AI and Phone Numbers – How Evolving Technology is Shaping Telecom
If you voted for:
“The first 1-800 number was introduced by AT&T. As a consumer-friendly alternative to collect calling, the Incoming Wide Area Telephone Service (INWATS) allowed customers to directly call businesses and other organizations without the caller being charged for the call.”
You may be surprised to find that the Dartmouth Summer Research Project on Artificial Intelligence predates the introduction of INWATS by just over ten years!
Just like telephone numbers have evolved tremendously since the mid-21st century – who in the 1960s would’ve guessed that one day you’d be able to use your phone to text with your favorite business or to authenticate your digital identity? – so too has artificial intelligence (AI) made great strides since the term was first coined at the 1956 Dartmouth Summer Research Project on Artificial Intelligence.
When it comes to AI technology, there are two primary types – traditional AI and generative AI. And while both are predicated on the usage of algorithms to parse data, learn from it and make informed decisions, that’s where their purpose, approach and applications diverge. In the case of traditional AI, the technology is most commonly utilized for predictive purposes such as performing particular tasks based on processing large amounts of data within a defined context.
The more dynamic of the two technologies, generative AI, demarcates itself by functioning in a manner that is originative. Specifically, generative AI takes machine learning a step beyond traditional AI and not only recognizes patterns and makes predictions but also generates new content that reflects the characteristics of the data it was trained on – style, tone, voice, etc.
While generative AI such as OpenAI’s Chat Generative Pre-Trained Transformer AKA ChatGPT has taken the world by storm – the AI chatbot is one of the fastest growing software applications in history, having gained 1 million users in its first 5 days and, as of today, boasts over 100 million users – the endless number of practical applications for traditional AI are equally impressive. In fact, with its broad range of use cases, such as AI-powered personal assistance, advanced spam filtering and fraud prevention, it feels like:
AI is EVERYWHERE!
This is especially true for telecom – AI is not only changing the way we work, communicate and connect, but it’s also helping to remove a lot of the friction that has historically impacted our industry.
How exactly is AI improving efficiency, performance and throughput, though? We’ve compiled a list of five of the most compelling advancements and opportunities that AI can provide to the telecom industry:
1. Network Optimization and Efficiency
Adopting machine learning offers organizations an easier and more effective way to analyze massive quantities of data, automate day-to-day network administration and detect potential failures and anomalies. AI-powered network optimization not only helps to provide a more seamless customer experience but also can enhance performance and better yet, reduce overall operating costs.
2. Personalized Experience and Support
Implementing AI can help telecom companies enhance their data on customer behaviors, preferences and usage patterns, all of which can be leveraged to develop unique user experiences. From more informed responses to consumer inquiries to delivering highly- tailored customer service to offering improved support, harnessing AI not only enhances satisfaction but can also potentially boost revenue, consumer retention and brand loyalty.
3. Predictive Maintenance and Service Assurance
Leveraging AI algorithms makes it easier and more efficient for service providers to monitor their network equipment in real-time, identify potential issues and schedule follow-up support. This level of proactive maintenance not only minimizes downtime but can also lead to reduced repair costs, maximized network availability and increased customer satisfaction.
4. Fraud Detection and Mitigation
Telecom operators handle vast amounts of sensitive data, often making them attractive targets for cybercriminals. With AI, businesses can better identify suspicious behavior and potential security breaches as well as detect and mitigate other fraudulent activities. Furthermore, since AI algorithms are continuously learning and adapting, they can help organizations enhance their security efforts, recognize emerging threats sooner and promote overall security and reliability.
5. Intelligent Network Planning and Deployment
AI can optimize infrastructure and expand coverage by facilitating data-driven governance. With more sophisticated intelligence, businesses are better equipped to identify areas of the organization where there is higher demand, thus enabling smarter, better-informed infrastructure development decisions. Whether its enhanced systems placement or optimized base station location, the intelligent network planning data that AI technology can provide has the potential to minimize operating costs, promote improved resource allocation and ensure seamless connectivity.
Although traditional AI and generative AI have clear differences, there is one major commonality that can’t be ignored – AI integration is no longer a nice to have; it’s a MUST have to keep up with innovation and technology. The five benefits detailed above are only a small sampling of ways to integrate AI into telecom, however. With new and emerging use cases such as self-healing networks that help keep the digital world stable and secure and SON (Self-Organizing Network) technology that minimizes the lifecycle cost of running a mobile network, AI is poised to continue to greatly impact our lives.
From network optimization to enhanced fraud prevention, AI clearly provides a boundless range of competitive advantages – competitive advantages that can be leveraged to enhance customer experience AND more importantly for businesses, retention. At a time when consumers are more empowered than ever, ignoring AI is a strategic gamble at best and a one-way ticket to financial ruin at its worse. With this in mind, members of the telecom industry should ask themselves: