Today’s data center teams are doing less clicking and more coding. In a recent study conducted by Futurum Research, in partnership with Nokia, the results make one thing clear: the era of purely manual data center management is over. Nearly every organization surveyed has implemented at least one modern NetOps automation practice. In this post, we’ll explore the rise of automation and AIOps (AI-powered IT operations) in data centers. Why are so many IT pros investing in automation tools? Because with growing complexity and uptime demands, automated and AI-driven operations are fast becoming the only way to keep networks efficient and reliable.

Automation everywhere – From monitoring to config management

It’s impressive just how pervasive core automation practices have become. Automated monitoring and alerting are practically standard now – 67% of organizations have real-time infrastructure monitoring in place. This means software, not humans, is watching the network 24/7 for anomalies. Likewise, 58% use infrastructure-as-code or configuration automation tools (think Ansible, Terraform) to manage device configs. Instead of logging into switches manually, engineers are writing scripts and using version-controlled playbooks. Similarly, 54% have deployed AI/ML-based incident detection solutions, a flavor of AIOps that spots patterns and anomalies that could indicate trouble. Even fail-safe mechanisms are common – about half (49%) use auto-failover systems to instantly handle link or device failures. Not one respondent said “we use none of these” – a full 0% reported having no modern automation at all in their environment. It’s safe to say every enterprise is doing something to automate their data center ops (see Figure 1).

Figure 1. Which of the following technologies or practices does your organization use today?

Source: The Data Center Network Imperative: Key Trends Driving the Next Era of Data Centers, Futurum Research,
September 2025.

Beyond these basics, many organizations are adopting DevOps-style practices in networking. Approximately 45% are managing network configurations via Git or similar version control (treating network config like code) and 44% have implemented CI/CD pipelines to automate testing and deployment of network changes. Change management is becoming more rigorous: 44% have formal change approval workflows with role-based access controls and one-third have even built custom in-house automation scripts to fill gaps. Forward-leaning teams are experimenting with cutting-edge techniques – 33% have deployed “self-healing” auto-remediation tools that trigger predefined fixes when issues arise and 20% practice chaos engineering or disaster recovery simulations to stress-test their resilience. These numbers show that a significant subset of enterprises are truly pushing the envelope. While not everyone is doing chaos testing, the fact that one in five already are is telling.

Crucially, all this automation isn’t just about convenience – it’s about reducing errors and speeding up operations. As one network engineer might quip, “scripts don’t go on vacation or misconfigure the router when tired.” The survey data reinforces that sentiment: every company is using at least one automation tool and most have embraced several, marking the end of the old manual-only days.

AIOps and advanced capabilities on the rise

What about the more advanced stuff, like AI-driven operations and intent-based networking? Those aren’t futuristic concepts – they’re happening now. IT leaders rated several emerging technologies as highly important for reliability. For instance, roughly 80% of respondents said having the ability to pre-check and post-check network configuration changes is critical (averaging 4.2 out of 5 in importance). In plain terms, they want automated “dry runs” and validation tests to ensure changes don’t break anything – a very specific automation capability. Similarly, around 78% rated an integrated network digital twin (a real-time software model of the network for testing changes) as very important for improving reliability. These forward-looking tools appeal because they prevent outages by catching mistakes before they hit production.

The exciting part is that many organizations aren’t just musing about these capabilities – they’re implementing them. The survey asked about current adoption plans across a range of advanced operations tech and the results show rapid progress from pilots to production. For example, 59% of companies have already implemented automated config change validation tools, with another 23% actively rolling them out. Over half have a network digital twin in place (49% implemented), as well as closed-loop automation systems (50%) that can adjust the network on the fly and intent-based networking (50%) where you declare high-level intents and the system self-configures. Even AIOps platforms are in production at 43% of organizations, with an additional 31% in pilot or deployment stages. Furthermore, some foundational “safety net” practices have gained solid traction: 58% have put their network configurations under version control and 60% have automated rollback mechanisms to instantly undo bad changes. Not long ago, concepts like digital twins or intent-driven networks were cutting-edge ideas; now they’re quickly becoming essential in modern data centers.

The motivation behind this embrace of automation and AIOps is directly tied to the reliability and efficiency goals we discussed earlier. By automating routine tasks and using AI to anticipate issues, IT teams aim to minimize human error and response times – two big contributors to downtime. The survey analysis noted that integrating monitoring, testing, CI/CD and AI analytics creates an “intelligent automation loop” that continuously validates the network’s state against the intended state. In other words, these tools work together to catch misconfigurations or anomalies early (or even prevent them entirely), which drastically improves uptime.

What’s the lesson?

If there’s one lesson for IT pros, it’s that automation and AIOps are now essential arrows in the quiver. Leading organizations aren’t automating just to save admin time – they view it as a strategic lever for reliability, consistency and scalability. For a data center operator or CIO, the question to ask is: Are we keeping up? If you’re still doing primarily manual network changes or lack AI-driven monitoring, it may be time to pilot these tools to stay on par with industry peers. Start with areas that hurt the most – maybe automate your change validations or invest in an AI-based monitoring tool that can predict failures. The survey data suggests that even advanced practices like digital twins or self-healing networks are no longer exotic; they’re becoming expected. Adopting an automation-first mindset will not only reduce toil but also boost confidence that your infrastructure can handle growth and disruptions. As one practical tip, consider framing automation projects in terms of reliability outcomes (e.g., “this will reduce outages by X%”) when seeking buy-in – the survey shows those are outcomes business leaders care about. Ultimately, the path to truly reliable, scalable data center operations lies in embracing automation and AI – so don’t be left behind on that journey.

This blog post is number 3 in a series of 5. To see the other posts, visit this page.

You can also find results from the full study here.