By 2035, management consoles as we know them will vanish, replaced by AIOps that seamlessly manage the delivery and security of applications.
If that sounds dramatic, read on and consider the findings from the 2025 F5 State of Application Strategy report. The journey toward agent-based operations has already begun. Back in 2019, a mere 9% of respondents employed data-driven automation. Fast forward to 2025 and nearly half, 44%, are letting data drive script invocation within operations. It’s a small step from there to employ AI agents to generate and then execute those scripts.
Against this backdrop, the stage is set for a new era where AI will be the primary control plane for application delivery and security in the future.
Yes, I said what I said.
The shifting sands of application delivery
Application delivery as a discipline has always been dynamic, evolving alongside changes in application architectures, infrastructure, and user expectations. The move from monolithic to microservices architectures put unprecedented stress on traditional management approaches, forcing organizations to reevaluate how they handle complexity and scale. The enterprise portfolio is now strongly modern, with 53% of applications categorized as modern applications, a figure that is set to grow along with AI adoption.
Virtualization, containers, and clouds—once novel—are now table stakes. They brought with them an ever-increasing reliance on automation. The leap from automated scripts to AI-driven decision-making is, quite simply, the next logical progression.
This year’s research highlights a pivotal shift: Nearly half of respondents indicated they want to use AI for policy generation and operational decisions. And they’re comfortable doing that: 99% expressed comfort with AI acting on its own to execute at least one operational function.
Respondents enthusiastically want generative AI to take action on their behalf to manage application delivery and security.
It’s clear enterprises are fed up with inefficient workflows, conflicting consoles, and the complexity associated with working with APIs, leading to a collective push for a single, AI-driven interface capable of operating across multiple environments.
Bye-bye, console. Hello, AIOps.
Why the imminent demise of the management console? In a hybrid multicloud world, operations teams juggle a litany of environments, tools, and dashboards.
We’ve asked the same question about frustrations with delivering and securing applications in multicloud estates for almost a decade. The top three have rarely changed, with a focus on complexity of APIs and tools, application performance problems, and migration of applications across clouds.
This fragmentation escalates the risk of misconfiguration, compliance drift, and security blind spots. Throw in microservices that communicate through ephemeral networks, plus an ever-growing list of APIs, and you have an operational nightmare waiting to happen.
To wit, this year we asked respondents to select just the top two to narrow down what really frustrates folks. Even we were somewhat surprised by the results: 53% of respondents cite inconsistent security policies across multiple clouds as their top frustration, with 47% pointing to inconsistent delivery policies as a close second.
Enter AIOps, a practice combining automation, analytics, and AI-driven orchestration to maintain and optimize application services. AIOps promises to unify observability data, integrate security policies, and enforce consistent governance across all environments. Instead of clicking through multiple consoles, operators will interact with a single, intelligent system capable of understanding natural language, making recommendations, and executing tasks with minimal oversight. More than half of organizations want to use AI to automatically adjust delivery policies to meet service-level objectives—a clear indicator that trust in automated decision-making is on the rise.
The path to an AI-driven control plane
One major paradigm shift is that AI will be the primary control plane for application delivery and security in the future. This means the “brain” of your infrastructure—the place where data about applications and APIs from users, systems, and networks is processed—will be an AI platform that not only analyzes but also makes real-time adjustments.
To make this work, organizations need clean, consistent data streams and robust governance frameworks. An AI is only as good as the data it ingests. That’s why we see a renewed emphasis on end-to-end observability: continuous monitoring across physical, virtual, and cloud resources. Once the data is unified, AI can discern patterns—like a sudden traffic spike or suspicious user behavior—and respond instantly by reconfiguring load balancing, adjusting firewall rules, or spinning up more resources.
Security is also no longer an afterthought. AI-driven security means dynamic, context-aware policies that adapt in real time. For instance, if an anomaly indicates a potential threat vector, AI can immediately apply additional WAF rules or tighten API security without waiting for manual intervention.
Building momentum to 2035
We’re already seeing the seeds of AIOps sprout across industries.
This shift won’t happen overnight. It will require cultural and operational changes, particularly around trust and governance. But organizations that embrace AI-driven operations early will likely reap the benefits of reduced operational overhead, faster response times, and a more secure posture in the face of ever-evolving threats.
By 2035, the notion of manually clicking through tabs in a management console to deliver or secure applications will feel as antiquated as dial-up modems and floppy disks. AIOps will be the standard. We can either cling to outdated management paradigms or prepare for a future where AI is the decision-maker, the watchtower, and the controller of all things app-centric. The numbers—and the momentum behind them—speak for themselves.
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