AI and Automation to Transform the Telecoms Industry and Impact Society

AI and Automation to Transform the Telecoms Industry and Impact Society

AI and automation reshape the telecommunications industry, enhancing customer service, operational efficiency, and sustainability. Explore these technologies’ impact on society and telecom companies’ future.

The telecommunications sector is experiencing a major transformation fueled by the rise of automation and artificial intelligence (AI) technologies. Telecoms are evolving beyond traditional roles, becoming integral to various sectors such as transportation and healthcare, which are relied upon by billions globally. When harnessed correctly, this data offers rich insights that will usher in a new era of modernization, transforming how the sector operates and enabling telecom companies to offer a best-in-class service to their consumers and wider society beyond this. 

The evolution of telecommunications is anchored in technological advancements, including AI and automation. While automation executes tasks, AI focuses on making informed decisions about those tasks. Combined, they form the cornerstone of the industry’s digital transformation, enhancing customer experience, operational efficiency, and sustainability efforts.

Here are four areas in which AI and automation will transform the telecoms industry and impact society.

Reaching the answer faster

One of the key benefits of AI and automation in telecoms is the boost in customer experience (CX). Societal and technological shifts profoundly impact customer expectations, priorities, and behaviors, with recent research finding that 81% of customers expect faster service as technology advances. Looking ahead, generative AI tools and Large Language Models will increasingly have a role to play in meeting their needs. 

LLMs offer a faster, more effective way to access data. Suppose a consumer has a query and needs to contact their telecoms provider. In that case, LLMs enable them to simply and easily find the information that may be available but is difficult to find, which can often lead to a negative customer experience. LLMs can also bring those capabilities to service reps, enabling them to assist customers with the speed and accuracy they expect. For example, when customers need information on installing a router in their home, LLMs can guide them to the information they need, or a customer service agent can rapidly find the same information and support them. Representatives on different continents can now deal with issues, with instant translation breaking the language barrier. This ease of use is empowering telecom employees across the board.

Making data discoverable

Only now has dealing with data been forbiddenly complex for business users. But, thanks to the generative AI boom, non-technical users are empowered to access and understand data they might otherwise struggle to comprehend. The ability to ask questions using natural language gives business users access to the full power of data sharing. For network engineers, for example, who design networks but don’t engage with data directly, LLMs will offer the potential to find and extract the information they need, let’s say, on local weather patterns, without dealing with complicated and messy data.

This allows the benefits of big data to spread through a company rather than being siloed to a department of trained and well-informed data scientists. As a result, businesses can become data-driven but in an accessible way, whether sitting at a desk or in the field. 

Using AI in the field

It’s well-known how useful AI technology is for pulling out the data needed for the big, strategic decisions around network engineering. Still, it can also be hugely helpful for in-the-moment field responses. Suppose a tree falls and damages a mobile service tower, for example. In that case, it can be difficult for field operatives who don’t have access to all of the data relating to the incident to make decisions without sending crews out to the site. 

LLMs’ data-sifting abilities can make accessing all the data easier and make the big decisions rapidly. LLMs enable teams to access data from geospatial and location-based services, which, combined with satellite imaging, means operatives can see the full picture of what has occurred. As a result, they can send out the right person at the right time, achieving the peak efficiency that only AI can deliver.

Smarter sustainability

Efficiency is becoming ever more important when considering a telecom’s sustainability targets. Companies in the sector face growing pressure from consumers, investors, and regulators to reduce their carbon footprint and achieve net-zero emissions. At the same time, telecom organizations are facing rising service demand sparked by initiatives such as remote work, digitization, and cloud-based solutions. Energy-efficient technologies such as autonomous networks will be critical in the global decarbonization effort. 

So, what is an autonomous network? In the same way, an autonomous car might save fuel by intelligently staying at an optimal speed without unexpected acceleration or deceleration; autonomous networks automatically find the optimal configuration for the network, reducing waste. AI and machine learning (ML) can automate network management tasks, leading to significant cost savings, faster response to network issues, improved customer experience, and, importantly, reduced energy consumption. In the future, truly autonomous networks will handle their energy consumption and operations, heralding a new era of high performance and sustainability. 

Integrating AI and automation within the telecommunications sector will drive a more intelligent era of innovation and efficiency. As telecom companies’ operations are reshaped, the essence of connectivity and service delivery is redefined. At this critical juncture, embracing AI and automation is crucial for fostering customer satisfaction, achieving sustainability goals, and driving forward groundbreaking services. The future of telecoms lies in harnessing these advanced technologies to navigate the complexities of the digital age, ensuring the industry remains a leader in the global economy. This transition, pivotal for the industry and the wider world, demands strategic implementation and visionary leadership to unlock its full potential.