Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
For the past few years, artificial intelligence in IT has been surrounded by outsized expectations and uneven results. Early promises focused on sweeping transformation, but many teams were left with pilots that didn’t quite match the hype. As 2026 approaches, that phase is ending. AI is now reshaping IT in a far more practical and grounded way, driven not by novelty, but by necessity.
Across industries, IT organizations are reaching a breaking point. Ticket volumes continue to rise, cyber threats are growing more complex, and staffing constraints show no sign of easing. In this environment, automation is no longer a “nice to have” experiment or a future roadmap item. It is becoming a baseline expectation for how modern IT environments operate.
At the same time, IT leaders are becoming more precise about what they mean by automation. Traditional, rule-based automations still play a critical role in executing predefined tasks. However, they are increasingly being complemented by autonomous, AI-driven systems that can reason over context, make risk-aware decisions, and act dynamically within defined guardrails when conditions change.
As a result, the central question for IT leaders is no longer whether AI can help, but which responsibilities can be safely and reliably handed off to autonomous systems, and under what controls.
Based on ongoing conversations with IT leaders across multiple sectors, three shifts will define how automation, and the move toward more autonomous operations, reshapes IT in 2026.
Automation Becomes Core Infrastructure
In 2026, automation will move out of the category of optional tooling and into the realm of core infrastructure. IT teams will increasingly expect automated systems to handle routine remediation, ticket triage, and common user-level issues as a default capability.
Historically, automation has often meant predefined workflows that execute specific tasks when triggered. Those systems remain essential. What is changing is the expectation that automation frameworks can operate across broader workflows, interpret signals across the IT environment, and determine the appropriate action without requiring constant human direction.
This represents a meaningful change in mindset. Automation has long been layered on top of existing workflows as an efficiency booster. In practice, that made it easy to deprioritize when budgets tightened or implementations became complex. Over the next year, that approach will no longer be sustainable. The volume and velocity of day-to-day IT work has simply outgrown manual processes and one-off scripts.
As a result, IT leaders will start designing environments with automation assumed from the outset. New workflows will be evaluated based on how easily they can be automated or autonomously managed, not how efficiently humans can execute them. Systems that rely heavily on constant manual intervention will increasingly be viewed as fragile or outdated.
This shift does not eliminate the need for skilled IT professionals. Instead, it redefines where their time is best spent. By pushing repetitive and predictable tasks into automated systems, and allowing more adaptive systems to handle decision-making within defined boundaries, teams can focus their expertise on oversight, improvement, and strategic decision-making rather than constant firefighting.
Higher-Order Issues Move into Automation’s Reach
As large language models and automation frameworks continue to improve, 2026 will mark a turning point in the complexity of tasks these systems can address. What began with basic ticket routing and simple fixes is expanding into more advanced troubleshooting scenarios.
Elements of tier-two and even tier-three support will increasingly be assisted, or in some cases resolved, by AI-driven systems. This does not mean automation will replace deep technical judgment. Instead, more advanced systems will handle the structured components of complex problems: interpreting telemetry, narrowing down root causes, proposing remediation steps, and executing well-defined actions where confidence thresholds are met.
By resolving issues end-to-end or escalating only when human judgment is required, autonomous IT systems powered by AI reduce the need to involve scarce senior expertise in every incident, helping teams resolve problems faster and more consistently across the organization.
In 2026, success will depend on realism. IT leaders will need to evaluate tools based on where they genuinely perform well today, rather than where vendors promise they might perform tomorrow. The most effective organizations will be those that expand automation and autonomy incrementally, building trust through measurable outcomes rather than attempting all-or-nothing transformations.
Security Becomes the Primary Driver
While efficiency gains have long been the headline benefit of automation, security will emerge as its most powerful catalyst in 2026. Attack surfaces are expanding faster than IT teams can manually monitor, and the window between detection and impact continues to shrink.
In this context, automation is increasingly viewed not as an operational convenience, but as an essential layer of defense. Automated detection and remediation enable faster, more consistent responses to threats, while more autonomous systems can continuously assess risk, verify outcomes, and escalate only when human intervention is required.
This reframes the role of automation within IT strategy. Rather than simply accelerating internal processes, automated and autonomous systems become active participants in protecting the environment. For many organizations, this will be the tipping point that pushes automation from pilot programs into production-critical systems.
Security-driven automation also influences how teams are structured. As machines handle rapid response and enforcement, IT professionals can focus on policy, governance, and the continuous improvement of operational processes and security controls. The result is a more resilient operational model that balances speed with oversight.
What This Means for IT Leadership
By 2026, the most important shift will not be technological, but organizational. IT leaders will need to move beyond viewing automation as a collection of tools and start treating it as a fundamental operating principle. This includes setting clear boundaries for what systems are allowed to do independently, defining escalation paths, and building confidence through transparency, auditability, and control.
Automation becoming non-negotiable does not mean relinquishing responsibility. It means evolving how responsibility is exercised. Teams that embrace this shift thoughtfully will be better positioned to scale, secure, and sustain their operations in an increasingly complex digital landscape.
The era of asking whether AI belongs in IT is over. In 2026, the defining question will be how effectively organizations move from basic automation toward trusted, autonomous operations at the core of how IT runs.
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ABOUT THE AUTHOR
Tal Dagan is CPO at Atera, the #1 AI platform for IT management. Before joining Atera, Tal held several executive positions including VP of products at Redis Labs and Taptica, and the head of products at Flash Networks. Tal holds a BSc in computer science and business administration from the Hebrew University (cumlaude), Won the Tel Aviv University prize for outstanding achievements during his MSc in computer science, and completed executive education on strategic marketing management from Columbia University. Having deep technological roots, Tal is an expert in product innovation and development.
