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The role of generative AI in networking
As networks grow more complex, generative AI emerges as a tool that can help network teams with a wide range of tasks, such as writing scripts, documentation and incident response.
Enterprise networks have never been more important than they are now. Network teams routinely deliver networking as a reliable component of business, which means they have to keep up with the evolution of standards, technologies and expectations. But network teams face greater challenges as they try to support these new demands.
Significant networking shifts are spreading in the enterprise, while IT departments simultaneously face flat budgets and a workforce crunch. Aspiring IT professionals are now less likely to specialize in networking than other practice areas, and seasoned professionals are heading toward retirement.
Despite this complexity, generative AI (GenAI) continues to develop into a versatile technology that could eventually support network operations. When generative AI reaches a sufficient level of maturation, it could help network teams automate routine tasks, respond to incidents and account for the reduced workforce, among other benefits.
How GenAI can support networking
GenAI tools could aid burdened network teams in several ways. If network teams layer generative AI -- with its aptitude for natural language -- onto machine learning AI tools, they might be able to handle increased workloads, even as staffing declines.
GenAI can help network professionals with the following:
- Write programs and scripts.
- Create documentation.
- Formulate policy and configurations.
- Assist with audits.
- Respond to incidents.
- Act as a virtual assistant or mentor to network professionals.
Write programs and scripts
Network teams in some organizations already experiment with GenAI or currently use GenAI tools to write network automation scripts. GenAI can help network professionals write scripts in the following ways:
- Provide program stubs.
- Write structure.
- Check syntax.
- Offer feedback.
Network engineers shouldn't immediately use code that GenAI tools provide without question, however. GenAI can give network teams an advantage on a project, but they should still check, modify and complete codes before execution.
Create documentation
GenAI tools can also help network professionals create more human-readable and complete documentation of their networks. Network professionals can input configuration and inventory files, network mapping data and other notes they've already developed into a GenAI tool, and the tool can generate full written descriptions and -- in some cases -- diagrams.
Formulate policy and configurations
GenAI tools that have been properly trained on the configuration syntax of different network tools can create network policies. For example, if network administrators input verbal descriptions of the network intent into a GenAI tool, the tool can generate commands to implement those intents. The same is true for the reverse: A GenAI tool can look at configurations and create a description of what the network will do, and network professionals can compare the output with the intent.
Assist with audits
If GenAI tools are able to review configurations, they could also assist with network audits. Comprehensive audit tools that can quickly provide insight into configuration drift and misconfigurations are already available, but network professionals might prefer to have this capability woven into one tool that also includes policy analysis and documentation assistance.
Respond to incidents
Many AI and machine learning tools are already adept at incident response. For example, they can sort through many alerts and alarms, as well as sift out trends, identify unifying factors and find anomalous -- but harmless -- occurrences. If these tools include GenAI capabilities, they could better understand human questions and provide understandable answers.
Act as a virtual assistant or mentor to network professionals
Current GenAI tools have a long way to go, but they have the potential to aid a static or shrunken workforce. For example, tools could fill in gaps to nurture new talent and support existing staff.
On the one hand, GenAI might serve as an all-around assistant to network engineers, helping by automating routine tasks or filing change management requests. On the other hand, GenAI could also act as a mentor to new network professionals as they enter the field. These tools could train network professionals on best practices for network management and operations, teach them specific technical skills and serve as encyclopedic references for questions.
GenAI needs more development before widespread use
Although GenAI has the potential to support networking, the technology isn't quite there yet. It could take some time before GenAI becomes capable and trustworthy enough to support network operations. Tools that can hallucinate or refuse to cooperate aren't reliable enough for enterprise network use. Even when GenAI becomes sufficient for widespread use, it will still likely take longer before the cost of capable tools is within reach of most organizations.
However, the potential that GenAI tools hold could be enormous for network teams. GenAI could make networks more reliable and secure, and also ease the challenges of fully staffing the network and keeping up with evolving needs and challenges.
John Burke is CTO and principal research analyst with Nemertes Research. With nearly two decades of technology experience, he has worked at all levels of IT, including end-user support specialist, programmer, system administrator, database specialist, network administrator, network architect and systems architect. His focus areas include AI, cloud, networking, infrastructure, automation and cybersecurity.
