Aviatrix Blog 
Change is one of the few constants in the rapidly evolving cloud networking industry. 2024 brought innovations in GenAI, a renewed emphasis on resiliency and security, and new partnerships and integrations across the ecosystem. In this blog series, Aviatrix leaders will discuss what cutting-edge innovations and rising challenges in cloud networking and security they’re seeing come into focus in 2025. See previous blog posts on cloud networking and security in 2025 here.
Faizan Mustafa, Vice President of AI and Enterprise IT at Aviatrix, is driving the company’s AI initiatives. Faizan began his career in IT systems at AT&T and led management and technology consulting projects at Mazars and BearingPoint. He then served as Chief Information Officer at Toyota, where he led the rollout of SAP S/4HANA and the integration of Internet of Things (IoT) and big data solutions. In his current role at Aviatrix, Faizan helps to marshal Aviatrix’s resources to take advantage of AI’s possibilities.
Agentic AI: The New Operating Model for Multicloud Networks
In 2025, Agentic AI or AI that can operate without human intervention will introduce a paradigm shift in multicloud networking by acting as an adaptive orchestration layer capable of intelligently managing network performance, security, and resource allocation across diverse cloud environments. Unlike conventional AI systems that react to inputs or events based on pre-configured rules, agentic AI operates as a proactive collaborator that continuously learns, reasons, and adapts to ever-changing network conditions.
This next-generation AI is not about “self-driving” or “self-healing” networks—terms that promise autonomy but often fail to address the complexities of real-world cloud ecosystems.
Instead, agentic AI focuses on dynamic optimization, predictive resource scaling, and granular traffic shaping across hybrid and multicloud architectures. By integrating contextual data from workload patterns, network telemetry, and threat landscapes, agentic AI ensures smarter decision-making that reduces latency, minimizes congestion, and enhances resilience against performance degradation.
Practical Use Cases of Agentic AI in Multicloud Networks
1. Proactive Network Optimization
Agentic AI will enable real-time performance tuning by analyzing historical and live network data to predict peak loads and adjust network pathways before bottlenecks occur. This ensures that multicloud deployments maintain consistent service levels even under varying demand.
2. Intelligent Resource Allocation
Unlike static provisioning models, agentic AI can act as an intelligent broker that allocates bandwidth and computing resources across cloud providers based on current and projected needs, leading to cost savings and higher resource efficiency.
3. Predictive Threat Mitigation
With deep learning models trained on security telemetry, agentic AI has the potential to anticipate threats by recognizing subtle patterns that could signal emerging attacks. It helps create context-aware security policies that adapt in real time, ensuring robust protection without manual intervention.
4. Cross-Cloud Traffic Management
Multicloud environments often suffer from inefficient traffic routing, leading to latency and unnecessary costs. Agentic AI will enhance cross-cloud traffic flow by dynamically identifying the most efficient routes for data and optimizing inter-cloud connectivity for critical workloads.
5. Latency-Aware Load Balancing
Through continuous monitoring and machine reasoning, agentic AI performs latency-aware load distribution, ensuring that workloads are processed in the optimal cloud regions, thereby enhancing end-user experience and application responsiveness.
Agentic AI: Enabling Smarter, Faster Decisions at the Edge
As edge computing evolves, localized decision-making is emerging as a critical enabler for modern applications that demand real-time responsiveness and stringent data privacy. By processing data closer to where it is generated, edge computing reduces the need for extensive data transfers, ensuring low-latency performance and improved compliance with data sovereignty regulations—a key requirement in industries like healthcare, finance, and autonomous systems.
In this context, agentic AI offers a powerful means of enhancing decision-making at the edge by bringing intelligent autonomy to distributed systems.
Unlike traditional models that rely on centralized cloud processing, agentic AI enables edge devices to autonomously analyze data, detect anomalies, and respond to potential threats without waiting for instructions from central servers. This approach not only enhances network efficiency but also strengthens security by mitigating risks locally, limiting the exposure of sensitive data, and reducing the likelihood of large-scale breaches.
By empowering edge nodes with advanced reasoning capabilities, agentic AI has the potential to unlock new levels of scalability and resilience in applications such as IoT (Internet of Things), smart cities, augmented reality, and connected vehicles, paving the way for more adaptive and self-sufficient digital ecosystems.
Simplified Cloud Networking with Agentic AI
The future of cloud networking will involve a shift towards intelligent, adaptive, and proactive management driven by agentic AI. These advancements promise a practical approach to solving key challenges in multicloud environments by:
- Optimizing all areas of the network — Enabling cost-efficient resource allocation, real-time traffic optimization, and predictive security that dynamically adjusts to evolving threats.
- Localized decision-making — Agentic AI’s role in edge decision-making offers new possibilities for distributed systems to operate with greater autonomy and efficiency. By processing data closer to where it’s generated, agentic AI enhances low-latency performance, improves compliance with data sovereignty, and strengthens security through localized threat mitigation.
- Turning infrastructure into ecosystems — With its ability to orchestrate complex networks, enable smarter edge decisions, and enhance operational resilience, agentic AI has the potential to transform multicloud infrastructures into more agile, scalable, and secure ecosystems.
As businesses demand more streamlined operations, improved network efficiency, and faster insights at the edge, agentic AI and related technologies will play a pivotal role in shaping the next generation of cloud networking.
For more expert insights on cloud networking in 2025, see Aviatrix CEO Doug Merritt’s “Cloud Networking 2025: What This Year Holds for Cybersecurity, AI, and More.”