Examining AI in the Mobile Network Industry
The telecom industry is experiencing technological growth and innovation never seen before, propelled forward by the advent of 5G broadband as well as the internet of things (IoT) capabilities.
Artificial intelligence (AI) is currently experiencing a boom, with many mobile network operating (MNO) companies adopting AI to assist in their complex management operations.
With its multipurpose and multifunction capabilities, AI has the potential to be a key driver for growth in numerous areas, ranging from infrastructure maintenance to sales and retail operations.
AI has also proven itself to be an important part of the larger digital transformation strategies that many telco and MNO enterprises are embracing.
It’s no secret that the mobile communications landscape has experienced serious challenges inhibiting its growth in recent years. AI has been used as both a tool and a solution to overcoming growth challenges that have capped incoming revenue potential. Leading MNOs have already begun to deploy AI technologies across their vast network of processes.
Remaining competitive in this increasingly software-defined, cloud-based environment means MNOs must keep up with tech rollouts as well as the frontrunners championing them to their customers.
The State of AI in the Mobile Network Industry
As it stands, escalating costs for network management have been placing increasing pressure on MNOs for years.
As global traffic and the demand for more network capacity continue to grow, MNOs require increasingly complex and costly network equipment to meet these needs - and the returns on these necessary investment costs are barely outpacing their costs.
On top of this, MNOs also have to contend with changing customer purchasing and engagement habits, which have been influenced by the 2020e-commerce trend, causing online demand to surge.
To navigate these challenges, MNOs need to make important decisions around their investment strategies relating to the customer experience. Simultaneously, they need to optimise and simplify their processes to lower costs without negatively impacting their customer retention rates.
To add to this, MNOs are receiving vast amounts of high-value data from multiple sources, including mobile phones, networks, customer profiles, customers’ online behaviours and purchasing history, geo-location data, customer service and support utilisation, customer communication transcripts, contracts, bills, IoT devices…the list goes on.
MNOs are effectively sitting on a goldmine of intelligence that can help transform and reshape their operations but are failing to do so from alack of data analysis tools that are sufficiently robust to take on the quantity and complexity of data.
AI can assist with all of these industry-wide obstacles and more, as we’ll see below, by utilising smart scheduling, forecasting, machine learning analysis and personalization and other operational efficiencies.
How Can AI Help MNOs Level Up Their Service Offerings to Customers?
Network optimisation
AI is vital for MNOs to use self-optimising networks (SONs) that enable 5G broadband. SONs allow operators to optimise and navigate traffic on their networks based on traffic information by region and time zone.
To do this, AI is used to detect network anomalies through advanced algorithms that look for patterns within the data. This enables MNOs and telcos to detect current anomalies and predict them, allowing them to proactively fix them before they become a serious problem.
Chatbots and virtual assistants
AI can also be used to power conversational AI platforms like virtual assistants and chatbots. Virtual assistants are built to automate and scale conversations with customers and subscribers and can use complex natural language processing to detect and evaluate a customer’s mood based on their choice of language.
Chatbots are also able to communicate with customers and can use machine learning capabilities to respond to questions and provide solutions, simplifying support efforts and reducing call volumes at support centres.
Fraud prevention
MNOs can also harness AI’s analytical prowess to detect, combat and reduce instances of fraud. Using machine learning algorithms, AI can detect real-time anomalies on their networks such as unauthorised network access, fake profiles, and suspicious account activity based on historical data.
The system can automatically restrict or block access as soon as fraudulent activity is detected to minimise potential damage and losses.
Predictive maintenance
AI platforms can leverage predictive analytics to help MNOs monitor and maintain the state of their network infrastructure and equipment.
Advanced algorithms and analysis of data patterns allow AI software to predict future results based on historical data, including anticipating potential network failures or shutdowns based on pattern recognition.
Doing this enables network managers and teams to proactively fix problems and issues before they affect subscribers on the other end.
Robotic process automation
Robotic process automation (RPA) is an AI-driven type of automation technology that streamlines business processes so that they run on autopilot without any manual intervention.
This allows operators to manage their back-end support processes more easily by taking repetitive, time-consuming tasks like order fulfilments and data entry off of their plates, freeing up agents’ and managers’ time so they can focus on more important requirements.
Conclusion
The avenue of AI is still evolving and will continue to impact the mobile network industry in the years to come, bringing more exciting changes and opportunities for MNOs to refine their processes and tap into new revenue models.
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We take on the risk so you can receive all the benefits.
If you’re ready to find out how Airvantage can help your enterprise, book a consultation with us
