AI/Machine Learning in Telecom

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AI/Machine Learning in Telecom

** FUTURE REPORT – Publication date TBA**

Calling for all AI practitioners to share their innovations in the emerging field of AI and Machine Learning in telecom.

Applying AI for improving prediction and business outcomes will transform decision making in most job functions of telecommunication operators in the next decade. AI tools and technology, used in the right context, will improve customer care, network operations and planning, fraud detection, and personalized marketing.

The use cases that we see the highest investment in AI over the next three years in the telecom sector include:
1) A 20-fold improvement in isolating faults and service impacting events
2) More accuracy in predicting demand of network capacity
3) Better asset allocation for capital investments
4) Increases in customer retention
5) Reducing fraudulent transactions
6) Improvements in personalized marketing campaigns
7) Predictive maintenance and avoidance of unnecessary truck rolls
8) Improvement in energy management

If you have a use case that you want to share in the telecom domain, for inclusion in our upcoming report, please provide some initial details to get the process under way.

** FUTURE REPORT – Publication date TBA** 

Publication Date
01/01/2018
Authors
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Applying AI for improving prediction and business outcomes will transform decision making in most job functions of telecommunication operators in the next decade. AI tools and technology, used in the right context, will improve customer care, network operations and planning, fraud detection, and personalized marketing.

– Report Contents

– * How the Market is Evolving
– * Forecast
– * Use cases targeted at specific buyer
– * Techniques to improve the ML model
– * Harvesting and grooming the data sets
– * Supplier Eco-system