IT support has traditionally relied on technicians moving through requests one at a time. An employee reports an issue, a technician gathers the relevant details, investigates the cause, applies a resolution, records the outcome and moves on to the next request.
That model works well for complex problems, but it can also leave skilled IT staff spending substantial time on repeatable tasks.
A new approach is emerging around software that can take responsibility for defined stages of that process. Rather than simply answering a question, an AI agent can be assigned a specific IT workflow, from receiving a request and gathering information to carrying out approved actions and recording what happened.
The broader shift is about rethinking how routine support work is divided between people and technology.
An AI Agent For IT Support
An example is Robin by Atera, an AI technician that remediates Tier-1 and complex Tier-2 technical incidents end to end autonomously taking real actions on devices, servers, mainframes, and networks, without needing a technician in the loop.
Robin can receive requests through channels such as email, Microsoft Teams, Slack, the Atera Customer Portal and third-party IT service management tools. It can then gather context, ask follow-up questions, search company knowledge, and determine whether the request can be handled automatically or should be passed to a technician.
In practice, Robin resolves up to 92% of Tier-1 and complex Tier-2 technical incidents autonomously, without a technician in the loop.
That workflow is different from a conventional chatbot because the agent is designed to participate in the process rather than simply provide information.
From Answering Questions To Taking Action
The distinction between an AI assistant and an AI agent is becoming more important as businesses experiment with autonomous systems.
A chatbot may explain how to reset a password. An agent can be designed to identify a password-related request, determine the appropriate workflow, carry out an approved reset, and record the result.
Robin’s workflow follows that model. Atera says the system can analyse a request, choose a resolution path, execute approved actions on devices or in the cloud, and use predefined playbooks when certain conditions are met.
The broader shift toward agents is also creating new questions about how businesses manage these systems. TechRound has examined the new cybersecurity challenge created as organisations give AI systems greater access to workplace processes and software.
The issue is not limited to IT departments. Businesses are increasingly considering whether specific tasks handled by people can instead be assigned to software that operates within defined boundaries.
A Technician’s Workflow Broken Into Steps
Where AI agents add real value is in the follow-through. Robin, for example, can ask clarifying questions, search internal knowledge, and use customer-specific instructions before choosing a resolution path, then execute approved actions on devices or in the cloud.
Where an action needs approval, the workflow routes the request to the appropriate person rather than proceeding unchecked, and once work is complete, Atera says Robin updates the ticket with the outcome and escalates unresolved cases to a technician with a summary of what’s already been done.
That shifts the technician’s role. Instead of manually working through every stage of every request, the technician becomes the escalation point, stepping in for cases that need judgment or intervention rather than routine execution.
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The Rise Of Digital Workers
The same idea is appearing outside IT. Businesses are experimenting with agents that support customer service, administration, research, finance, operations, and other functions.
TechRound has also explored whether small businesses and AI agents could change how companies approach routine knowledge work.
For IT teams, the attraction is easier to understand because many support requests already follow repeatable processes. Password resets, application installation, device setup, troubleshooting, and other common requests can often be expressed as sequences of actions and decisions.
That does not mean every IT problem can be reduced to a workflow. Complex incidents often require context that is difficult to capture in advance. Human technicians also remain responsible for decisions that involve unusual circumstances, competing priorities, or organisational judgment.
Where the Human Technician Still Matters
The arrival of AI agents does not remove the need to define responsibility. It makes that responsibility more explicit.
An agent needs access to the systems relevant to its role, instructions that define what it can do, and rules for when a person should take over. Those boundaries become especially important when an agent can perform actions rather than simply generate a response.
Forbes has explored the wider uncertainty around AI agent adoption, noting that the technology is attracting significant attention while businesses continue to work out what practical agent-based systems should look like.
AI Helpdesks And The New IT Model
AI support is already becoming part of broader helpdesk discussions. Web hosting providers, managed service companies, and internal IT departments are examining how agents can handle initial requests while human specialists focus on more complicated work.
A recent AI helpdesk discussion from MamboServer looks at how AI can be incorporated into support operations. IpCisco has similarly examined AI agents in IT and the situations in which organisations might consider automated handling for particular requests.
The emerging model is less about replacing an entire IT department and more about dividing the workload. Agents can take responsibility for clearly defined processes, while technicians retain ownership of problems that need human expertise.
What Comes Next For IT Technicians?
AI agents are giving businesses another way to organise technical support. Instead of treating AI as a tool that simply sits alongside the helpdesk, companies can assign it a defined role within the workflow itself.
Robin represents one version of that approach. It receives requests, gathers information, works through defined resolution paths, executes approved actions, records outcomes and escalates cases when human involvement is needed.
The important question for IT teams may therefore be less about whether AI will become part of the helpdesk and more about which responsibilities are suitable for an agent, which require human judgment, and how the two should work together.
