The telecoms industry is poised to be transformed dramatically by Artificial intelligence. Over time, AI will be able to deliver the capabilities and insights telecom operators need in order to automate and proactively address issues in network, service and security operations, and customer care.
However, we’re still very much in the early days when it comes to AI implementation. While AI is gaining a lot of hype there is also growing confusion, with many operators unclear about what AI can do for them — or how to get their AI initiatives off the ground.
To get a better sense of what is and isn’t working for early AI-adopters, Nokia commissioned a research study on the current state of AI in the telecoms industry. Based on nine in-depth interviews with senior leaders responsible for exploring or implementing analytics and AI initiatives, and a global online survey of AI leads at over 50 service providers, here are the five things every service provider needs to know about the journey to implementing AI.
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AI is a journey – not a standalone technology
AI refers to the computing capabilities that allow machines to perform human-like functions in human-like ways, such as inferring and planning. In actuality, there is no single device or application that “does AI” — it encompasses a broad spectrum of concepts and technologies. And in order for it to be effective for service providers, it needs to be embedded in all aspects of the business.
Today’s companies are beginning this implementation journey. Many are already using targeted data analysis to inform human-led decision-making, or even fixed-policy automation where machines follow scripts written by humans. As a next step, companies should aspire to have automation supported by machine learning, with systems and processes that run, learn and self-improve with limited human input. With this step underway, companies will be closer to “the promised land” of AI: fully autonomous systems.
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Companies are looking to AI to improve the present
The service providers surveyed predicted that AI will have the biggest impact in three areas: augmenting sales and marketing, optimizing networks and operations, and enhancing the customer experience. The common thread in these responses was that they intend to use AI to improve existing business processes.
That’s a good starting point, but companies need to play the long game, too. That means thinking about how AI can unlock new revenue streams by monetizing customer data or launching and supporting new services.
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AI rolls out in three main ways – with one clear winner
Nearly one-quarter of survey responders reported that their company is implementing AI through a centralized approach, where a senior executive ensures it stays at the top of the agenda by leading the initiative. Others have set up cross-functional R&D units to serve as “internal vendors” to business units, using AI to solve specific business problems. Some are leaving it to the business units themselves to run their own isolated initiatives.
The final results? Our research shows that companies are much more likely to convert pilot AI projects into live or scaled projects when they adopt some level of centralized coordination. In fact, 82% of those taking a centralized approach have at least one live AI project, compared to just 38% of those running siloed initiatives.
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Providers are in a good position — if they can handle their data
In order to function correctly, AI requires vast quantities of data. The good news is that service providers arguably have more subscriber information than companies in most other industries. But the most useful data must also be of sufficient quality — and that’s where many providers struggle.
With 56% of service providers facing problems with inconsistent or fragmented data, the data they have often isn’t “clean” enough to feed into machine learning algorithms. Additionally, more than 75% of survey respondents said their data storage systems need improvements for the information collected to be labelled and organized in a way AI systems can use. A more disciplined approach to data is needed — one that also accounts for data privacy and security.
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A new approach to partnerships is vital
Very few of the AI projects in our study made it to live deployment. The industry is at risk of getting stuck in a limbo state where AI stalls out and never reaches its full potential — “proof-of-concept purgatory”.
Some level of partnering is necessary, because most service providers don’t have the resources to fully develop or implement AI on their own. However, the traditional way of doing that — rigid procurement processes and buying ready-made solutions — no longer works. Only 29% of telcos who stuck to that traditional approach managed to go live with AI. Compare that to 61% of those who explored ways of working more collaboratively with vendors, and branched out beyond their usual group of vendors.
The pressure for service providers to go “all in” with AI is growing. As customers continue to expect more dynamic, responsive and personalized services, AI will be essential to anticipating and accommodating their needs faster and in a more agile way. Service providers should approach AI projects by picking a place they want to start, then begin to incubate, fine-tune, and learn from their mistakes along the way – because AI is a journey. And companies who start their AI journey now, with these five essential truths in mind, will be putting themselves far ahead of the pack.
