Every single time end-of-year rolls around, you get a new barrage of “IT predictions for next year” articles. Most of the time, they don’t say anything new.
Vaguely hopeful, and designed not to offend anyone; you could swap the year on most of them and no one would notice, mine included!
I don’t think 2026 will afford us that luxury.
We’re walking into a year where the pressure on service and support teams is higher than ever. Various reasons contribute to this, including economic tension, rapid AI adoption, new security expectations and an industry still clinging to processes built for a different world. So, instead of recycling the same talking points, let’s talk about what’s actually happening.
Let’s discuss the uncomfortable truths, the shifts we’ve pretended weren’t there and the opportunities hiding inside all the disruption. Here are the 2026 Service Management trends we need to face head-on — the ones that will reshape ITSM, whether we’re ready or not.
1. We finally admit that Incident Management isn’t Service Management
Incident Management has carried too much weight for too long. Somewhere along the way, we convinced ourselves that being good at putting out fires meant we were providing good service.
But deep down, practitioners have always known that Incident Management is the receipt that proves something went wrong. It’s the bill you pay when your technology experiences weren't designed to survive everyday use.
And yet for years, we’ve held it up as the centerpiece of Service Management. I think that 2026 is the year that illusion cracks.
For years, we measured success by speed: speed of response, speed of escalation, speed of closure. Quick reflexes were the whole game. But speed can only hide a fragile system for so long.
In 2026, the metric shifts from reactive heroics to resilient engineering — the kind of quiet, patient, behind-the-scenes work that doesn’t show up on a dashboard until something doesn’t break. We move from counting tickets to counting the absence of avoidable failures.
We start valuing the work that prevents people from having to contact support in the first place. We start building services that survive real-world pressure instead of collapsing under it. And we stop confusing “We handled the outage well” with “This is a well-designed service.”
This doesn’t mean Incident Management disappears, of course. It just stops pretending to be the whole story of Service Management. It becomes what it always should’ve been: a safety net, not the main act.
2. AI eats the work, but it can’t have your culture
AI is going to take work off your plate in 2026. Basic triage, password resets, navigation questions and status checks, even a chunk of troubleshooting — all the stuff that’s basically pattern recognition, is going to get swallowed by automation. And most teams won’t miss that part.
But the catch is that AI is very good at doing what you tell it, and absolutely terrible at understanding why people behave the way they do.
It can route a ticket, but it can’t sense when someone is frustrated because their manager just asked for an update. It can give an answer, but it can’t adjust its tone to match a customer who’s clearly having a rough day. It can look up knowledge articles, but it has no idea which solution “actually works” versus which one is technically correct but always leads to three follow-up contacts.
That gap…the messy, emotional, human stuff…is where culture lives.
Culture is built out of the shortcuts everyone silently agrees to, the accumulated knowledge that never made it into a wiki, the empathy you develop after supporting the same people for five years, the trust you earn by fixing something before someone even asks.
AI can mimic professionalism, but it can’t mimic culture. And customers feel that. Maybe not consciously at first, but they can tell when a support experience has life behind it versus when it’s stitched together from prediction models and polite filler text.
AI can automate tasks. But only people can make an experience feel alive. And the more AI we introduce into support, the more obvious that becomes — because what customers appreciate most about a great IT team isn’t the speed or the scripts. It’s the sense that someone on the other end cares, understands them and is genuinely trying to help.
AI can’t give you that, but your culture can.
3. Experience Management takes center stage while workflow automation takes over
Over the past few years, Experience Management really had its moment. We built voice of the customer programs and feedback loops. We discovered new ways to quantify friction. We journey-mapped everything that moved: onboarding flows, outage communications, the way people request software, even the steps someone takes when their laptop starts making weird noises.
For a while, it felt like we were finally cracking the code. If we could just understand how people felt at each moment, we could orchestrate a better experience. But you can’t deliver a smooth, meaningful experience if your underlying structure is a mess. 2026 is the year that reality hits hard.
As organizations rush to adopt AI, the spotlight shifts away from the shiny “moments that matter” and onto all the unglamorous machinery underneath. It turns out that experience — real, repeatable, scalable experience — depends on the stuff no one brags about on LinkedIn.
Before you can delight anyone, you need:
- Clean workflows that don’t collapse when one person is out sick.
- Strong APIs so your tools can talk to each other without duct tape.
- Structured data that isn’t buried in comments or tribal knowledge.
- Automated processes that handle the predictable work without human intervention.
- Fewer exceptions than there are employees.
- Less “Ask Sally, she knows how to do it” floating around in people’s heads.
This is the part of Service Management nobody wants to prioritize, because it doesn’t feel exciting. There are no confetti cannons for retiring a decade-old workflow or normalizing how a request type is routed.
You can’t put “Reduced the number of undocumented steps in this process from nine to two” on a billboard. But this is the work that makes everything else possible.
In 2026, support and service teams will need to roll up their sleeves and deal with the experience leakage. They start cleaning up the operational plumbing that’s been ignored for years because everyone was too busy chasing satisfaction scores and “moments that matter.”
The voice of the customer programs will come back and innovate. The journey maps will still be maintained and updated. But these will only be meaningful once the stuff behind them stops leaking, wobbling or relying on a single heroic[JL1] employee.
4. AI trainers become a new role in service and support
If 2025 was the year everyone rushed head-first into AI, then 2026 is the year we collectively realize something a little humbling: AI is not a self-driving car. It doesn’t get better on its own. It needs training, supervision, correction and a surprising amount of human coaching.
Basically, everything you’d give a new team member who’s enthusiastic but clueless about your organization’s quirks. And that’s when a new role starts to take shape.
You see it first in the teams that jumped early into automated support. Someone becomes “the person who checks the bot.” At first it feels informal, but gradually that person starts noticing patterns the rest of the team misses: the bot getting overly confident about the wrong fix, the conversations drifting into tone-deaf territory, the AI repeating a bad habit because it learned it from an outdated article. Before long, those observations turn into real responsibilities.
People begin reviewing AI interactions the same way a teacher flips through a stack of essays: looking for misunderstandings, spotting emerging themes, catching the places where the model “sort of” understood the question (but still managed to land ten feet from the target). And because LLMs don’t understand context unless you give it context, support teams end up acting as translators between human reality and machine logic.
The machine becomes more reliable, less chaotic, more aligned with how the team actually wants to serve people. And ironically, the process of teaching the AI forces support teams to confront their own blind spots — all the inconsistencies, shortcuts, contradictions and unspoken norms they’d been operating with for years. Funnily, teaching an AI how your environment works makes you understand your environment better too.
So, in 2026, support teams train AI, coach AI, shape AI and in doing so, improve service design. The more they refine the machine, the more they refine the system it operates within. And that is what ultimately pushes IT toward more resilient, self-healing services.
5. And yes, there will be layoffs
Here’s one of those things people don’t like including in the feel-good “new year predictions” posts. But have you looked at the news? Economic pressure isn’t going anywhere next year.
You can already feel it in the way leaders talk about budgets or how often someone asks “Do we really need this tool?” Organizations are tightening their belts, consolidating platforms and looking harder than ever at what work can be automated or redesigned. It’s not personal; it’s the financial weather we’re all standing in.
Layoffs are a sign that the old way of assigning value — mostly by counting how much reactive work you do — is starting to break down. If your worth is measured by how many tickets you touch and AI suddenly touches half of them, the math changes fast.
The same goes for organizations. If your company prioritizes profitability over people; you aren’t going to be earning much loyalty from your staff.
And the teams who protect themselves aren’t the ones who cling to old responsibilities; they’re the lucky employees who innovate and morph into the new requirements. Less time spent on repetitive ticket-taking means more time spent strengthening experiences before they break. Less constant firefighting means more opportunity to build services that don’t collapse at the first sign of stress. Less process policing means more thoughtful, intentional automation that reduces work instead of masking it.
People who understand how to work alongside AI — who can guide it, refine it and design around it — will be the ones shaping the future of our industry. That’s the skill set companies will fight to keep.
6. Embrace the transition
2026 is the year we recognize the change that’s already happened: slowly, quietly, in the background while we were busy keeping things moving. The year we start naming the truths that have been building under the surface for a long time.
And for teams willing to lean into resilience, culture, automation and transparency, it’s going to be a defining year. A stabilizing year where the work finally feels aligned with the future we’ve been talking about for so long.
The transition is already happening. This is when we choose to take it seriously.