration Management Database (CMDB) to check for assets using specific software and whether they’ve been updated.
3. AI agent determines the urgency of patching the software and performs any approval checks required
4. Patch updates are scheduled via your integrated patch management system and any user notifications are sent, including an update to the risk management team.

This reduces risk exposure and speeds up risk mitigation timelines while reducing the manual workload of your IT or cybersecurity team in deploying patches.

Use Case: Control Testing Automation

Control testing is not only a key strategy in risk management, but it’s also a mandatory requirement in meeting your compliance requirements for certifications like SOC2 and ISO27001. To meet minimum standards, human-led control testing will be required, but your can utilise Agentic AI agents to perform addition control testing between your required checks to continually work to minimise risks.

What does this look like?

1. Compliance certification requirements, risk management strategies and control tests are setup in your risk management platform
2. An AI agent is deployed and trained to perform these control tests at regular intervals, when changes are made, or when user activity is flagged as being potentially risky
3. The AI agent performs these control tests, including checking acces rights, encryption protocols and patch levels.
4. Where a configuration or user activity falls outside of acceptable risk levels or breaches policies, the AI agent can either deploy a fix for certain issues or raise a ticket to your risk management team for action.

This helps ensure that you can continue to meet your compliance requirements, keep your cybersecurity risks to a minimum and increase the overall level of risk management in a scalable methodology.

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SecOps Management: Threat Detection and Response

Security Operations (SecOps) is all about speed, precision, and constant vigilance. Traditional SecOps platforms are great at aggregating alerts and logging suspicious behaviour, but without intelligent automation, your team can easily become overwhelmed with noise and false positives.

By integrating your SecOps tools with a platform powered by Agentic AI, you can elevate your threat detection and response from reactive to proactive. AI Agents can continuously monitor telemetry data, detect abnormal activity, and take autonomous action to neutralise threats or escalate high-risk events.

Use Case: Threat Detection and Response

Security teams are often flooded with alerts, many of which don’t require action, but still demand time to investigate. Agentic AI can help teams focus on real threats by automating the detection, triage, and even resolution of security incidents.

What does this look like?

1. An AI Agent continuously monitors logs, endpoint telemetry, and behaviour analytics across your SecOps tools (e.g., SIEM, EDR) to detect anomalies that match known threat signatures or suspicious patterns.
2. Once a threat is detected, the agent assesses severity based on business context, such as asset sensitivity, user role, or past incidents.
3. If the threat meets preconfigured risk thresholds, the AI agent takes action, quarantining affected endpoints, revoking credentials, or blocking access via firewall or identity systems.
4. For complex or unclear cases, it escalates the incident to your SecOps team with full context and recommended next steps
5. The AI updates relevant systems, such as your incident response logs, CMDB, or risk register, and notifies stakeholders across IT and security.

By taking immediate action on threats and streamlining decision-making, Agentic AI reduces mean time to detect (MTTD) and respond (MTTR), helping security teams stay ahead of evolving threats, without drowning in alerts.

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IT Asset Management: Automated Lifecycle Tracking and Compliance Enforcement

IT teams are responsible for managing a constantly shifting landscape of hardware and accessories: laptops, monitors, peripherals, printer supplies, and more. But traditional asset tracking methods often fall short: updates are manual, data gets out of sync, and inventory decisions are reactive rather than strategic.

With Agentic AI, IT asset management becomes smarter and more responsive. AI Agents continuously track stock levels, usage patterns, and equipment assignments, taking action before a shortage or overstock becomes a problem. Whether it’s ensuring the right gear is available for a new starter or reordering toner before it runs out, Agentic AI keeps your hardware ecosystem running smoothly.

Use Case: Inventory Management of IT Hardware and Consumables

Keeping track of physical IT inventory, especially consumables and accessories, can be a constant drain on time and accuracy. Traditional asset tracking systems rely heavily on manual updates and reactive restocking, which leads to delays, over-ordering, or critical shortages.

Agentic AI can take over this repetitive and often overlooked function, monitoring inventory levels in real time and automating the supply chain to ensure employees have what they need, when they need it.

What does this look like?

1. An AI Agent continuously monitors stock levels of hardware and consumables across your asset management system or warehouse tools, covering everything from laptops and monitors to printer toner and docking stations.
2. Usage patterns and consumption rates are analysed over time, allowing the AI to forecast future demand based on seasonality, onboarding trends, or department-specific needs.
3. When inventory drops below threshold levels, the AI automatically raises a purchase request, routes it for approval, and notifies procurement teams to take action, or completes the order autonomously if pre-approved.
4. For user-assigned assets, the AI checks whether spare equipment is available before onboarding a new employee, provisioning the right kit, and updating the CMDB instantly.
5. If hardware goes unreturned after offboarding, the AI flags the issue, triggers reminders, and escalates to facilities or HR if required.

This kind of proactive inventory automation means fewer delays in onboarding, fewer surprise shortages, and better budget control. Agentic AI doesn’t just track what you have—it makes sure the right equipment is available, accounted for, and deployed efficiently, with no manual effort.

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Autonomous, Context-Aware Action Across the Enterprise

Across these use cases of Agentic AI in Enterprise Service Management, we can glean just a small fraction of the value that Agentic AI can yield when applied to service delivery processes. It’s aware of the business environment, understands processes and logic, and can take proactive action and ownership of delivering outcomes. Agentic AI goes far beyond rule-based workflow automation and works to transform and accelerate service delivery.

Servicely’s Enterprise Service Management platform utilises intelligent automation, Generative AI, and, most importantly, Agentic AI, to aid businesses in shifting repetitive or manual work from service agents to AI agents, freeing up service teams to focus on higher value work. You can see a demonstration of multi-agent orchestration below.

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If you’re interested in applying Agentic AI to your service delivery processes, you can get in touch with our team here.

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