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By the end of 2012, T-Mobile US was grappling with considerable obstacles. With a market capitalization under $6 billion, it was falling far behind giants like AT&T and Verizon. However, in 2013, T-Mobile made a bold move by rebranding itself as the “un-carrier,” aiming to stand apart from its competitors through straightforward pricing, flexible contracts, and an array of customer perks. This strategic transformation, paired with the crucial merger with Sprint in 2020—which provided access to vital mid-band spectrum for 5G—ushered T-Mobile into a new chapter. Today, the company boasts a market cap exceeding $200 billion and caters to over 100 million customers, solidifying its position as one of the largest and most valuable mobile networks worldwide.

Despite this remarkable growth, T-Mobile is dedicated to preserving the original spirit and the “punching upwards” mentality that fueled its rapid rise, as stated by CEO and President Mike Sievert. Sievert, who stepped into the CEO role in 2020 after serving as COO since 2015, emphasizes, “We have more opportunities ahead than ever before, as we’ve shifted from a telecommunications company to a technology leader, providing us with a new canvas to serve our customers.”

Through collaborations with leading AI innovators like OpenAI and Nvidia, T-Mobile—recognized by TIME as one of the 100 Most Influential Companies in 2024—is well-positioned to influence the future of connectivity in the coming decade. During a conversation with TIME in November, Sievert shared his thoughts on the company’s future vision.

This interview has been edited and condensed for clarity.

In your recent discussion with Nvidia CEO Jensen Huang, you explored the idea of co-inventing the future. What vision do you have for that future?

Given T-Mobile’s current standing, we possess a significant opportunity to shape the future of connectivity.

Connectivity has never been more crucial in our lives. Just last week, a major storm swept through Seattle, causing a power outage in our home, yet our connectivity remained stable. Although the nearest T-Mobile tower was down, our self-healing network redirected signals from a more distant tower.

It occurred to me that if I had to choose between power and connectivity, I would prioritize connectivity. Being able to check on my kids and my mother, even during a blackout, underscored the vital service we provide. This realization fuels our desire to work with the brightest minds in the industry to envision what connectivity will look like in the next decade.

Unsurprisingly, AI technology will play a pivotal role in this future: networks will be equipped for real-time optimization to ensure top-notch connectivity wherever our users are located.

Together with Jensen, we are pioneering a concept we refer to as AI-RAN (Radio Access Networks). Presently, we have computing capabilities at our thousands of network nodes nationwide, and we plan to virtualize these into 60 data centers near the edge of our network—this will allow us to capitalize on the efficiencies of a centralized, virtualized data center.

Network demands vary throughout the day. By leveraging surplus computing resources to manage AI workloads during off-peak periods, we can significantly enhance the user experience.

What does the virtualization of the network into data centers entail, and how does this improve user experience?

In our core functions, AI-RAN can enable self-correcting networks in real-time, which is essential as data loads continue to rise. AI technology will drive network demands higher, necessitating that we stay ahead of this expanding requirement.

For example, envision a future scenario where you are uploading high-definition video to an AI cloud, but a large vehicle blocks the signal between you and the tower. As you move, the network will automatically adjust to sustain your upload.

We anticipate AI workloads will play a crucial role in the edge cloud. Currently, we have two distinct types of workloads: massive cloud workloads requiring substantial computing resources and local AI processing on devices. These two methods are fundamentally different.

We foresee a “Goldilocks demand,” where emerging large language models (LLMs) will focus more on the processing of video, images, and audio. Effectively analyzing real-time data requires a blend of cloud-like computing capabilities and proximity to the end user, presenting an ideal opportunity for edge clouds.

While we currently do not have a business model in place for this venture, I shared an exciting multi-year plan at our capital markets day that does not incorporate this aspect. Nevertheless, we perceive it as a significant opportunity, especially now that T-Mobile possesses an extensive infrastructure and technological capabilities that were unavailable just a few years ago.

We believe that as AI applications become more immersive, they will benefit from the Goldilocks architecture I described. Whether this assumption holds true remains to be seen, but the good news for our financial prospects is that it doesn’t matter—we’re committed to building it, as it will enhance our core business.

You’ve partnered with OpenAI to develop “IntentCX,” a platform that employs AI to understand and address customer needs in real-time, set to debut in 2025. What does an ideal customer experience look like to you?

A central focus of our strategy is to eliminate pain points. To be an exceptional wireless service provider, we strive to minimize customer interactions by proactively preventing issues.

In 2023, we recorded our lowest churn rate ever—though, given our size, that still meant 8 million individuals switched to other providers. I liken it to an “accident chain”—each customer who departed encountered a series of problems that led to frustration and ultimately their exit. Each of these individuals leaves behind data trails indicating what went wrong and how we could have acted differently.

In the past, we haven’t effectively utilized this data; we’ve merely scratched the surface. However, over the last two years, we’ve focused on restructuring our data systems so that AI can analyze all pertinent information—network data, billing data, customer interactions, and more—simultaneously to trace these trails.

Our aim is to create advanced bot technologies that will genuinely impress. However, it’s not about erecting barriers between us and our customers; it’s about using this technology to foster an experience that deepens their loyalty to us.

T-Mobile has recently transitioned from being a “challenger” to a “champion.” What does this transformation entail?

Leading a team that has achieved remarkable success over the past decade, one of my main challenges is to sustain everyone’s drive, humility, and determination for the future. Our approach has evolved.

In the past, T-Mobile was a smaller player competing against much larger rivals, fostering a culture of striving against giants for our customers’ benefit. We launched the “un-carrier” movement because we were fundamentally different from those larger corporations. We often reminded ourselves that one day we’d reach or even exceed their size, but we must remain unlike them—companies that overlook their customers, take them for granted, and lack innovation. The current question is how we can maintain that ethos amid our success.

This encapsulates our transition from “challenger to champion.” Instead of merely addressing others’ shortcomings, can we set new industry standards that no one else has envisioned? For instance, can we lead the way in offering direct-to-cell service through a partnership with SpaceX, eliminating dead zones and enabling mobile phones to connect directly to custom low Earth orbit satellites? We announced this initiative two years ago and are closing in on its launch. Another example is “T-Priority”—utilizing advanced 5G technology to establish a dedicated 5G network for first responders nationwide. Our focus during this challenger-to-champion phase is pioneering innovations that others cannot replicate.

In a recent earnings call, you referred to T-Mobile’s “secret sauce.” How would you define it?

A defining trait of our success over the past decade is our ability to deliver on our promises—something no other company in our industry can claim. If you were to compare our Capital Markets Day in 2021 with those of our competitors at the same time, you’d find that we are the only company still actively pursuing the initiatives we outlined. This reliability resonates with investors, the public, and our customers, showcasing our execution capability.

Moreover, we must anticipate future trends. Perhaps we were fortunate, or perhaps we were insightful, but a considerable portion of our success stems from recognizing the potential of 5G technology. While much of the industry expected 5G to focus on new devices rather than smartphones and to rely on millimeter wave spectrum, we saw it differently.

We recognized that customers wanted their smartphones to operate seamlessly everywhere, with speeds at least ten times faster than before. The technology to realize this lay in mid-band spectrum within a layered 5G network. Consequently, we acquired Sprint, which held a rich trove of mid-band spectrum but was struggling with its business model. This merger has arguably been the most successful in telecommunications history, laying the groundwork for our current organization.

We accurately predicted the trajectory of 5G, and while competitors are scrambling to catch up, they are years behind. It’s crucial to keep looking forward, and we are determined to get the next era right.

Are there any elements of the future of AI that concern you?

My primary concern lies in the speed at which we adapt. Technologies are advancing rapidly, revolutionizing our interactions with computing and each other. Companies that can foresee these changes, invest wisely, and capitalize on opportunities will thrive. A common debate surrounding AI is whether it’s merely a fleeting trend or if it will genuinely deliver value. I am convinced that this is not an AI bubble; it is our duty as companies like T-Mobile to harness these advancements and demonstrate their transformative potential.

If companies like ours fail to showcase significant breakthroughs enabled by this technology, the perceived benefits will be postponed. This is one reason why firms like OpenAI and Nvidia are eager to collaborate with us—they recognize our proactive stance and share our goal of proving tangible value for end users while generating financial rewards for all parties involved.

We are already tapping into the potential of AI. After two years of diligent work, I announced in September a goal to reduce direct problem-solving and customer service interactions by 75% over the next three years.

We are on the right path to achieving this. We have a comprehensive quarterly plan in place, and we’re already witnessing the value unfold. This is just one of several metrics I shared. We’re proving to ourselves that our goals are attainable, as we’ve laid the groundwork. Our T-Life app is functioning, and by 2025, we will address the most challenging aspects of this initiative. Once we roll out significant delivery elements, I believe we’ll be on the verge of fully realizing this opportunity within the next year, and we can already sense that potential.

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