Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Steve Petryschuk, Vice President, Product and Market Strategy, Auvik
If 2025 showed IT leaders anything, it’s that networks are becoming more complex by the day, and legacy observability tools and strategies need to evolve. Enterprise networks are growing increasingly fragmented across cloud, edge, and on-prem environments. With this amount of endpoints to manage, complexity is no longer just a temporary challenge, it’s the default state.
In fact, almost half of IT professionals in 2025 reported lacking real-time visibility into their network connectivity. This shocking gap in visibility highlights that capabilities once viewed as “nice to have”, like AI-powered end-to-end observability and unified discovery, are now essential to maintaining reliable and resilient services.
At the same time, networking teams are being asked to operate differently: shifting from reactive infrastructure management to an outcome-driven model. IT must now align network objectives to larger business outcomes and goals, reframing this infrastructure as less of a cost center and more of a growth driver. In 2026, these changes will redefine network management as a platform discipline in the year ahead – one that will combine visibility, AI automation, and operational rigor to support modern digital operations at scale.
The End of “Simple” Networks and The Case For AI Integration
One of the biggest contributors to the explosion in endpoints is the continuation of remote and hybrid work (becoming more of a permanent policy versus a temporary disruption to in-person work). The network “edge” is now managed across thousands of personal devices, home networks and public wifi connections.
As IT teams are spread thin, relying on fragmented device monitoring, legacy tools and siloed metrics can no longer deliver the in-depth visibility needed to maintain reliable, efficient, and resilient operations. Device data may still be trapped in disconnected dashboards, not only creating security blind spots but also making it nearly impossible for IT teams to manually track the origins of vulnerabilities and network failures. Regaining control in the year ahead will start with embracing AI discoverability. Larger scale integration of AI will quickly shift from a “nice-to-have” to a business imperative, as AI delivers the ability to seamlessly map every network asset and device, to correlate disconnected data into actionable insights.
As modern network operations shift into a platform-forward mindset, IT leaders will also be looking to build fully unified, self-service infrastructure that teams can manage and access without manual intervention. On an enterprise scale, this workflow automation cannot be accomplished without the help of AI – enabling IT teams to scale operations while managing compounding traffic growth and risk.
What’s more, by automating routine, repetitive tasks like ticket resolution, organizations will free up human expertise to focus on resilience, optimization, and innovation – allowing IT to be the business-enablement function it is designed to be.
From Keeping the Lights on to Delivering Measurable Business Outcomes
Historically, IT teams have primarily been tasked with tracking infrastructure performance metrics (ticket volume, uptime, meantime to repair etc.). This reactive approach focused more on immediate troubleshooting and ticket resolution, ignoring the critical function IT teams play in powering business growth.
In 2026 and beyond, IT teams will be expected to treat networking as a business-enablement function, changing how teams define outcome ownership, workflows, and accountability. For example, priorities may shift from resolving the oldest ticket to prioritizing network issues based on their necessity in driving larger revenue and business objectives. This is a departure from how IT teams have traditionally managed networks, moving from utility providers to essential strategic partners.
Managing Cultural Shifts and Preparing Teams for Change
Aligning teams with this large-scale digital and operational transformation, ultimately, is the hard part. Powering success in this shift towards AI infrastructures and reframing IT as a key growth driver requires business leaders to rethink how they approach hiring, success metrics, and mutual accountability. Employees must be provided with the group incentives, consistent AI and threat upskilling opportunities, and clear-cut goals to shift their mindset from individual measurement (ticket resolution and box-checking), to team goals that strive to create larger resilience and long-term service-enablement.
So, Now What? – Where Network Leaders Should Start
These changes foreshadow a monumental shift in how IT teams operate and drive outcomes. Driving AI and operational transformation starts with prioritizing the automation of network visibility across all environments and endpoints, immediately freeing up more time for IT pros to transition into a more strategic, growth-oriented role. This also requires change management upfront. IT and c-suite leaders must first provide employees with clear-cut metrics, responsibilities, and upskilling to motivate and encourage these professionals to embrace AI and work towards larger business goals.
The New Mandate for Network Management
Network observability enables not only IT but business outcomes, justifying greater investment in fully-integrated AI platforms. Harnessing large-scale automation, networking teams will be tasked with combining visibility, automation, and operational rigor to manage distributed, complex networks in the years ahead. These massive shifts in strategy will define the next era of networking, providing IT leaders with the opportunity to reposition networking from a background task to a core strategic driver.
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