Artificial Intelligence: Agentification – The Benefits of AI Agents Doing (Some of) Your Work

As artificial intelligence (AI) capabilities evolve, the IT service management (ITSM) opportunities shift from isolated use cases, such as virtual agents, to more holistic and transformative use cases. This has been termed “Agentification,” with the term “Agentic AI” also in vogue.

In the context of ITSM, particularly within IT service desk operations, Agentification is a major step change in what’s possible with AI. It involves deploying autonomous, intelligent AI agents that carry out complex, goal-oriented tasks, such that the AI no longer just supports humans but now actively contributes to the effective processing of tickets.

This blog explores what Agentification is, its benefits to businesses and individuals, examples of how it’s reshaping ITSM operations and roles at the IT service desk, and the challenges IT leaders must navigate to implement it successfully.

Agentification explained

Agentification is the assignment of work to AI-powered software agents. Importantly, this isn’t just the automation of steps but the enablement of software to think, act, and make decisions.

Unlike traditional chatbots or scripted automation, Agentic AI agents are goal-oriented, context-aware, and capable of multi-step execution. They are often also described as being:

• Autonomous – working independently once given a goal or instruction
• Adaptive – learning from interactions and outcomes to improve their outcomes over time
• Interoperable – interacting with multiple tools, data sources, and other AI agents or humans

Agentification turns ITSM AI capabilities into what the IT industry has termed “digital co-workers.”

The benefits of agentification

To best understand how Agentic AI will help your organization, you must view the benefits through different lenses. The examples below take an IT service desk view across three different perspectives.

At a business and IT service desk level, Agentic AI offers:

• Greater availability – with agents working 24×7.
• Improved service quality – with faster resolutions (with many incidents resolved instantly), consistent responses, and reduced error all contributing to better IT experiences.
• Lower operational costs – AI can improve cost-effectiveness by handling thousands of interactions in a shorter period of time.
• Scalability – AI capabilities can easily scale IT support capacity during peak periods or company growth.

For an individual providing IT support, Agentic AI offers:

• Reduction in workload– for example, it can undertake repetitive ticket triaging or data entry.
• Higher-value IT support roles – with AI taking on the repetitive tasks, IT professionals can focus on more strategic IT support tasks, improving the end-user experience, and leveraging innovation to improve operations and outcomes.
• New skills – both in moving to higher-value IT support activities and the growth in digital abilities that come with AI use and “collaboration.”

For end-users, Agentic AI offers:

• 24×7 availability – with IT support always available on-demand, even outside of business hours.
• Instant IT support – with Agentic AI, there’s no waiting in IT service desk telephone queues or for email responses for basic IT issues.
• Better IT support experiences – not only due to the availability and speed but also through personalized, contextual help based on the end-user’s incident history and behavior.
• Proactive notifications – Agentic AI can warn end-users of known issues or suggest preventive actions (and via their preferred communication method).

Examples of Agentic AI in action

For IT service desks, example Agentic AI use cases include:

• Triage agents that read incoming tickets, classify them, assign priority, and route them to the correct resolution group (which could be another AI agent).
• Virtual support agents that troubleshoot end-user issues via chat, run scripts, and create IT service desk tickets when needed.
• Knowledge agents that extract insights from resolved tickets and automatically update knowledge base articles.
• Escalation agents that monitor ticket queues and service performance to escalate or reassign at-risk tickets.
• Problem management agents that detect patterns among incidents to identify potential problems.
• Onboarding agents that automate the IT elements of employee onboarding across systems.
• Sentiment monitoring agents that assess end-user satisfaction and emotional tone in service interactions.

The potential pitfalls of agentification

Agentification is not without challenges, though, and IT leaders need to manage the associated risks to help ensure successful adoption. These potential pitfalls include:

• Unrealistic expectations – business leaders might expect Agentic AI to immediately work to reduce ticket volumes and IT support costs, eliminate errors, or make the IT service desk “hands-free.” This can lead to frustration if the agents need “tuning” and exceptions require human input.
• Not adequately managing job loss concerns – given that Agentic AI agents can replace tasks and potentially some roles. This is part of a larger need for organizational change management (OCM) to help with change resistance.
• Insufficient human oversight – AI agents might misclassify or mishandle incidents, or fail to understand complex or emotionally charged end-user interactions.
• Poor data quality – AI agents rely on information sources such as historical ticket data, configuration management database (CMDB) records, and end-user behavior patterns. Unfortunately, inaccurate, outdated, or inconsistent data leads to bad recommendations and faulty actions.
• Security and compliance risks – autonomous agents interacting across systems can pose risks if they make access changes incorrectly or act on spoofed or unauthorized input.
• AI bias and the need for decision transparency – if AI agents make decisions, they must be explainable and fair (with biased outcomes due to skewed training data avoided).

Microsoft Co-pilot studio supports the creation and management of autonomous AI agents and Provance ServiceTeam has incorporated agentification in the product.

Here are some more resources we think you might be interested in:

Blog Post: The Human Touch in AI Adoption

Blog Post: How AI will Influence Core ITSM Capabilities

Blog Post: AI Driven ITSM: Pioneering Workload Management for the Future

Blog Post: Microsoft Copilot: The AI and Automation Opportunity for ITSM

Whitepaper: Cloud Lighthouse Crafting Your Future-Ready Enterprise AI Strategy

Stephen Mann is Principal Analyst and Content Director at the ITSM-focused industry analyst firm ITSM.tools. Also an independent IT and IT service management marketing content creator, and a frequent blogger, writer, and presenter on the challenges and opportunities for IT service management professionals.

Other posts by Stephen Mann include:

Why and Where ITSM Needs ITAM, The Evolution and Benefits of ITSM Tools, Why and How Your ITSM Capabilities Need to Change and The Skillsets IT Service Desk Agents and Managers Need in the Age of AI

Provance® sponsored the publication of this blog post to help inform and educate you about AI and ITSM.

Provance empowers organizations with—AI-infused—Microsoft-centric IT Service and Asset Management products. Our ServiceTeam® ITSM and ServiceTeam® ITAM Power Apps, built on the Power Platform, maximize investments in Microsoft technologies. Leveraging the Azure, Dynamics 365, and Microsoft 365 clouds, Provance Power Apps posses the same digital DNA as the Microsoft platform and products ecosystem that drives your success. ServiceTeam ITSM ensures secure, scalable, and flexible IT service management, while ServiceTeam ITAM lets you proactively plan and manage IT assets cost-effectively. Achieve “best-of-platform” benefits along with service management excellence with ServiceTeam.