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Telcos in APAC Are Betting on AI to Gain a Competitive Edge

Compelling use cases are encouraging telecommunications companies in Asia Pacific (APAC) to invest in, adopt and implement artificial intelligence (AI) solutions at a faster pace than other sectors.

The telecom industry is investing heavily in AI. Investment in this sector is expected to touch US$2.5 billion by 2022, at a compounded annual growth rate (CAGR) of 46.8 percent between 2017 and 2022, and APAC is expected to show the highest CAGR during this period.

A recent study, Artificial Intelligence is Critical to Accelerate Digital Transformation in Asia Pacific, published by Forrester in partnership with Appier, points to the high adoption of AI in the IT and telecom industry in the region. Sixty-four percent of the respondents from the telecom sector say that they are already implementing AI solutions within their businesses. This adoption rate is well ahead of other sectors in the region.

The Impact of AI on Functions Across Enterprises

AI today is impacting every function within an enterprise, from research and product design to sales and customer service.

In one study, 32 percent of decision-makers surveyed believed that by 2020, AI’s greatest competitive impact will be on sales, marketing or customer service. The 2017 Boston Consulting Group (BCG) – MIT Sloan Management Review study “Reshaping Business With Artificial Intelligence” states that customer-facing activities, such as marketing automation, customer service, and support services, will be most impacted by AI over the next five years.

AI has a lot to offer the telecom industry in particular, across different aspects of the business. Telecom operators have access to mind-bogglingly vast amounts of customer and network data. Using AI, they can make sense of this data at a granular level and access rich insights to improve customer service, boost operational efficiency and introduce new revenue streams.

As the Forrester study finds, the telecom sector in APAC aims to use AI in innovative ways in order to stay competitive and flexible, so they can better anticipate and respond to market changes. Additionally, telcos aim to speed up the generation of customer insights and improve existing products and services.

Using AI to Enhance Customer Service and Improve Marketing

Undoubtedly, the fastest growing and most visible use case for AI in this industry is customer service. Telecom companies around the world are using automated chatbots to streamline customer operations and applying machine learning algorithms to make customer service more seamless and cost-efficient.

For example, Ask Spectrum – Spectrum’s AI-powered virtual assistant – can help customers with their questions around their account or Spectrum’s services, and can even help troubleshoot issues. In 2017, Vodafone launched its chatbot TOBi, which simulates human conversation, and live chats with customers to respond to their questions. Closer home, Indonesian telco Telkomsel now only employs chatbots to answer most customer queries.

AI can also be immensely valuable in sales and marketing functions, by creating a personalized user experience and boosting customer engagement and retention. Telcos can use AI tools to analyze users’ preferences, interest areas and past purchase patterns, profile subscribers, and map these onto typical conversion rates to make personalized and relevant recommendations. AI-powered insights can help them recommend the appropriate packages to users, and push these to them at the right time – for example, marketing an add-on package when customer data shows that the subscriber is close to using up their data quota for the month.

Applying AI in Operations

However, the customer angle is only one half of the story. AI can also find application in network optimization and predictive maintenance. AI-powered algorithms monitor network data to detect problems as they occur in real time, and help in quick and efficient resolution. AI can enable a network to self-heal, self-optimize and self-learn, and make decisions autonomously. This ability to detect and solve potential issues before the customer is even aware of them, leads to proactive and enhanced customer service. Additionally, telcos can offer better service delivery through better network performance and improved reliability.

Take the example of SK Telecom, considered a pioneer in the use of AI through the implementation of Tango, its AI-powered network operation system. Used across all of SK Telecom’s telecommunication networks, Tango uses machine learning to analyze network traffic information and optimize network operation.

There are various such examples of how telecom companies all around the world are successfully using AI and machine learning within their operations, but AI implementation in this sector is not without its challenges.

Challenges to the Rapid Adoption of AI

Different studies, including the Forrester report, point to the prevalent barriers to AI adoption across enterprises, including those in the telecom sector. These include:

  1. Difficulty in attracting and developing skilled resources that can implement cutting-edge AI solutions and transform business
  2. Difficulty in building a skilled and agile cross-functional team to work with AI solutions
  3. Security concerns around the adoption of AI solutions
  4. Internal resistance to change within the organization, especially given the popular notion that AI replaces people
  5. Lack of leadership support for AI initiatives, and competing priorities for investment

With AI offering unprecedented opportunities to obtain effective insights into customers and operations, telecom companies in the region are focusing on finding a way around these obstacles in order to accelerate their digital transformation and stay ahead of the competition.


* For more insights into AI adoption across different industries, read our industry-focused infographic and the full Forrester study.

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