Many confuse artificial intelligence (AI) with what they see in sci-fi movies: machines able to reason, use common sense, achieve conceptual learning and even show creativity, self-awareness and emotions. However, today’s AI technology is far from this futuristic concept.
Today’s AI is more about a technology that can analyse a huge amount of information to take rapid, accurate, around-the-clock decisions to achieve specific goals. But more importantly, today’s AI is not only about technology. It is also about optimizing the interaction of humans with machines and vice versa, to create a collaborative intelligence. That is where the power lies.
We must therefore use it in a core transformative way to rethink how we are doing things and conducting our businesses. Used correctly, AI will allow us to focus on what we are the best at: delivering valuable human interactions.
To this effect, AI’s main impact will be in complementing and augmenting human capabilities, not replacing them. Like having humans with superpowers.
Looking ahead, telecommunication, technology and banking industries have the highest level of interest in adopting AI. However, from a telco point of view, benefits generated by using AI tools will be felt in four main areas:
Customer care: AI can be used here not only to automate interactions with customers, but also to improve customer experience and scoring in general. It is estimated that AI-enhanced network performance will generate industry savings in customer acquisition costs and reduction in loss of revenue of up US$46 billion. Predictive maintenance: At Orange, we have already implemented AI applications which can predict faults and prompt us to deal with the potential issue before it takes place. It is estimated that the industry’s operating profits may increase by US$9 billion, as a result of the reduction of the frequency and duration of network outages.
Radio access network operations: AI-enabled self-organized and fully adaptive mobile network solutions are expected to generate 30% reduction in infrastructure spend and US$14 billion in new revenue. Additionally, the use of such agile network solutions will be crucial in the delivery of a fluid 5G network environment.
Cybersecurity: When it comes to cybersecurity, AI, machine learning (ML) and deep learning (DL) tools will not only enable real-time fraud detection, but will also bring intelligence to help identify patterns and prevent further attacks. It will also be used to help differentiate between real traffic and increasingly sophisticated fraud attempts.
Orange is spearheading its approach to anti-fraud for Voice with 2 key AI-driven services.
“@first”, fights by-pass fraud in two ways: firstly, using a powerful call-tracking system and secondly, with its versatile profiling system. The latter, named TBS-D, is a data mining-based tool, which sits at the crossroads of AI, machine learning and statistical analysis. @first enables users to detect in real-time by-pass calls appearing on their network.
Orionis is Orange’s AI-based voice fraud detection solution, aimed at reinventing fraud prevention. It not only enables Orange to analyse 400 Gigabytes of data daily, but it also helps us identify fraud attempts in real-time. Through AI, machine learning and, in the near future, deep learning, Orionis enables the faster detection and treatment of fraud, which brings customers the peace of mind they need to focus on their core activities instead of fighting the tiresome impacts generated by frauds.
