As Generative AI exits Gartner’s ‘Peak of Inflated Expectations’ and slides into the ‘trough of disillusionment,’ the conversation surrounding the technology has also shifted from forward-looking hype to more practical discussions about what businesses must do to ensure its successful implementation. We all know how important data quality is in regard to Gen AI – indeed the phrase ‘garbage in; garbage out’ – has become practically a cliché in the technology industry. But, whilst still incredibly important, data quality is by no means the only factor businesses must perfect before embarking on a Gen AI journey.
The network can often be overlooked as a crucial element when it comes to successful implementation of any new technology, yet paradoxically it is crucial for the successful integration of Generative AI. A consistently, predictable performing network comes hand in hand with excellence in Gen AI because it ensures efficient data transfer and processing, which is essential given the vast amounts of data that large language models require. Many Gen AI applications, such as real-time language translation or interactive chatbots, even require instantaneous responses. High-performance networks enable these applications to function smoothly without delays, enhancing user experience.
Without the right network infrastructure in place, implementing Gen AI is like to trying to run a marathon in flip-flops. In fact according to Expereo’s Enterprise Horizons 2024 report when 650 global CIOs were asked about the leading obstacles to AI implementation within their organisation, almost a quarter (22%) of respondents said that their network and connectivity infrastructure was simply not ready to support large data/AI projects.
Take, for instance, a retail company aiming to use Gen AI for real-time customer service chatbots – without smooth and scalable network infrastructure, they might face severe performance bottlenecks, leading to slow response times and frustrated customers. Data transfer delays are another critical issue — think of a healthcare provider using GenAI for patient data analysis but struggling with slow data uploads, delaying crucial diagnostics.
Ensuring scalability through your network
Perhaps the most important factor that makes good network infrastructure so essential for Gen AI specifically, is its scalability.
The more the scalable the network, the more Gen AI applications can grow and handle increased data loads seamlessly. As the applications grow, they require more computational power and bandwidth to process and transfer large datasets efficiently. Scalable network infrastructure supports this by providing the necessary resources to accommodate growth, whether through cloud-based solutions, which offer ease and flexibility, or self-hosted options, which provide control and potential security benefits.
Additionally, scalable networks enable seamless integration with existing IT systems, ensuring that different components can communicate effectively and maintain high performance even as the workload increases. This adaptability is crucial for maintaining the efficiency and effectiveness of GenAI applications as they expand and evolve.
But how do you do this?
Designing a scalable network for Gen AI involves leveraging cloud-based solutions like AWS, Google Cloud, or Azure to provide flexible and adjustable resources. High-performance computing (HPC) clusters are essential for handling intensive computational tasks, and these can be scaled horizontally by adding more nodes.
This can be challenging and costly for businesses that lack the expertise and resources to do it themselves. That’s why many organisations opt for a third-party connectivity provider who can handle all the aspects of designing, deploying, and managing a network infrastructure that supports Gen AI applications. These providers can offer a range of benefits that can help businesses achieve their goals and overcome their challenges with Gen AI.
Firstly, an expert connectivity provider can play a crucial role in managing network infrastructure for Gen AI applications by offering deep network performance insights. When Gen AI applications begin to overconsume network resources, the provider can swiftly identify and address these issues through real-time analytics tools, or like in Expereo’s case using an Event Driven Automation to ensure swift identification of issues. This proactive approach ensures that network performance remains optimal, preventing bottlenecks and maintaining the seamless operation of AI-driven tasks.
In addition to network performance, the provider can enhance application performance by leveraging advanced internet solutions. By applying AI to optimise network performance to their own solutions, they can dynamically adjust traffic flows and prioritise critical AI workloads for their customers. This ensures that Gen AI applications run smoothly, with minimal latency and maximum efficiency, ultimately improving user experience and productivity.
Furthermore, the provider can offer comprehensive visibility into the health and performance of the network through robust analysis tools. Automation plays a key role here, enabling the network to self-heal and adapt to changing conditions without manual intervention. This holistic view and automated management ensure that the network remains resilient, reliable, and capable of supporting the demanding requirements of Gen AI applications.
Preparing for the tools of tomorrow
We may have left the ‘Peak of Inflated Expectations,’ but we can still expect to see Gen AI have an increased impact on organisations of all shapes and sizes. In order for businesses to navigate the tightrope between being left behind AI-enabled and rushing an expensive and ineffective implementation, business and technology decision-makers must make sure they have all the necessary groundwork in place to ensure that their AI transformation has the best possible chance of success.
That means ensuring that an organisation has a network, ready and able to enable Gen AI and that there are expert partners in place who can guide the business through this process.
