AI in Networking: 7 trends to watch in 2025

Damien Delard

February 20, 2025

AI is transforming data networking with user-centric, efficient and sustainable solutions.

As industries evolve through digital transformation, networks remain the critical enabler of seamless operations in sectors such as healthcare, government, utilities, transportation and education. As the complexity of managing these infrastructures grows, organizations are looking to AI for intelligent, secure and autonomous systems that will help to simplify their operations.

This blog post explores the transformative role of AI in data networking and highlights seven key trends that align with the principles of user-centric, efficient and sustainable solutions.

1. AI simplifies network complexity

AI and Machine Learning (ML) are transforming network infrastructure from traditional, manually operated setups to fully autonomous systems. In 2025, AI-powered networks provide:

• Zero-touch provisioning for quick and efficient deployment
• Self-configuring and self-healing systems to maintain operational continuity
• Personalized connectivity that adapts dynamically to user patterns, minimizing latency

These intelligent solutions reduce operational overhead and simplify the management of intricate network environments, including multi-site and distributed architectures.

2. AI is the core of Intent-Based Networking

AI-integrated Intent-Based Networking (IBN) is redefining how organizations manage and align their networks with business objectives. In 2025, AI enables:

• Real-time intent translation: Converting business goals into actionable network configurations
• Unified orchestration: Managing hybrid, multi-vendor environments seamlessly
• Enhanced routing protocols: Leveraging technologies like Shortest Path Bridging (SPB) to optimize traffic flows across complex network topologies

SPB ensures efficient and scalable Ethernet networking, offering organizations a robust foundation for deploying AI-driven IBN solutions.

3. AI elevates network security

As cybersecurity threats grow increasingly sophisticated, AI is revolutionizing network security with innovative solutions. These include:

• Behavioral analytics: Identifying anomalous activities to preempt potential breaches
• Automated threat mitigation: Responding to incidents in real time to minimize disruptions
• Edge security: Protecting decentralized data processing points with AI-powered algorithms

By integrating SPB with AI, networks can enhance security through streamlined traffic isolation and simplified segmentation, improving resilience against potential threats.

4. AI optimizes the network for enhanced performance

AI-driven optimization advances network performance through predictive, real-time intelligence. Key features include:

• Dynamic traffic management: Predicting and mitigating congestion proactively
• Energy-efficient operations: Leveraging AI for smart resource allocation, reducing power consumption
• Scalable architecture: SPB supports plug-and-play network expansion, ensuring flexibility and reducing complexity in large-scale deployments

These innovations align with global sustainability goals while ensuring reliable, high-performance network operations.

5. AI delivers the power of network digital twins

Network digital twins—virtual models of physical networks—are essential for strategic planning and performance enhancement. Today, they offer:

• Scenario testing: Evaluating network changes in a controlled environment
• Predictive maintenance: Anticipating hardware failures before they occur
• Enhanced planning with SPB: Simplifying modeling and simulation of SPB-enabled networks, ensuring optimal performance across dynamic environments

Digital twins combined with SPB allow for risk-free experimentation and informed decision-making, driving innovation and operational excellence.

6. AI works in synergy with 5G

The integration of 5G and AI delivers unparalleled connectivity and innovation. This synergy supports:

• Low-latency applications: Enabling critical use cases like autonomous vehicles and remote surgeries
• IoT scalability: Managing billions of connected devices seamlessly
• SPB-enhanced slicing: Leveraging SPB’s deterministic routing for tailored network slices, ensuring efficient resource allocation

This convergence enhances both the scalability and reliability of AI-powered 5G networks.

7.AI enhances collaboration networks

Collaboration platforms are becoming smarter with AI, enabling more productive and innovative interactions. Advancements to date include:

• Bandwidth optimization: Ensuring uninterrupted communication during collaborative efforts
• Content-aware networking: Allocating resources dynamically to prioritize critical tasks
• SPB-enabled architecture: Facilitating cross-border virtual workspaces with simplified, loop-free topology, ensuring robust and secure collaboration environments

AI and SPB together enhance global teamwork, creating adaptive and reliable networks for the modern workforce.

Conclusion

The evolution of AI-driven networking is reshaping the benchmarks of efficiency, security and sustainability. The trends discussed—ranging from network autonomy to AI-powered 5G and digital twins—underline the critical role of AI in modern networks. By integrating technologies like SPB, networks achieve not only operational simplicity but also unparalleled scalability and performance.
This transition to AI-powered, SPB-enhanced networks is not merely a technological upgrade but a strategic imperative for organizations to stay competitive in an ever-evolving digital landscape. The future is intelligent, autonomous and sustainable, and organizations embracing these advancements are set to lead in the interconnected world of tomorrow.