In the Asia Pacific (APAC) region, there is a clear desire to transform business operations through digitalization. With rapid technological advancements, businesses are increasingly recognizing the potential of AI to revolutionize various functions and significantly improve efficiency and productivity. This growing recognition makes AI adoption a cornerstone of modern digital transformation strategies.
However, while the potential of AI is immense, its implementation – especially in the networking space – requires a strategic and well-thought-out approach. Without it, companies risk embarking on costly and ultimately unsuccessful experiments. To fully exploit AI and optimize their digital transformation journey, companies must leverage the most advanced networking technologies available today.
An AI-native network goes beyond traditional models by delivering actionable insights, autonomous operations, and a conversational interface. These networks anticipate and resolve issues before they impact business operations, ensuring seamless connectivity and optimal performance for both the operator and end user. Additionally, an AI-native network infrastructure means AI is deeply integrated into the architecture from the start, designed with experience-driven questions in mind, and optimized for AI from the start.
By leveraging AI operations (AIOps), AI-native networks offer significant benefits. These technologies can reduce operational costs by up to 85%, creating a strong incentive for businesses to adopt these solutions to achieve significant cost savings, improve efficiency, and enhance performance.
The impact of AIOps on the end-to-end network
To fully harness the power of an AI-native network, businesses must take an experience-first approach. This means asking critical questions like, “How do we ensure that every user, everywhere, has a consistent experience?” These questions serve as more effective implementation guides than traditional metrics like device performance or hardware speed, which, while important, are secondary to delivering seamless experiences.
AIOps systems can act quickly on this data, proactively fixing issues before they impact the user experience. AI-native networks excel at this, providing automated insights that allow IT teams to quickly identify and fix issues, ensuring network reliability and user satisfaction.
When AIOps is applied end-to-end across wired, wireless, WAN, and data center domains, it maximizes the value derived from AI investments and enables businesses to accomplish more with fewer IT resources. This value extends across the entire network, benefiting end users, operations teams, and compliance teams alike.
Implementing this experience-driven approach relies on three key areas: the right data, real-time networking, and reliable infrastructure.
First, extracting rich network data from switches, access points, routers, and firewalls allows network operators to gain a detailed understanding of end-user experiences. This detailed knowledge is essential to making informed decisions and implementing effective solutions to truly meet user needs.
Finally, the demand for the right infrastructure cannot be overstated. With AI enabling businesses to process unprecedented volumes of data, scalable and secure infrastructure is essential. This allows the network to handle increased data loads and maintain reliable performance at scale, providing users with the seamless experiences they expect.
Improving outcomes with native AI networking
Proactive AI-powered network operations, when implemented correctly, deliver agility, automation, and assurance. They reduce complexity, increase productivity, and ensure reliable performance at scale. Innovations such as digital experience twins, which identify and resolve issues before users realize they exist, and advanced data center applications improve operational efficiency and drive cost savings.
Imagine an office where every virtual meeting goes smoothly. Proactive networked AI preemptively resolves potential issues to ensure high-quality, uninterrupted communication while maintaining a consistently excellent user experience.
It can automatically detect and resolve issues in real time, capturing packets in the cloud to diagnose and fix root causes. This reduces the need for costly on-site visits and improves network reliability and performance. In some cases, this means reducing trouble tickets by up to 90% and on-site visits by 85%. This efficiency saves IT teams significant time, money and effort, allowing them to focus on strategic initiatives rather than constant troubleshooting. The real value of these networks lies in their performance, which supports broader digital transformation goals.
AI-native networks are important for businesses in the Asia Pacific region that want to stay competitive. By adopting a strategic, experience-driven approach, businesses can harness the power of AI in networks, setting new benchmarks for efficiency and user satisfaction. As businesses continue their digital transformation, investing in proactive AI-native networks will be essential. This helps minimize costs, improve user experience, and achieve operational excellence, driving significant and sustainable business growth.
