Broadband World Forum (BBWF): AI is a pretty hot buzzword at the moment, meaning different things to different people. How do you define AI in your work at KT?

JP Lee (JPL): I'll start off with a bold statement; KT believes that AI is the strategic technology asset that the company simply has to focus on in the future. Currently, KT is the largest telecom operator in Korea and it provides many innovative services to the largest number of corporate and individual customers. But, the biggest challenge with these services is that, as they grow, customer care, network and service quality management become increasingly difficult. Indeed, maintaining cost competitiveness and providing differentiated services are extremely difficult, because KT’s competitors use almost the same equipment based on global standards.

In this sense, AI is a technology that can make a very fundamental difference for service differentiation and quality improvement for customers and contribute to new sales opportunities and cost reduction. Therefore, KT is committed to adopting and expanding AI technology in all directions and is interested in recruiting top-notch AI experts. Unsurprisingly, KT's efforts are expected to continue for years to come.

BBWF: What is the driving force for you and KT to implement AI in your network?

JPL: The biggest driving force in bringing AI to the network was the sponsorship of executives. KT's CEO and other C-levels in various departments such as R&D, Marketing, and Network, believed that KT's core competencies are in the network, and that KT can achieve sustainable competitive advantage in the market by integrating AI with its capabilities. Another big driving force is that Korean customers are not very resistant to adopting new technologies. Indeed, Korean customers are well-known early adopters of new technologies in ICT, and this tendency is a positive factor in expanding AI-based network services.

BBWF: Was this the impetus for the Dr Lauren project?

JPL: The major reason for launching the Dr. Lauren Project was to provide high quality network services to customers and to increase the productivity of human network operators. Dr. Lauren aimed to quickly and efficiently analyze the root causes of network failures that are most relevant to customer service quality among many network operations and maintenance tasks. When the Dr. Lauren project was kicked off, many of KT's network professionals were very suspicious of the actual capabilities of the project, including claims that it would identify a root cause of a failure in less than a minute.

Dr. Lauren was initially applied to analyze the root causes and identify locations of failures in the transport network and outside plants [OSPs] of KT's vast network and is now expanding to the extent that it can predict failures of IP and wireless networks as well. As Dr. Lauren's root cause analysis accuracy continues to improve and the number of networks that can be covered increases, the number of antagonisms and suspicions about AI in KT is slowly diminishing.

In particular, KT does not have a plan to replace existing network experts with AI, but as a companion or supporters of them. The primary goal of using Dr. Lauren is to provide network operators with the opportunity to focus on more productive and important tasks instead of spending their valuable time analyzing repetitive failures. Now, positive perceptions of Lauren are spreading and, as a result, more employees are acknowledging that AI should be the next key differentiator for KT.

BBWF: What was your greatest challenge when deploying Dr Lauren?

JPL: The biggest hurdle for Dr. Lauren is that there are no customer and user experiences. Many people know that AI technology is commonly used in handwriting recognition, autonomous driving, and Go. However, people have very vague concept about AI-driven network operation. This issue will be repeatedly addressed in the future. I expect Dr. Lauren will cope with such homework for quite some time!

BBWF: In your opinion, do you think there is enough collaboration in the industry to create AI solutions for telecoms?

JPL: At present, I think that it is the beginning of AI-driven network operation. In fact, when we started working on the Dr. Lauren Project, we looked at long-term collaborations with prominent developers or purchasing good solutions, but we couldn't find the technology or developers we wanted. Most big IT companies have their own AI experts, but they have very few developers with network expertise. Huawei, Ericsson, Nokia, and Samsung have started developing technologies similar to Dr. Lauren on top of their network equipment. However, it seems that there is not much collaboration in the industry.

BBWF: Finally, how do you see AI impacting the industry in the next 3-5 years?

JPL: This is actually quite a difficult question to answer! In my very personal opinion, and based on my experience developing and deploying Dr. Lauren, I think that AI will be a technology in the telecom industry that will completely change the way we compete. Telecoms operators have been competing in terms of speed, security, and quality in the fixed line, and in the wireless sector, focusing on coverage and price differentiation. However, this type of competition was basically a method in which only a few telcos competed in each region based on global standards. However, as AI spreads in the telecommunications industry, the technology does not have to comply with standards, and what sets it apart is how each company processes and uses its network and service data. In this way, some telecoms may introduce new global AI telecommunication services as Google and Amazon do. As a result, I anticipate that we will see the competition landscape change dramatically.

In addition, by actively utilizing AI technology, telcos can innovate ways to reduce costs. When applying Dr. Lauren, KT realized that AI technology can not only reduce network operation cost but simultaneously improve service quality. In the future, therefore, I think that we will see the telecom industry use AI more aggressively and extensively to reduce operational expenses. Customers will surely experience highly upgraded, differentiated, and AI-driven customer services, marketing communications, as well as network qualities.