How Gen AI and 5G can work together to drive enterprise success

Two technologies pushing enterprise business objectives forward on a global scale are 5G and generative artificial intelligence, or Gen AI.  

5G networks, whether through a wireless wide area network (WWAN) or a private network carry vast amounts of data with minimal latency and enhanced security. Meanwhile, Gen AI offers numerous examples of how it can streamline business insights and automate repetitive tasks across various industries. 

While both technologies provide value separately, their real potential is unlocked when combined. More specifically, Gen AI and 5G can — and quite frankly should — co-exist in a mutually beneficial relationship that maximises network performance while simultaneously optimising each Gen AI use case. 

The impact of 5G on Gen AI 

The very nature of Gen AI, whether training a large language model (LLM) or using a mainstream Gen AI tool, makes 5G its perfect partner. 

Any enterprise attempting to train an LLM, could be leveraging as much as petabytes if not more to ensure the Gen AI function is able to support massive workflows and a large customer base. This training process requires large and continuous data transfers and, therefore, requires a network to facilitate these transfers with high bandwidth and low latency.

A centrally managed 5G WWAN network allows network administrators to leverage the power of 5G and ensure each data training exercise gets the network support it needs. This could include traffic steering to create bandwidth for Gen AI training or link bonding to increase the bandwidth necessary for large data transfers. Alternatively, enterprises can leverage a private 5G network to ensure each Gen AI model has dedicated 5G bandwidth while the model is trained. 

Once a model is deployed, or if enterprise personnel leverage a more general AI tool like Chat GPT, the goal is to get live responses to complete business goals. For example, Gen AI-enhanced cameras are becoming an everyday use case for businesses to collect large amounts of actionable data. These cameras, which organisations also use for security purposes, can track who enters a facility, the number of people entering, and their license plates. The camera then shares all that data back to a central system for analysis. Often these cameras are placed in areas where it might be cost-prohibitive or too time-consuming to run wires. Therefore, 5G can play an important role in ensuring that video from the cameras is delivered back to its AI analytics platform with high performance and reliability. 

The advantages of Gen AI on 5G networks 

If an enterprise invests in a 5G WWAN or a private 5G network, the hope is to have a highly available network ready to support business objectives. Gen AI technology can help improve the performance and availability of the overall network, while simultaneously streamlining operations for IT teams in charge of network administration. 

Ensuring a high-performance, reliable network 

Gen AI models are trained on massive amounts of data about the network's operation. Based on this data, a model can identify a baseline for network traffic performance, allowing Gen AI to detect disruptions or anomalies. The model can also pinpoint the root cause of the issue and formulate recommendations on how to troubleshoot it before it impacts network service and, ultimately, business success. This intelligent approach to fault management keeps 5G networks highly available. 

Empowering IT teams with advanced technology 

For lean IT teams that are constantly asked to do more with less, Gen AI can be the perfect asset to alleviate team workload and increase team efficiency. Most notably, some enterprises implement LLM-based Virtual Experts into their network administrative workflows. These virtual experts are helping some administrators get real-time answers to questions about the network using Natural Language Processing, or AI, which allows software to understand and communicate in human language. 

In the past, a difficult query about network performance could force the network administrator to consult multiple technical documents. Now, the Gen AI-based Virtual Expert can synthesise information from many different documents to provide an answer to the administrator in just a few sentences or through graphs, saving valuable time for today’s IT teams. 

Enhancing network security with Gen AI 

Gen AI will be especially useful for network security purposes. Today’s enterprise networks are experiencing an unprecedented amount and sophistication of attacks. In fact, some threat actors are even leveraging Gen AI to help them. Network security personnel already see everything from more targeted phishing attacks to new forms of mass-produced malware. 

It’s only right that enterprises use Gen AI to protect their networks. Leveraged correctly, Gen AI tools can monitor your 5G network for all types of unusual behaviour. This includes unusual or unauthorised sign-ons, phishing attempts, and various malware. Gen AI will provide real time alerts — on the very same 5G network — so IT security teams can quickly respond and minimise any network damage. 

Investing in interconnected technologies for maximum benefit 

As businesses across industries continue to move towards a digitally connected future, the focus will shift away from investing in isolated technologies. Organisations that implement complementary technologies will not only optimise their investments but also gain a competitive edge. Gen AI and 5G are an ideal example of this synergy. With Gen AI set to drive the future of automation and 5G primed to become the standard for connectivity, investing in both will create faster data analysis, more efficient processes, and ultimately, accelerated business success.  

Darryl has over 20 years of experience in the IT industry and has held many leadership positions in vendor, distribution and reseller organisations including HP, Imperva, ServiceNow and Infoblox. Darryl is VP Partner Sales, EMEA at Ericsson. He enjoys conducting business in multi-cultural and cross geography environments.