As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. Machine learning can deliver benefits across telecom provider operations with financially-oriented applications - including fraud mitigation and revenue assurance - which currently make the most compelling use cases. Predictive machine learning applications for network performance optimization and real-time management will introduce more automation and efficient resource utilization.
Marketing automation platforms save time, improve efficiency and increase productivity; but, they do not provide deep insight into the 2.5 quintillion bytes of data being created every day as people move from screen to screen consuming information and making buying decisions. In November 2013, IBM introduced the Watson Ecosystem Program, opening up Watson as a development platform and giving companies the ability to build applications powered by Watson's cognitive computing intelligence. Watson is a cognitive technology that processes information more like a human than a computer -- by understanding natural language, generating hypotheses based on evidence, and learning as it goes. Rather than simply automating manual tasks, artificial intelligence adds a cognitive layer that infinitely expands marketers' ability to process data, identify patterns, and build intelligent strategies and content faster, cheaper and more effectively than humans.