Artificial Intelligence (AI) and cloud technologies are transforming the IT landscape at an unprecedented pace. Automation, machine learning, and intent-based networking promise to simplify operations and reduce the need for manual tasks. With these advancements, some professionals wonder: Are traditional networking skills still relevant?

The short answer: Absolutely. Networking remains the backbone of every digital innovation, and certifications like Cisco or Arista are more valuable than ever.

Key Takeaways:

• How the landscape has changed with AI
• Why networking skills still matter
• How a certification can support your career path
• How to utilize AI tools in your networking career

The Changing IT Landscape

AI-driven tools and cloud platforms have revolutionized the management of networks. Tasks that once required manual configuration are now automated through scripts and intelligent systems.

However, these technologies don’t eliminate the need for networking expertise. Instead, they change the nature of the work.

IT professionals must understand how networks function to design resilient architectures, integrate automation tools, and ensure security across hybrid environments.

Why Networking Still Matters

Networking is still the foundation for everything. AI, cloud, and IoT all depend on a robust network infrastructure. Without reliable connectivity, even the most advanced AI systems fail to deliver value.

Automation can handle routine tasks, but when something goes wrong, such as latency spikes or routing anomalies, human expertise is indispensable.

Cybersecurity threats often exploit network vulnerabilities. Networking knowledge is essential for securing data flows in hybrid environments. Understanding protocols, segmentation, and traffic flows is critical for implementing zero-trust models and safeguarding data.

The Role of Networking Certifications

Certifications remain a trusted way to validate skills in a competitive job market. Certifications from recognized organizations serve as proof that you have mastered specific technical skills. Employers trust these credentials because they are standardized and globally recognized.

These are some networking certifications we recommend:

• Cisco CCNA/CCNP: Industry-standard credentials for routing, switching, and network security.
• Arista: Specialized certifications for data center and cloud networking.
• CompTIA: Vendor-neutral foundational networking and security skills, great for beginners.
• VMware: Network virtualization and SD-WAN for cloud and data center environments.
• AWS: Cloud networking, hybrid connectivity, and secure architectures.

Technology evolves quickly. Certifications ensure you stay current with the latest tools, protocols, and best practices, which is especially important in networking, where cloud and AI integration are changing the game.

Networking + AI = Future-Proof Skills

The future of networking and IT isn’t about choosing between networking and AI; it’s about combining them. AI-driven tools are transforming how networks are monitored, optimized, and secured, but they still depend on professionals who understand the underlying infrastructure.

The two skills create a powerful combination:

• AI Enhances Networking: AI can automate repetitive tasks, like configuration, performance monitoring, and anomaly detection.
• AI-Driven Network Analytics: Modern networks generate massive amounts of data. AI tools analyze this data to predict failures, optimize traffic, and improve security. Engineers who can interpret these insights and apply them strategically will be invaluable.
• Automation and Intent-Based Networking: AI enables intent-based networking, where engineers define desired outcomes, and automation handles execution. To leverage this, you need strong networking fundamentals, plus skills in automation frameworks.

This hybrid skill set positions professionals for roles in NetDevOps, cloud networking, and AI-driven infrastructure management.

Career Implications: Networking Skills Are Your Competitive Edge

The demand for networking expertise is evolving. Roles such as these require strong networking fundamentals plus knowledge of emerging technologies:

• Cloud Network Engineer
• Network Automation Specialist
• Security Architect

The rise of AI and cloud technologies has amplified the need for networking expertise. Here’s why:

• Hybrid skill sets are in high demand.
• Networking knowledge enhances cloud careers.
• Security roles depend on networking.
• Salary trends favor multi-skilled professionals.

Networking is evolving, not disappearing. By combining networking certifications with AI, automation, and cloud skills, you position yourself as a future-ready IT leader. This hybrid approach ensures long-term relevance and opens doors to senior roles in architecture, security, and infrastructure strategy.

Networking Skills Will Always Matter, Even in an AI World

Networking is, and will remain, the backbone of modern IT. AI and cloud technologies enhance efficiency, but they cannot replace the need for skilled professionals who understand how networks operate.

If you’re planning your career path, start with networking fundamentals and certifications, then layer on cloud and automation skills. This combination will make you indispensable in the age of AI.

Ready to enhance your career? Explore technical certifications today and take the first step toward becoming a next-generation networking professional.

FAQs About Networking Skills with AI

Are networking skills still relevant with AI and automation?

Yes. AI and automation simplify routine tasks, but they rely on a strong network foundation. Professionals need networking knowledge to design, secure, and troubleshoot complex infrastructures.

Won’t AI eventually replace network engineers?

No. AI augments network management but cannot fully replace human expertise. Engineers are needed for strategic planning, architectural design, and handling exceptions that automation cannot predict.

How does AI impact network troubleshooting?

AI tools can predict issues and automate fixes, but complex problems often require human judgment. Networking knowledge ensures you can interpret AI insights and apply solutions effectively.