TLS telstra group limited

Ther have been numerous reports that the rise in the use of...

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    Ther have been numerous reports that the rise in the use of Artificial Intelligence technologies may be particularly beneficial for telcom companies- & will increase profitability (as they will likely require less staff, & other efficiency savings). Eg.

    V. Pulakhandam said

    "The Continuous Drive to Boost Revenue

    Along with this opportunity, however, comes the continuous pursuit of and need for revenue growth. AI is helping telecom organizations reach this goal quickly, while also improving network capabilities and enabling faster processing of large volumes of data.

    Telecom operators are now looking for ways to optimize, disrupt and innovate. They can do so by embracing data, ML and AI. These technologies will not only lead to greater efficiencies, but also to increased revenue and improved margins. To reach their revenue goals, telcos should focus on use cases across all aspects of their business, build common data infrastructure and integrate ML into workflows and processes.

    New Opportunities Await

    AI and ML are boosting innovation in telecom, providing opportunities for new ideas to accelerate digital transformation. These opportunities can come in a variety of ways, including:

    • Better customer service – such as automating customer service inquiries, routing customers to the right agent, etc.
    • Network optimization – giving telecom companies the ability to identify the root causes of complications in network operations. The ability to optimize customer interactions, network design, planning, operations and more allows for optimized CAPEX and OPEX resource allocations.
    • Predictive maintenance for example, AI-based predictive analytics can help telecoms provide better services by proactively fixing problems with communications hardware; monitoring the state of equipment, anticipating failure based on patterns and more.
    • Fraud detection – including theft or fake profiles, behavioral fraud and other activity. Applying ML algorithms to customer and operator data can help prevent fraud and provide real-time responses to any suspicious activity".


 
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