10 Oct 2025
The rapid advancement of Artificial Intelligence prompts concerns about the future of network engineering jobs, raising questions about whether current roles will persist. This exploration from Cisco Live reveals a prevailing industry sentiment of cautious optimism, where AI is seen as an augmenting tool rather than a wholesale replacement for human expertise.
The prevalence of Artificial Intelligence raises fears about job displacement, with some predicting 50% of current roles, particularly in IT and network engineering, may disappear within five years.
The Cisco Live conference, the world's largest networking event, visibly demonstrated an overwhelming integration of AI across keynotes, solution booths, and advertisements, signaling its pervasive impact on the networking industry.
Most professionals express optimism about AI, viewing it as the future that enhances experiences and daily work, emphasizing that failing to learn and adapt to AI now risks being left behind.
Network engineers are leveraging AI for tasks such as code co-piloting, automating manual processes, and serving as an assistant for information verification, significantly boosting efficiency and providing a strong starting point for complex tasks.
AI is perceived as a significant convenience, analogous to early computing peripherals, enabling natural conversational interaction with systems and offering immense opportunities despite the inherent responsibilities of its powerful capabilities.
Network engineering roles are not expected to vanish but will transform, moving beyond traditional manual tasks to more specialized functions supporting high-performance computing, GPUs, and large language models in data centers.
Professionals actively using AI gain a distinct advantage over those who do not, highlighting the necessity to adapt now and develop critical thinking skills to interpret AI outputs, identify inaccuracies, and ensure responsible implementation.
Cisco announced new AI advancements, including the Deep Network Model—a purpose-built AI for networking that performed 20% better than leading LLMs on CCIE tests—and AI Canvas, an AI-first control panel capable of autonomously troubleshooting and applying network policies based on natural language intent.
Network certification exams may evolve to include practical, implementation-focused scenarios that allow the use of AI tools, with a strong emphasis on critical interpretation of AI-generated responses and foundational networking knowledge.
Despite AI's rapid progress, human network engineers remain crucial for innovative ideas, for understanding how networks fundamentally work, and for guiding AI, especially as the increasing demand for AI infrastructure requires more specialized human oversight.
AI isn't going to replace you, but someone using AI will.
| Insight | Explanation | Implication |
|---|---|---|
| Industry Outlook on AI | AI is visibly pervasive across keynotes, booths, and advertisements at Cisco Live, indicating a significant industry-wide shift. | Adapting to AI is essential for professionals to remain relevant in the evolving technological landscape. |
| Engineer Sentiment & Practical Use | Most engineers express optimism about AI, actively using it daily for tasks like code co-piloting and automating mundane activities to enhance efficiency. | AI is already making daily work easier, but its effective integration still requires human expertise and critical judgment. |
| Job Market Transformation | Network engineering roles are changing, with some existing job forms potentially diminishing, but new, more specialized opportunities are emerging, particularly in supporting AI infrastructure. | Continuous learning, especially in areas like cybersecurity and automation, is crucial for career longevity and capitalizing on new roles. |
| Human Role vs. AI Role | AI functions as an advanced assistant, augmenting human capabilities and handling routine tasks, which could lead to improved work-life balance for engineers. | Humans are vital as gatekeepers and critical thinkers, indispensable for innovation, validating AI outputs, and maintaining overall network integrity. |
| Cisco's AI Offerings | Cisco unveiled specific AI tools like the Deep Network Model for networking tasks and AI Canvas for autonomous, intent-based network management. | The industry is moving towards AI-driven network operations, necessitating engineer proficiency in interacting with and overseeing AI systems. |
| Evolving Skill Requirements | Future network engineers need not only foundational network knowledge but also advanced security skills, automation expertise, and the ability to interpret AI results critically. | Professional development and certifications must adapt to assess critical evaluation skills, alongside practical application, rather than solely memorization. |
