Automation has firmly established itself as the backbone of modern network security. What was once seen as something advantageous to aim for is now more or less expected, underpinning everything from policy enforcement and compliance to day-to-day operational consistency across increasingly complex hybrid environments. It has become the mechanism that allows security teams to maintain control at scale, reducing manual effort while keeping pace with constant change.
But that progress is not evenly distributed. According to AlgoSec’s State of Network Security 2026 report, while 24% of organizations now operate at a high level of automation, one in five still rely primarily on manual processes. While automation may be widespread, maturity varies significantly, and that inconsistency is quickly becoming one of the defining challenges in network security today.
Automation has become so deeply embedded in how network security operates day-to-day, that it now supports the continuous enforcement of policy across hybrid environments, ensures compliance requirements are met without constant manual intervention, and validates changes before they go live. And as environments have expanded across cloud, on-prem, and distributed architectures, the role of automation has expanded with them. Policies need to be applied consistently across multiple control points, changes need to be tracked and verified in real time, and risk needs to be assessed in context rather than in isolation.
Automation provides the structure that makes this possible, allowing teams to maintain alignment between what was intended and what is running. All of this has changed how automation is perceived. It sits at the center of operational control, shaping how policies are enforced, how environments are governed, and how teams manage complexity at scale.
Despite widespread adoption, automation maturity varies significantly across organizations. Some have embedded it across their environments, linking workflows, policies, and enforcement into a cohesive system. Others are still applying it in isolated pockets, automating individual tasks without extending that consistency across the broader network.
According to the above report, while 24% of organizations report high levels of automation, a further 26% saw they’re using it at lower levels, creating a middle ground where progress is fast for some but slow for others. Many organizations sit in a transitional state, where automation exists within certain teams or tools, but hasn’t been extended across the full network security lifecycle. This is potentially quite risky, because it creates an uneven operating model where policies may be enforced automatically in one environment but handled differently in another. Changes may be validated in some workflows but not in others. Over time, these gaps accumulate, making it harder to maintain a clear and accurate picture of risk.
As automation becomes more established, attention is turning to what comes next. Agentic AI is starting to extend what automation can do, introducing a layer of context and analysis that goes beyond predefined workflows. It can surface patterns across complex environments, highlight potential policy conflicts, and provide recommendations based on how changes are likely to play out in practice. These capabilities are already finding a place in day-to-day operations, improving visibility across hybrid networks, identifying policy drift, and prioritizing risk in ways that would be difficult to achieve manually. In other words, it adds a level of intelligence to existing processes, helping teams interpret what’s happening across their environments rather than just execute predefined actions. Most organizations are still cautiously applying agentic AI in controlled scenarios where outcomes can be observed and validated. Decision-making still sits with human teams, with AI acting as a supporting layer rather than a replacement.
The next phase of automation is not being held back by capability. The tools are there, and in many cases, they’re already delivering value. The challenge lies in how those tools are connected or, more often, how they are not. Automation, policy management, and AI-driven insights frequently operate across different systems, owned by different teams, with limited coordination between them.
This lack of alignment makes it difficult to scale automation beyond individual use cases. A workflow might be automated within a single tool, but without shared policy frameworks or unified visibility, its impact remains contained. Decisions made in one part of the environment don’t always carry through to others, creating gaps in enforcement and inconsistencies in how risk is managed.
The report reflects a clear shift toward consolidation as a direct response to this very challenge. Around three quarters of organizations have already brought at least some of their security tools or policies under a single management layer, pointing to a broader move toward unified control. As environments continue to grow in complexity, that kind of alignment is becoming essential to ensure automation works as part of a connected system rather than a collection of isolated processes.
Automation has earned its place at the core of network security, but its effectiveness now depends on how well it is connected, governed, and understood across the entire environment. The next phase of growth will be defined by cohesion, where aligned policies, integrated workflows, and trusted oversight determine whether automation delivers control, or just more complexity.
Red Sky Alliance is a Cyber Threat Analysis and Intelligence Service organization. For questions, comments or assistance, please contact the office directly at 1-844-492-7225, or feedback@redskyalliance.com
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