Artificial intelligence has found its way into virtually every corner of our lives. It's in our homes, in our cars and in our phones. It can be found across multiple industries including banking, agriculture, healthcare, transportation and telecommunications - to name only a few.
And it's a growth industry.
Through the beginning of October 2017, year-to-date venture capital investment in AI totaled $7.6 billion vs. $5.4 billion in 2016 and $4 billion in 2015, according to the PitchBook Platform.
Not only has investment in AI increased, but M&A activity as well, with tech giants such as Google's Alphabet, Microsoft and Apple all acquiring AI companies over the past two years to enhance and expand their products and services.
So what's driving this interest and investment?
Lots of it and growing.
With the proliferation of devices, the rise of IoT and growth in cloud-based services, there's an ever increasing volume of both customer and network data where AI can be used to understand, optimize and improve business and network capabilities. In addition, AI combined with data analytics can synthesize these huge volumes of data to offer actionable intelligence that will make devices smarter and improve performance.
To date, AI is best known as the technology behind the immensely popular digital voice assistants such as Amazon's Alexa, Google Home or any of the voice assistants found on smartphones such as Apple's Siri or Samsung's Bixby.
Their attraction is the simple fact that users are able to interact with their services and devices without using their hands.
Telecom and AI
But beyond the consumer, AI is finding its way into many telecom networks as a means to help operators improve network efficiency, lower operating costs and improve the quality of both service and customer experience.
In today's telecom networks, operators are already leveraging AI through the use of customer service chat bots that are automating customer service inquiries, routing customers to the proper agent, and routing prospects with buying intent directly to sales people.
However, AI can bring even greater benefits - especially as operators transition their infrastructure with software-defined networking and virtualization technologies. As the network becomes more autonomous, AI will be used to self-diagnose, self-heal and self-orchestrate the network. Additionally, AI will be able to gather and process network data in real time to enable faster decision making.
Since AI systems use algorithms to look for patterns, it will be able to both detect and predict network anomalies, enabling operators to proactively fix problems before customers even notice an issue. In addition, this capability will also help to identify patterns or suspicious activity related to potential security threats - allowing the network to block suspicious traffic in real time before it impacts network performance.
AI will also play a key role in enhancing the customer experience, particularly with respect to subscriber intelligence. It will allow operators to analyze content usage trends, network activity and offer conversion rates, in order to push personalized offers and services to the subscriber at the right time. Furthermore, by being able to simultaneously interpret multiple data points, operators will be able to ensure that proposed new products are sold at the right price - based on an intelligent evaluation of competitor products and impact on existing offers - and offered at the best time to appeal most to potential buyers on a per-customer basis.
The potential for AI in the telecommunications industry remains largely untapped. The continued growth of data - driven by IoT and cloud services - will make automation an operational imperative towards enabling service agility and cost efficiency, particularly as the number of end points grows exponentially larger.
With 5G on the horizon, networks will support a much wider variety of services and applications. This will require the need for autonomous traffic classification and anomaly detection in order to achieve better utilization of network resources - allowing the network to adjust services based on user need, environmental conditions and business goals, resulting in better network optimization.
SDN and NFV may form the foundation for the next generation of networks. But it is AI that will leverage these capabilities to drive new revenue streams and increase customer loyalty, while enhancing network efficiency, improving processes and reducing costs.