5G has become the standard choice for connecting mobile phones and devices globally, but its adoption within enterprises has been slow. The potential of 5G in enterprise settings is currently focused on connecting services and applications that extend beyond the walls of these organizations. The lack of connectivity expertise, killer apps, and significant advantages over existing Wi-Fi networks are the main obstacles for 5G within enterprises. According to a recent analysis by ABI Research, enterprise 5G did not gain traction in 2023 and is unlikely to do so in 2024. Enterprises prioritize use cases and outcomes over the name of the connectivity technology, as they are not experts in this field. While 5G has been successful in the consumer segment, it has struggled to gain traction in the enterprise market.
The integration of artificial intelligence (AI) and machine learning is seen as a potential growth area for enterprise 5G, but it is not expected to see significant progress in the coming year. The ABI Research authors predict that AI and machine learning will not have a major impact on the 5G Radio Access Network (RAN) domain in 2024. Closed-loop automation, including near-real-time RAN intelligent controllers, will remain a niche topic. Tom Snyder, executive director of RIoT, attributes the slow adoption of 5G in enterprises to the fact that Wi-Fi is more efficient and cost-effective. Most enterprise use cases involve connecting machines and equipment within a confined space, where Wi-Fi is more than sufficient. Additionally, there has not been a compelling killer app for 5G in the enterprise market. The cost and complexity of involving a cellular operator in the network do not outweigh the benefits for large enterprises, while small enterprises prefer the customer service and real-time support offered by managed service providers for their Wi-Fi networks.
However, there is still great potential for 5G when it comes to applications or services that extend beyond enterprise walls. For example, 5G can seamlessly track devices both indoors and outdoors, unlike other technologies such as GPS or Bluetooth. This opens up opportunities in indoor navigation, vehicle tracking, and asset tracking. Upcoming iterations of 5G will enable real-time applications such as remote surgery, autonomous vehicles, and augmented reality. As 5G evolves to standalone networks, network slicing will help deliver consistent performance and low latency for specific applications. The use of AI in enterprise settings will drive the need for faster link performance and lower latency, as large volumes of data need to be processed and decisions need to be returned quickly. However, the distance between the AI and the cloud introduces latency, which hinders decision-making and delivery.
In conclusion, while 5G has been widely adopted in the consumer segment, its adoption in the enterprise market has been slow. The lack of connectivity expertise, killer apps, and significant advantages over Wi-Fi networks are the main barriers. However, there is still potential for 5G in applications and services that extend beyond enterprise walls. The integration of AI and machine learning is also seen as a growth area, although progress in this field is not expected to be significant in the coming year. As 5G evolves and new capabilities are unlocked, it is likely that more innovative use cases will emerge, driving the need for faster link performance and lower latency.