It often is difficult to explain how and why artificial intelligence, as used by telecom and internet service providers, matters. But AI has been used in telecom, in some ways, for as much as a decade.
AI seems essential for operating virtualized networks and already is being used for customer service applications and call centers. Self optimized networks that can reconfigure themselves for better performance without manual intervention are a prime example.
That noted, most professionals in the industry will have little immediate need to make decisions about AI, or perhaps even encounter applied AI in their daily activities.
Beyond that, decision makers who must authorize spending on AI also face issues.
One problem is that AI most often is a process or feature used by applications and networks, not ever a retail end user service or app. End users and customers cannot actually discern when and how AI improves their service, apps and experiences.
The other problem is that applied AI does not actually lead in a direct way to incremental revenue growth, either. As with other features such as voice control or Wi-Fi access, AI can enhance existing products, provider higher perceived value, improve stickiness, reduce churn or ease new customer marketing efforts.
But it is difficult to quantify those effects. AI, when applied to processes, apps or services, does not produce a direct uptick in sales or revenue.
Over time, fee-based services could develop, but it always has been difficult to move customers or users from free products to higher-value paid products. That will be true in both for-profit and nonprofit settings.
That noted, AI might have some of the highest possible impact in the telecom industry, McKinsey consultants believe.
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