Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By James O’Regan, product marketing for Stratusphere UX and CommandCTRL at Liquidware
If you’ve attended any vendor event or read any product roadmap in the past twelve months, you’d think AI is about to transform end-user computing overnight. Every slide deck has the same message: AI-driven automation, AI-first everything.
That’s not how technology adoption works in real IT departments.
The reality for EUC teams in 2026 will be messier and more uneven. Some organizations will see genuine value from AI in their monitoring and troubleshooting workflows. Many others will still be figuring out the basics: consistent telemetry, reliable baselines, and clear ownership of issues.
What follows are five predictions I’m confident about for the year ahead. None of them are revolutionary. They extend trends already emerging in the market. But taken together, they paint a picture of what EUC teams should actually be preparing for, beyond the conference keynote version.
1. AI Won’t Replace EUC Monitoring Tools. It Will Be Absorbed into Them.
A year ago, there was speculation that standalone “AI for IT” platforms would emerge as a new category. That hasn’t happened, and I don’t expect it to.
Instead, AI capabilities are being absorbed into existing monitoring and DEX platforms as features. Natural language querying, anomaly detection, automated correlation: these are becoming table stakes, not differentiators.
What this means for EUC teams: Don’t evaluate “AI tools” as a separate category. Evaluate how your existing vendors are integrating AI into workflows you already use. The question isn’t “should we buy AI?” It’s “does AI make our current tools more useful?”
2. The Visibility Gap Will Widen.
AI is only as good as the data underneath it. Teams with comprehensive telemetry, established baselines, and clean data will get value from AI-assisted troubleshooting. Teams without these foundations will not.
This creates a widening gap. Organizations that invested in observability over the past few years are positioned to benefit. Those still relying on patchy data collection and reactive troubleshooting will fall further behind, not because AI is bad, but because AI amplifies whatever you already have.
The architecture matters too. AI works best when it can query a centralized data lake rather than pulling from fragmented sources. Some vendors are building their platforms this way: aggregating endpoint telemetry, user experience data, and application performance into a single repository that AI can query holistically. Others are bolting AI onto siloed data stores and hoping for the best.
What this means for EUC teams: If your telemetry is inconsistent or your baselines don’t exist, AI won’t fix that. It will just help you reach the wrong conclusions faster. Visibility comes first. Centralized data comes second. Then AI.
3. AI-Assisted Troubleshooting Will Reward Prepared Teams (and Frustrate Everyone Else).
The demos look impressive. Ask a question in natural language, get an instant root cause analysis. The technology works. The question is whether your environment is ready for it.
In environments with consistent telemetry, clean data, and clear ownership, AI-assisted troubleshooting will genuinely accelerate triage and resolution. Teams will resolve issues faster and spend less time digging through logs.
In environments with years of accumulated complexity, inconsistent naming conventions, and unclear escalation paths? The same tools will frustrate. Not because the AI is broken, but because AI amplifies whatever state your operations are already in.
What this means for EUC teams: AI-assisted troubleshooting is coming. The value you get from it depends on your readiness. Teams with solid foundations will pull ahead. Those without will wonder why the technology isn’t delivering what the demo promised.
4. Shadow AI Will Become an EUC Governance Problem.
Users aren’t waiting for IT to roll out AI. They’re already using ChatGPT, Copilot, Gemini, and dozens of other AI tools to troubleshoot issues, write scripts, summarize documents, and automate tasks.
Most EUC teams have limited visibility into what AI applications are running on endpoints, how often they’re used, and what data they’re accessing. That’s a governance gap that will become harder to ignore in 2026.
Security and compliance teams are already asking questions. Which AI tools are in use? Are they approved? What data is being shared with them? EUC teams without answers will find themselves in uncomfortable conversations.
What this means for EUC teams: You need visibility into AI usage across your endpoints. Not to block it, but to understand it. Shadow AI is the new shadow IT, and it’s growing faster.
5. Proactive IT Will Become the Expectation, Not the Aspiration.
For years, proactive IT has been a goal on roadmaps and strategy decks. Something to work towards. In 2026, it becomes the baseline expectation.
AI makes proactive issue detection achievable at scale. Degradation is spotted before users notice. Patterns are identified before they become outages. Problems are resolved before tickets are raised.
Leadership teams are starting to understand that this is possible. Which means “we didn’t know” no longer counts as an acceptable answer. Teams still operating reactively will face harder questions about why issues weren’t caught earlier.
What this means for EUC teams: The bar is moving. If your peers catch issues before users complain, and you don’t, the gap will be visible. Proactive isn’t a nice-to-have anymore. It’s becoming table stakes.
Where This Leaves EUC Teams
None of these predictions requires believing that AI will revolutionise EUC overnight. They’re grounded in what’s already happening: uneven adoption, capability gaps, and a slow shift in how IT success is measured.
The teams that will benefit from AI in 2026 are the ones doing the groundwork now: building visibility, establishing baselines, and creating processes that AI can accelerate rather than replace.
Everyone else will keep firefighting. Just with fancier dashboards.
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ABOUT THE AUTHOR
James O’Regan leads product marketing for Stratusphere UX and CommandCTRL at Liquidware, where he also serves as Community Lead. With 21 years in end-user computing, he writes about digital employee experience, real-time remediation, and what AI will change in EUC. He hosts two podcasts: Impact of AI: Explored, where he cuts through AI hype to find what actually works, and Liquidware Chats, featuring conversations with Liquidware partners and the broader EUC community.
