With the recent advent of the 5G as a disruptive technology driver for network transformation, CSPs worldwide remain thrilled about 5G’s business potential. At the same time, they are likely overwhelmed with the evaluation, prioritization, experimentation, and commercial rollout of the use cases and services envisioned by 5G. For better or worse, they will be in this mode for the next decade or so, not only because of the enormous potential of 5G but also how challenging and involved its realization will be.
The three principal 5G use case categories comprise:
1. enhanced mobile broadband,
2. massive machine-type communication,
3. ultra-reliable and low-latency communication.
The individual use cases under these categories are far too many to list here as they address diverse industries and sectors such as automotive, entertainment, logistics, manufacturing, transportation, agriculture, education, healthcare, public safety and security, and smart communities. In years to come, there is no doubt that commercial rollout of the emerging use cases in any of these industries will gain much global recognition and lead to a great deal of innovation, both from a technology and business perspective. Based on their deep expertise from edge-to-core-to-cloud, CSPs are in a unique position to lead the 5G innovation.
An equally important development has been happening on the AI front, perhaps at a faster pace. Whether we realize it or not, the age of AI has been upon us for some time now. There is already a large and diverse set of revolutionary AI applications that we knowingly or unknowingly make use of in our daily lives (e.g., while searching for things online, spending time on social networks, coping with spam, using the map, ridesharing, making financial decisions, detecting/preventing fraud, interacting with chatbots replacing customer agents, seeking recommendations of all sorts). An increasing number of sophisticated and fascinating AI applications (e.g., DALL-E, ChatGPT) are on the way.
It is worth noting that AI-driven advancements so far have been largely driven by non-telco players such as Google, Netflix, Facebook, Amazon, and Microsoft. It is unlikely however any industry, discipline, or field that comprises vast amounts of transactional data and that can benefit from advanced data analytics will remain unimpacted by or independent of AI for too long. The telecom industry will be no exception. CSPs, in their quest to 5G, already announced their intentions to leverage AI with a primary focus on reducing the 5G network complexity and achieving autonomous operational capabilities at scale. As a result, a new breed of advanced AI-driven tools and processes for network planning, network performance management, zero-touch automation, lifecycle management, fault detection and isolation, and self-healing are finding their way into the CSP’s network as 5G deployments pick up.
That is a huge first step in a very long journey and CSPs must be grateful to 5G for creating the perfect conditions for AI technology to become an intrinsic part of their network investment. Working synergistically, 5G & AI will drive innovation. It is not until CSPs decide to take further steps to leverage AI to re-invent themselves however, they will be able to seize more profound benefits of AI. One such benefit involves AI’s pivotal role in transforming a CSP’s entire business and operational structure to become much more competitive. Examples from the non-telco world show that it is rather difficult, if not impossible, to realize the full benefits of AI in a traditional [analog] organization and the best results can only be achieved by re-architecting the operating mode of the organization to become digital. For more on the subject, refer to the HBR Press book “Competing in the Age of AI” by authors Lansiti and Lakhani [2020].
From a technology perspective, a CSP becoming more digital implies replacing its siloed data, systems, and solutions with an integrated, modern (i.e., cloud-based) data, analytics, and AI architecture that autonomously drives decision-making and improves itself on an ongoing basis by learning from each new piece of data. From a business perspective, it requires rethinking how a CSP can create and capture value from individual stakeholders (i.e., customers and partners). It implies taking a keen interest in the daily lives of each stakeholder, keeping close track of all kinds of activities, transactions, interactions, relationships, spending, patterns, and trends at a granular level – in similar ways to Google, Netflix, Facebook, Amazon, and Microsoft – and a willingness to experiment with the new to drive continuous improvement and increase operating performance. Last but not the least, from an organizational perspective, becoming more digital requires a culture and mindset change to avoid direct human intervention to the extent possible on the critical path of the product/service-delivery process, move data, analytics, and AI to the center instead, and try to automate the critical operational processes. All these contrasts with the way most CSPs operate today.
With or without 5G, traditional CSPs with complex, bureaucratic, and lagging operating models that rely upon organizational boundaries, structures, and practices set in place over the years will be seriously challenged, leaving them no choice but to transform their operating models in fundamental ways to be able to remain in the competition. CSPs who transform their operating models from analog to digital will flourish and grow their businesses beyond what is possible today. Those who insist upon preserving the restrictive and antiquated operating practices of the past will eventually be forced out of the competition. CSPs with an eye to 5G better have a roadmap in place that allows them to seize the larger potential of AI (above and beyond 5G) to transform their organization into a digital one.
