Verizon didn’t get off to the best of starts in 2026. On Wednesday 14 January, Verizon Wireless was struck by a widespread outage that disrupted calling, texting, and data services for customers across the US for approximately 10 hours, with the worst disruption reported in New York City, Atlanta, Charlotte, Houston and Brooklyn.

It was a major problem for Verizon, the largest carrier in the US with approximately 146 million subscribers nationwide, as well as a highly-public embarrassment. According to data from Recon Analytics, which polled 1,702 respondents, large businesses reported the highest direct impact: 44% said the outage affected their company, mid-sized companies came in at 33%, while 21% of small businesses were also impacted.

The firm has moved on from that and today the network is delivering, says CEO Daniel Schulman:

Following the actions we took after the January event, our network performance metrics have improved sequentially every month as we embed sophisticated AI models that allow us to autonomously fix network issues in minutes as opposed to hours.

Schulman prefers to pay heed to the first public discussion of its AI Connect initiative, a converged platform integrating network transport, edge compute, and GPU infrastructure into one AI-fit architecture. According to Schulman, its mission scope has expanded:

Our first focus was obviously address our mobility and broadband end-to-end customer experience, fix that, launch our new value proposition, put into place our transformation work streams and assure that we have the right cost structure in place to invest where we needed...we’re clearly beginning to see signs of that success.

But behind the scenes, it was clear that there was a kind of once-in-a-generation opportunity for Verizon to participate in the massive AI infrastructure build-out. As we talked to hyperscalers, alternative cloud providers, enterprises, there was a need for ever-increasing compute power.

Everybody knows about this demand - and the shortfall experienced globally - but the argument has become more layered, suggests Schulman:

The way that that compute power has moved over the last year or so is, at first it was about optimizing racks, and then it was basically saying, ‘How do we combine racks within a data center to optimize compute power?’. Now it really is about, ‘How do you connect data center to data center to assure that you can optimize and maximize the ever-exploding need for compute?’.

And while that data center connectivity demand is exploding, there's an equal amount of desire and demand to power inference models and applications that need ultra low latency, like robotics or remote surgery, autonomous driving, and move that out into the edge as opposed to these big massive data centers.

This plays to Verizon’s strengths, he adds:

Our assets are suddenly in tremendous demand for that data center connectivity.  We have thousands of central offices, many of which were taking copper out of, and we are retro-fitting them to be remote data centers that are power-ready, permitted, fully redundant infrastructure. We did a small trial on that and sold out capability in 24 hours, so we're seeing large demand for that.

Elsewhere Verizon has signed a partnership with Google, valued at over $1 billion, to use Verizon dark fiber to connect their data centers. Schulman pitches: 

We're clearly an attractive player with differentiated assets that are in high demand. We've been building carrier-grade fiber routes for decades. We know how to get it done. We understand permitting. We do our own construction, and we have a solid balance sheet and a solid service reputation that the AI ecosystem needs and counts on.

But he adds:

The demand for these fiber routes that we currently have and that we are building is ultimately limited and that capacity and pricing [is something] we’re going to have to think about [as to] how we handle the demand for that.

This is just the start of something big in revenue terms, Schulman argues:

We believe that this is just the beginning. The build-out of AI infrastructure across the United States is one of the largest capital cycles of our lifetime, and Verizon is uniquely positioned to participate in it.  We own one of the most extensive long-haul and metro fiber footprints in North America. We have spent decades building the kind of carrier-grade, low latency, highly resilient transport network that hyperscalers need to connect compute to compute, model to model and region to region. We built that infrastructure for a different era, but it has turned out to be exactly the right asset for this one.

He adds:

We are moving quickly to expand our TAM (Total Addressable Market) in the rapidly growing AI infrastructure market. The agreements we have signed are the leading edge of a strategy that will become a meaningful incremental leg of growth for Verizon. We expect this initiative to noticeably contribute to our revenue growth starting next year and to grow substantially from there.... We have other deals that we expect to announce by year-end that, taken together, are expected to be worth multiple billions of dollars in revenue over the next several years.

Schulman sums up:

We're fortunate to be in a position where our assets and expertise intersect with this kind of generational demand... we see this accelerating business plus our AI Connect infrastructure providing us with a very different revenue future than we've had in a long, long time...These are long-duration, high-quality contracted revenue streams from some of the most demanding infrastructure customers in the world.

All of this is delivering results, he concludes:

We are fully on track to deliver at least $9 billion of OpEx and CapEx savings we said we would. The 10 transformation initiatives we launched are no longer plans on a page. They are showing up as lower cost to serve faster customer journeys, and a step change in productivity across the organization. 

We are rapidly becoming an AI-centric company in how we operate.

A bold ambition set out for all to see. Can Verizon connect this to long-term success? Time will tell.