Across industries in the Asia-Pacific (APAC) region, there is a visible drive to transform business operations through digitalisation. With rapid technological advancements, businesses are increasingly recognising AI’s potential to revolutionise various functions and drive significant improvements in efficiency and productivity. This growing recognition is making AI adoption a cornerstone of modern digital transformation strategies.
However, while AI’s potential is vast, its implementation — particularly in networking — requires a strategic and well-thought-out approach. Without this, businesses risk falling into costly and ultimately unsuccessful experiments. To truly harness AI and optimise their digital transformation journey, enterprises must leverage the most advanced networking technologies available today.
An AI-native network goes beyond traditional models by offering actionable insights, self-driving operations, and a conversational interface. These networks anticipate and resolve issues before they impact business operations, ensuring seamless connectivity and optimal performance for the operator and end user. Moreover, an AI-native networking infrastructure means AI is deeply embedded in the architecture from the start, designed with experience-first questions and optimised for AI from the ground up.
Leveraging AI operations (AIOps), AI-native networking offers substantial benefits. These technologies can reduce operational costs by up to 85%, providing a strong impetus for businesses to adopt these solutions for significant cost savings, enhanced efficiency, and improved performance.
The impact of AIOps across the end-to-end network
To truly harness the power of an AI-native network, businesses must embrace an experience-first approach. This involves asking critical questions, such as, “How do we ensure every user, in every location, is getting a consistent experience?” These questions serve as more effective guides for implementation than traditional metrics like device performance or equipment speeds, which, while important, are secondary to delivering seamless experiences.
AIOps systems can swiftly act on this data, proactively fixing issues before they impact user experience. AI-native networking excels here, providing automated insights that enable IT teams to identify and rectify problems quickly, ensuring network reliability and user satisfaction.
When AIOps is applied end-to-end across wired, wireless, WAN, and data centre domains, it maximises the value derived from AI investments and empowers businesses to achieve more with fewer IT resources. This value extends throughout the network, benefiting end users, operations teams, and compliance teams alike.
Achieving this experience-first approach hinges on three key areas: the right data, real-time networking, and a reliable infrastructure.
First, extracting rich network data from switches, access points, routers, and firewalls provides network operators with a detailed understanding of what end users are experiencing. This granular insight is crucial for making informed decisions and implementing effective solutions to truly address user needs.
Finally, the demand for the right infrastructure cannot be overstated. As AI enables businesses to process data at unprecedented volumes, having a scalable and secure infrastructure is essential. This ensures that the network can handle increased data loads and maintain reliable performance at scale, supporting the seamless experiences users expect.
Raising the bottom line with AI-native networking
Proactive AI-native network operations, when implemented correctly, offer agility, automation, and assurance. They reduce complexity, increase productivity, and ensure reliable performance at scale. Innovations like digital experience twins, which identify and solve problems before users notice, and advanced data centre applications are enhancing operational efficiency and driving cost savings.
Imagine an office where every virtual meeting proceeds without a hitch. Proactive AI in networking preemptively addresses potential issues to ensure high-quality, uninterrupted communication, 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 site visits and enhances network reliability and performance. In some cases, this means reducing up to 90% trouble tickets and 85% on-site visits. This efficiency saves IT teams significant time, money, and effort, allowing them to focus on strategic initiatives rather than constant troubleshooting. The true value of these networks lies in their performance, supporting broader digital transformation goals.
AI-native networking is important for APAC enterprises aiming to stay competitive. By adopting a strategic, experience-first approach, businesses can unlock the potential of AI in networking, setting new benchmarks for efficiency and user satisfaction. As enterprises continue their digital transformation journeys, investing in proactive AI-native networking will be key. It helps minimise costs, enhance user experiences, and achieve operational excellence, driving meaningful and sustainable business growth.
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