For decades, IT support has been structured around tiers. Level 1 handles the basics — password resets, access requests, connectivity issues. Level 2 picks up what they can't resolve. Level 3 owns the complex stuff. It's a model built around the assumption that you need humans to triage, sort, and route every single request that comes in.
AI is dismantling that assumption right now.
Level 0 and Level 1 Are Becoming Automated Functions
Agentic AI tools are already capable of handling the highest-volume, lowest-complexity incidents without a human touching them. Password resets. Account unlocks. Software provisioning. Basic troubleshooting flows. These aren't futuristic capabilities — they're being deployed today.
As these tools mature, the volume of tickets that actually require a human agent will shrink significantly. That's not a maybe. That's the direction this is heading.
So what happens to the humans?
The Tiers Redesigned
Here's what I believe is coming: the traditional separation between service desk and EUC support disappears. These two functions — historically siloed, often in tension — converge into a single, unified support team.
And tiered support as we know it gets redesigned. The Level 1, Level 2, Level 3 structure was built for a world where humans had to manually sort and escalate every request. AI eliminates that need. When a system can triage, classify, and resolve the majority of incoming incidents automatically, the handoff model that tiered support depends on becomes redundant.
What replaces it is a single, skilled team operating without the traditional boundaries. They won't be reading off scripts or following basic decision trees. By the time a ticket reaches a human, it will already have gone through AI triage. The easy ones will be gone. What's left will require real investigation — deeper diagnostics, cross-system thinking, nuanced judgment.
The merged team owns that space. They handle the incidents that demand actual thought, and swarm when needed, while AI handles the volume beneath them. Here's what this looks like:
- The AI Orchestrator is the day-to-day operator of the AI engine. This is the person who monitors how the AI is performing, feeds it accurate resolution data, flags gaps in its knowledge base, and ensures the responses it generates are correct and aligned with how the business actually operates. Think of this as the quality control layer — the human in the loop who keeps the AI honest. This role evolves directly from today's experienced support professional, and it's where most of the team will operate.
- The AI Engineer goes a level deeper. This role is responsible for configuring, tuning, and improving the AI models and automation workflows that power the support function. They work at the intersection of IT operations and AI development — understanding how the tools are built well enough to shape how they behave. This isn't a developer role, but it requires more technical depth than a traditional support background. It's the bridge between the team running the AI and the systems underlying it.
- The AI Architect is the strategic layer. This role designs the overall AI support model — determining which functions get automated, how AI and human workflows connect, what governance frameworks are in place, and how the support function scales over time. Critically, the AI Architect is responsible for ensuring the entire model is aligned with business outcomes — not just operational efficiency, but the broader goals of the organization the support function exists to serve. The AI Architect thinks in systems, not tickets. This is a leadership-adjacent role that requires both technical vision and a deep understanding of how the business operates.
Together, these three roles replace what used to be a rigerous tier structure with something more purposeful. Each one requires a different skill set, a different level of seniority, and a different relationship with the AI — but all three are grounded in the same principle: the AI is only as good as the people governing it. If nobody is auditing the outputs, validating the logic, and course-correcting when it gets something wrong, the whole model breaks down. That accountability has to live somewhere — and it lives with this team.
And that changes everything about what an entry level role in IT support looks like. Entry level will mean something different — and those coming into the field will need to arrive ready to meet that bar.
IT support isn't shrinking. It's growing up.
The Skill Set Has to Evolve — Full Stop
This shift makes certain skills non-negotiable going forward. Whether you're a seasoned technician or someone trying to break into the field, the expectations are changing — and the time to get ahead of them is now.
For Experienced Technicians
Cloud fluency isn't optional anymore. If your organization is running Microsoft 365, Azure AD, AWS workloads, or any hybrid environment — and most are — your support staff needs to understand how those environments work. Not at an architect level, but enough to troubleshoot effectively when something breaks in the cloud layer.
Cloud certification should become a baseline expectation for this unified support role. Whether that's AZ-900 as a starting point, or something more hands-on like AZ-104, AWS Solutions Architect Associate, or CompTIA Cloud+, the expectation needs to shift. These aren't stretch goals for ambitious technicians anymore. They're table stakes.
But technical skills are only half the equation. As AI takes over the transactional work, the interactions that reach a human will increasingly be the ones that are complex, frustrating, or high-stakes for the person on the other end. That means soft skills and emotional intelligence aren't nice-to-haves anymore — they're core job requirements.
The ability to communicate clearly under pressure, read the room, de-escalate a frustrated user, and show genuine empathy in a difficult moment — these are the skills that separate a good support professional from a great one. And they're exactly the skills AI can't replicate. Organizations that invest in this kind of development will build teams that users actually want to interact with, not just tolerate.
The technicians who thrive in this model will be the ones who can think across layers — endpoint, identity, network, cloud — and connect with people at the same time. Technical depth and human skill, in the same role.
For Those Breaking Into IT
The path into IT support still exists — it just looks different now. The traditional "start at the help desk and answer tickets" entry point is narrowing. What's opening up is something better. Here's where to focus:
Start with foundational certifications. CompTIA A+ and Google's IT Support Professional Certificate are still solid entry points that signal baseline technical competency to hiring managers. From there, layer in cloud — Microsoft's AZ-900, AWS Cloud Practitioner, and Google Cloud's Digital Leader certification are low-cost, accessible, and increasingly expected. For those who want to go deeper, AWS Solutions Architect Associate or Microsoft's AZ-104 demonstrate hands-on cloud capability that will set you apart.
On the degree side, a four-year degree in Information Technology, Computer Science, or Information Systems is still a credible foundation — but it's not the only path. Bootcamps and community college programs focused on cloud, cybersecurity, or IT support have produced strong candidates who are job-ready faster and at a fraction of the cost. What matters more than the credential is what you can demonstrate.
That's where projects come in. Build a home lab. Set up a virtual environment using free tiers from AWS or Azure and practice troubleshooting real scenarios. Deploy a ticketing system like osTicket and document your process. Contribute to open source projects. Build something — anything — that shows you can apply what you know in a real context, then learn how to showcase it in your GitHub. Hiring managers in this new model aren't just looking for certifications on a resume. They want evidence of curiosity, initiative, and the ability to figure things out.
Build people skills deliberately. Take a course in communication, conflict resolution, or customer experience. These aren't soft — they're the differentiators that will set you apart in a field where AI is handling the easy technical work. The humans who get hired will be the ones who can handle the moments that require real judgment and empathy.
Get comfortable with AI tools. You don't need to be a developer, but you do need to understand how AI-driven support tools work — how to interact with them, identify when they're wrong, and improve them over time. Hands-on experience with platforms like ServiceNow, Freshservice, or even consumer AI tools builds the intuition you'll need.
The Future Model Is Built Around People — And That's the Point
Here's the bigger idea underneath all of this: the support model of the future has to be built around people and how they actually work. Not around ticket queues. Not around SLA targets. Not around org chart hierarchies that made sense in 2005.
For too long, IT processes have asked end users to adapt to the system. Submit the ticket this way. Wait in this queue. Follow this script. The assumption was always that the process was fixed and the person had to fit into it.
That has to flip. AI gives us the opportunity — frankly the obligation — to design support around how people work, how they communicate, and what they actually need to stay productive. The processes have to move to meet the user, not the other way around.
This is what the unified support team makes possible. When AI absorbs the routine volume, the humans left in the room can focus on what machines can't do well: context, empathy, judgment, and real problem-solving. The role becomes less about processing requests and more about serving people.
IT leaders who understand this won't just redesign their org charts. They'll redesign their entire operating model — workflows, tooling, SLAs, hiring profiles — around this principle.
What This Means If You're Leading an IT Team
If you manage a service desk or EUC function, the question isn't whether this change is coming. It's whether you're getting ahead of it.
Start by auditing what your team actually spends time on. If a significant portion of daily ticket volume is Level 0 or Level 1 work, that's your AI runway — and your roadmap for where to invest in upskilling.
Think about what a merged, cloud-competent, AI-governing support function looks like for your environment. What does the job description change to? What certifications do you expect at hire? What does your onboarding track look like when cloud knowledge, AI oversight, and emotional intelligence training are all baseline expectations?
And then ask the harder question: are your current IT processes designed around how your people work — or around the system's convenience?
The Teams That Get Ahead of This Win
The organizations that treat this as an opportunity — to build a leaner, more capable, more human-centered support function — will come out ahead. The ones that wait for disruption to force their hand will be reactive and behind.
The tier model had a good run. But the future of IT support is a unified team that handles what AI can't, governs what AI does, and operates within a model designed around people first.
That's not a threat to the profession. It's an upgrade to it.