Can AI Help Move Beyond "Something Happened" to "Something Happened and the Network Fixed Itself"?

To say artificial intelligence is trendy is an understatement, experienced routinely by a growing number of consumers in the form of their smartphones and voice-activated assistants, invisibly in their consumption of content.

Investments in artificial intelligence have been highest, to date, in banking, retail, healthcare and manufacturing, IDC estimates. In the communications business, AI use cases arguably have been most pronounced in smartphones, customer service automation and possibly billing.

But it is logical to ask whether AI should not logically come to play a role in network operations and marketing, among other basic functions of communications networks.

Can AI be used by networks to make decisions based on customer activities or location? And does that create incremental value and revenue opportunities?

Can AI help network supervisors move beyond “I know what happened” to “I know what will happen” to “something happened and the network fixed itself?” That is not a terribly new idea, as the notion of “self-healing” networks has been around for some time in the form of ring networks that switch to backup facilities in the event of a primary ring failure.

The promise of AI is the ability to extend self-healing to more parts of the network and its functions.

The former might take the form of informing the creation and tear-down of actual connections and features, provisioning and monitoring of actual network requirements, internally and behalf of customers. The latter might take the form of such important insights as figuring out which customers are about to churn, and then matching new offers to them to address the churn drivers.

In other cases, AI arguably should help determine which customers, devices and services need upgraded features and querying those customers about the upgrades, without human intervention.

In other cases, AI should help inform service providers about which customers have needs for additional products, what solutions are appropriate and then pitching and provisioning without human intervention.

AI should play a role in security as well, but the broader issue is how many mundane, necessary activities could be enhanced by AI in ways that not only reduce costs and waste, but also allow the network to learn to operate more effectively. Right now, almost nothing can be done autonomously.

Ideally, AI would uncover new needs that the network actually can create and then deliver.

In other words, AI should help service providers with the long-held goal of virtualizing the network and enabling instant changes.

In its data centers, Google has used DeepMind to reduce energy consumption 40 percent. Similar benefits should be wrung from AI as applied to the operations of networks and the creation and marketing of its services. The issue is how much more self optimization is possible.

Given the need to continue reducing network operations costs, the use of AI would seem an almost-inevitable outcome.