Artificial intelligence in the telecom industry has been evolving at lightning speed. With global Mobile Network Providers (MNOs) entangled in network management and optimization complexities, traditional hardware dependencies, and more, AI offers to not only resolve legacy challenges but also provide inroads in improving CAPEX and OPEX. Let’s take a look at how this emerging technology is fuelling an industry-wide transformation and what it means for leading market players.
The growing impact of AI in telecom
Machine learning-based AI is helping network controllers witness intelligent network planning in action. From dynamic resource allocation, virtualization, to traffic prediction and management AI is supporting automated decision making. In network optimization, advanced ML algorithms can estimate interference, intelligently update nodes, and self-heal networks. Within operations and maintenance, it aids in detecting network failures, conducting a root cause analysis and initiating predictive hardware maintenance.
In the case of 5G network deployments, the complexities of maintenance, resource allocation, site planning, and surmounting infrastructure costs are some demanding issues impeding the operational efficiency of Communication Service Providers (CSPs). By leveraging AI, these providers can take advantage of automated configurations at reduced costs and maximized network value. What’s more, AI supports low latency applications. Therefore, it plays an indispensable role in the development of intelligent, next-generation equipment to support millimeter wavelength radio frequency.
Startups addressing key challenges
Startups in Self-Organizing Networks (SON), cloud native and the interference cancellation space are addressing prominent challenges in the telecom industry. For autonomous 5G networks, higher cell coverage, bandwidth, and millimeter frequency range are crucial for SON implementations. To ensure smooth implementations, startups are focusing on deep learning algorithms to develop self-healing and self-configuring networks that help boost and sustain high network speeds. Cellwize and Pivotal Commonware are some of the innovators in this space.
Similarly, traditional telecom hardware deters scalability of network deployment and optimization in the case of multiple vendors. To solve this, startups like Altiostar and Affirmed are building cloud-native architectures that enable virtualization, thus removing interdependencies between software and hardware. From eliminating enterprise security threats with the help of patented AI and ML techniques to providing MNOs with actionable user insights on the move, a slew of startups are also developing network security and analytics solutions.
AI adoption by major players
Artificial intelligence in the telecom industry is uncovering advanced applications to maximize business value. For instance, major players eager to offer distinctive customer experiences and enhance their services are leveraging this technology. Telefonica developed Aura, its customer-facing AI platform for understanding billing queries, data usage, etc. Similarly, Verizon launched Digital CX, an end-to-end managed services that leverage AI for enhanced customer support.
In the virtualization space, AT&T developed FlexWare – a network virtualization solution to deploy multiple functions using software only. Moreover, with 65.5% of its network already virtualized by 2018, the enterprise is aiming to reach the 75% benchmark by 2020. Another significant AI adopter, the NTT group is investigating deep learning and neural networks for early network failure detection, traffic prediction, and automating operations.
M&A deals: Technology segments in focus
Netscribes’ analysis of M&A deals since 2014 shows that companies across the telecom ecosystem are acquiring complementary AI technologies to accelerate the adoption of intelligent networks. A majority of high-value investments are being made in cloud native and AI security solutions. Among MNOs, some of the recent deals were made in cybersecurity, with Orange acquiring SecureLink – a leading AL & ML-based security intelligence provider. Among CSPs, Nokia is a prominent buyer in the network analytics space, while Ericsson has been focusing on cloud-native solutions. Other significant acquisitions that took place from 2015 to 2019 were in the SON and predictive analytics sphere.
On a final note, 5G networks, AI-powered chipsets, and SON are some of the top innovation areas driving the adoption of artificial intelligence in the telecom industry. Our research shows that major telecom players are integrating AI to hyper-automate their networks, proactively mitigate security concerns, and elevate customer experiences at scale. As the telecom industry prepares for the next wave disruption understanding the market and competitive landscape through in-depth technology assessments will be key to informing organic and inorganic growth decisions. Speak to us to understand the technology changes occurring in your industry and how your business can leverage them to gain a strategic advantage.