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Eoin Higgins

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 isn’t widely available yet, but the time is likely coming—and with it, the ability for users to deploy the technology for encryption and cryptography.

That includes threat actors. Marc Lijour, an Institute of Electrical and Electronics Engineers researcher, told IT Brew that attackers are already getting ready for the opportunity provided by quantum computing. They are “downloading everything they can at the moment and storing it, basically copying the internet and anything they can so they can open it later [using quantum technology],” he said.

That probably only applies to nation-states, John Bruggeman, a consulting CISO with CBTS and OnX, said. To Bruggeman, the likelihood is low that criminals are storing the information, but high that countries are.

“Probably the world’s largest storage repository is out in [Bluffdale] Utah—thanks to [former Utah senator Orrin Hatch and the NSA—and they are definitely, without a doubt, storing lots and lots of internet traffic waiting for the day when they can decrypt it using a quantum computer,” Bruggeman said.

 have, thus far, been limited in use to researchers and other high-volume projects. But the future of the technology is in commercial viability, Rigetti Computing CEO Subodh Kulkarni told IT Brew: “Almost all of us in the quantum computing field are absolutely convinced.”

Much of the talk around quantum computing remains hypothetical, but it’s fun to think about the possibilities. Oliver Dial, IBM Quantum CTO, told IT Brew that because the most common public key encryption online is based on factoring large number sets, a large enough quantum computer could theoretically break most of it.

“Those machines are still far outside of our reach, and it’s worth noting that there are new encryption protocols that are already approved by NIST, which are not vulnerable to this attack—they’re called quantum safe encryption algorithms,” Dial said. “It’s actually something that the world is working on adopting today to remove that boogeyman from the future.”

Switching encryption algorithms is easier than you might think, Bruggeman said, and “can be done in the background without disrupting day-to-day operations.” Often, users don’t even notice. Changing these backend details can be done quietly; it’s effectively a security software upgrade.

“You change the protocol that you’re using for the encryption algorithm, and now your point-to-point connections are no longer susceptible to man-in-the-middle attacks and harvest and decrypt later,” Bruggeman said.

It’s not a total fix to the issue, but it’s an easy step in the right direction. Bruggeman analogized it to developing fiber- optic internet solutions—one doesn’t have to change hardware as you increase the number of users.

“Imagine a scenario where you have fiber optic in your physical building—you’re in an office building, and you have 1,000 rooms and you have 1,000 people that come into work,” Bruggeman said. “You don’t have to change the fiber, you probably don’t even have to change the switches. The only thing you’d have to change is the backbone communication protocol.”

Update 10/20/2025: John Bruggeman's title has been updated.

Quantum cryptography offers ability to protect from attackers looking to break encryption

“They are definitely, without a doubt, storing lots and lots of internet traffic waiting for the day when they can decrypt it using a quantum computer,” a consulting CISO says.

 it had reached quantum supremacy—that their quantum computer had performed a calculation a regular computer could not—the technology continues to push boundaries.

Classical computing relies on bits (which can be either a 1 or 0) and classical computations involve a single input, algorithm, and output. 

 relies on “qubits,” which exist not only as ones and zeros but in a “superposition” state in-between, allowing quantum computers to analyze multiple solutions and outputs simultaneously. The technology has promise in the encryption space as well as simulations and research applications.

Google’s quantum supremacy was achieved through random circuit sampling, a complicated technical breakthrough that involves registering the output of a set of qubits. This sampling requires a level of processing power that’s not possible with standard computers, even powerful ones. Sergio Boixo, Google’s director of quantum computing, told IT Brew that the discovery was a watershed moment akin to the Wright brothers first taking flight.

“It was the first demonstration that there is a new, different paradigm of computation that allows you to do some things which are practically impossible for classical, traditional computers,” Boixo said. “It was not a commercial application yet, that’s still part of the journey.”

Before Google’s paper came out asserting the success of quantum supremacy, the idea of quantum computing’s viability was still being debated (IBM, which is also a big player in the quantum computing space, 

), superconducting quantum integrated circuit firm Rigetti Computing CEO Subodh Kulkarni told IT Brew. Now it’s no longer a question of if quantum computers will eventually become commercially viable, but when.

“Almost all of us in the quantum computing field are absolutely convinced,” Kulkarni said. “But even the skeptics who always thought this was something of the future and never really going to materialize, I think, can concur with us that this is going to happen.”

Timing is everything, and not everyone is going to agree on the watershed moments. Quantum computing has been in the works for decades. IBM Quantum CTO Oliver Dial is enthusiastic about the overall possibilities of the quantum community, but he points to a slightly earlier mark than Google’s quantum supremacy as key to the technology’s evolution. 

, IBM Quantum Experience’s cloud quantum processors opened the algorithms underlying the technology to a larger group of researchers, he said, which created an opportunity for anyone in the world to use the quantum hardware for research.

“It’s not so much the democratization of this research, although that’s part of what it did, but it’s really kind of making that step from, ‘Were building toys for us to play with ourselves,’ to where we are creating a tool for other people to use and do research with,” Dial said. “So, to me, 2016 is the watershed moment.”

One challenge faced by quantum computers is how to cool the hardware. Dial told IT Brew that IBM bases its quantum computers on supercomputing qubits, which can only operate at low temperatures. The devices are cooled to 0.02 degrees Kelvin above absolute zero, which Dial said is “colder than deep space.” While effective for quantum computers, it’s not a commercially viable technology.

“That is absolutely not something you want in your desktop,” Dial said. “It’s noisy, it’s loud, it’s maintenance-intensive. It belongs in a facility like a data center where we can give it the care and attention that it needs.”

Quantum processors currently provide physicists and other scientists with the tools to do big research projects that simply aren’t realistic with other computers. That’s the main use of the technology for now, Boixo said, but as things continue to move forward, the pool of who will use quantum computers will grow.

Of course, it’s not just scientists trying to uncover the limits of quantum technology who are using the computers. Marc Lijour, a researcher with the Institute of Electrical and Electronics Engineers, told IT Brew that attackers are interested in how quantum computers can potentially crack encryption much faster than traditional computers. They’re probably already playing with the technology, and waiting until the computers are widely available.

“Attackers…are downloading everything they can at the moment and storing it, basically copying the internet and anything they can so they can open it later [using quantum technology],” Lijour said.

That’s still a ways in the future. Boixo estimated chaining together 50–100 logical qubits is about five or so years away. With a number of firms looking at developing the next level of quantum computing, it’s a race. But the real adversary isn’t another company, it’s the limitations of material reality.

“There are, indeed, substantial, fundamental challenges to overcome,” Boixio said. “There is a broad community in quantum computing, there’s a lot of research that gets published by academia, but also industry groups, including ourselves and others. So, the whole field is sort of marching forward, and we’re still competing mostly against nature.”

Is quantum computing poised for another breakthrough?

“It was the first demonstration that there is a new, different paradigm of computation that allows you to do some things which are practically impossible for classical, traditional computers,” a Google exec tells IT Brew of quantum supremacy. 

Billy Hurley

John McKenny began his mainframe career in 1981, managing printers and reports generated by a powerful, refrigerator-size computer built to process and automate then-paper-based workflows at railway company CSX Technology.

Forty-plus years later, McKenny, now SVP and general manager for BMC Software’s mainframe business, helps clients operate and optimize the same mainframe technology from his railroad days—only the tech is now faster, sleeker, smaller, and AI-equipped.

While it’s tempting to think that virtually all modern enterprise IT workloads live in the cloud, or at least within on-premises hardware conceived and designed within the past 20 years, today’s mainframes still support critical applications in insurance, banking, government, and many other firms handling lots of transactions.

But what does the future of the mainframe look like, as more companies push to the cloud and begin to lose track of old languages (like COBOL) found in the decades-old hardware? We spoke with mainframe engineers like McKenny about how the mainframe is modernizing and opening its giant doors to emerging technologies and emerging enthusiasts.

A mainframe, a large-capacity computer with very high processing power, got its name from “the large cabinet or ‘main frame’ that held the central processing unit (CPU) of early computer systems,” 

,” designed in 1937, is considered the first mainframe computer. While early models had dimensions ranging from 2,000 to 10,000 square feet, says IBM, newer releases throughout the decades have shrunk to a more modest size, perfect for slotting into a data center.

Mainframes enable transactions at blazing speeds. IBM’s latest-gen mainframe system, the z17, released in April 2025, for example, boasts a processing capability of “up to 5 million inference operations per second with less than 1 ms response time.”

The mainframe, by design, has built-in features supporting can’t-fail applications, including redundant hardware components, a workload-balancing structure called 

, and advanced warnings of a faulty part.

“I’ve gotten calls from IBM throughout my career, and they’ve said, ‘Hey, one of your memory modules is failing. We’re on our way to replace it’…and nobody has any idea that that failure occurred,” Steven Perva, an expert mainframe innovation engineer at Ensono, told IT Brew.

Almost a century after their creation, mainframes, given their central role to many businesses, have remained in data centers and taken on new features.

One way to modernize, according to Perva, involves changing the software development approach for mainframes. Perva has been using new extensions to enable tools and capabilities familiar to non-mainframers, such as the AI code editor VS Code, the remote-access management interface SSH, and Microsoft Copilot code explanation.

Before these access methods, applications were (and still are, according to Perva) typically developed via TSO/ISPF command-prompt interfaces, also known as “green-screen” interfaces featuring 

-like green text on a black background. API connectivity, introduced by the z/OS Management Facility tool has enabled new coding options, Perva wrote to us in a follow-up email.

“It’s almost like a kid having a job that says, ‘Hey, we have all these new toys that are coming out. We want you to tell us which ones are fun,’” Perva said.

McKenny, too, has seen developers use similar code tools to write and update an application running on the mainframe. “By developing that in VS Code, they have access to look at and interact with information from the mainframe about that application, to get an explanation of that application, to get some insights as to how it works and all that can be done in a modern interface,” McKenny told IT Brew.

Many mainframes feature COBOL—the “Common Business-Oriented Language” invented in the 1950s. Expertise is currently in 

, as modernization, for some, might mean getting rid of all that COBOL.

Hassan Zamat, SVP at Kyndryl and the global practice leader for core enterprise and its mainframe-as-a-service platform zCloud, uses generative and agentic AI tools to translate legacy code like COBOL into modern programming languages like C# or Java, in addition to recommending architectural improvements.

Modernization could also mean a “hybrid” approach, pulling some on-mainframe functions into virtual mainframe environments in the cloud. A common “hybrid” scenario Perva sees: Orgs will move their development environments off the mainframe. “We see a lot of people who want to automate their testing, and they’re not developing all the time, so it doesn’t make sense for them to have a dedicated, forever-running development environment,” Perva said.

Tools like BMC’s AMI Ops and IBM Z’s AIOps use AI capabilities to monitor for disruption-causing events.

BMC’s annual mainframe survey, released in September 2025, revealed an emerging interest in the mainframe from younger IT professionals. Around 66% of the more than 1,000 global mainframe practitioners and stakeholders surveyed identified as millennial or Gen Z—an increase from 37% in 2018. Almost all (97%) of this year’s total respondents see the mainframe as a long-term platform or platform for new workloads—like generative AI assistants and even faster fraud detection and credit-risk scoring, McKenny shared as a few examples.

McKenny hopes to retire in the next 10 years or so, he said, leaving a place for a new generation responsible for taking the platform forward. “When you have someone that has a responsibility to develop on, to secure, to manage, to operate this environment for the next 15 or 20 or 25 years of their career, they’re more interested in looking at, ‘Hey, what are some of the new and different ways that we can exploit the power of this platform?’”

A man at a workstation, circa 1970. Behind him is an IBM System/370 mainframe computer. Credit: f8 Imaging/Getty Images

How the mainframe is modernizing, according to today’s IT pros

Mainframe practitioners discuss the “new toys” they’re playing with these days.

Some AI jobs demand a huge hardware buildout in the office, others require nothing more than a subscription to a cloud-based AI service such as OpenAI or Google Gemini.

Deciding whether to build out a customized AI platform, buy (or rent) one from a third-party vendor, or wait to see what the future brings is a critical choice, especially as many AI deployments haven’t paid off yet. For IT pros who decide to build, how can they ensure their AI hardware and software doesn’t become “shelfware”?

A 2025 MIT study revealed that 95% of 300 publicly disclosed AI initiatives found zero return on their investments.

In many cases when building out customized AI, “the reality is the servers become the equivalent of shelfware,” Dean Chyla, solutions director for compute and AI at solutions integrator Insight Enterprises’s Infrastructure Center of Excellence,

told IT Brew. “They’re sitting there. Maybe configured, maybe not configured, certainly not optimized. And there’s kind of a long road for customers like that, where they need to build the skills to actually use it.”

An org may decide to build their own large language model, or what Sundeep Goel, CEO at financial-control platform for AI infrastructure Mavvrik, called a “mini-AWS” (referring to Amazon Web Services). With the help of hardware like servers and private GPU clusters, companies can create the infrastructure they need to run an AI workload.

Goel sees cost and security as driving factors for this “repatriation,” or the returning of AI services from the cloud to a private data center, especially for industries that face regulations and need tighter control and visibility of their data.

“There’s a real sensitivity around sharing data in a public cloud where your competitors may benefit from it. Or you’re in a regulated industry, and you need to be very careful about what data you use to train public LLMs,” Goel told us.

A Mavvrik study found that 67% of 372 global companies are actively planning to repatriate some AI workloads to owned infrastructure, and another 19% are evaluating the move. “Companies that charge for AI are more likely to plan repatriation, linking monetization with tighter control over infrastructure,” the report said.

While hardware implementations could include servers and GPUs to allow customers to run multiple workloads, the investment doesn’t end there, Chyla warned; there is also infrastructure required, like high-speed networking and storage to support the GPU-enabled servers and feed data into the GPUs. Setting up and maintaining this infrastructure requires IT pros with considerable expertise.

The way to avoid a lack of return on ROI, Chyla advised, is to start with a good plan that engages organizational leaders.

“This should not be something that’s just pushed down from leadership without any input from stakeholders in the business,” he said.

Before buying hardware, Chyla recommends business leaders ask questions like:

What are the use cases that will impact your business? What business units have generated those use cases?

What platform have you chosen to run this on? (“If you choose a pure cloud provider, like one of the hyperscalers, then you’re locking yourself into using that platform for everything. So, is that acceptable to the business?”)

What are your regulatory and security requirements?

Do you have a center of excellence? Who are the stakeholders in that center of excellence?

Goel advised clients, especially software-as-a-service companies deploying their own AI products and training their own models in-house, to do financial analysis before making long-term infrastructure decisions: Measure total costs of ownership in a small pilot-level, and then examine costs at scale.

Some research projects at the Grainger College of Engineering at the University of Illinois Urbana-Champaign 

. Professors, for example, may need to create specialized models for a task using their own research data—say, images of weeds for agricultural recognition systems—to existing models. That fine-tuning requires hardware.

Other Grainger deployments, like the school’s CropWizard from UI U-C’s Center for Digital Agriculture, can use commercial models like ChatGPT or Gemini to consult a specific set of documents for specific answers to agricultural queries. The method, known as retrieval-augmented generation, customizes the general purpose model and requires no GPUs or special hardware.

“By doing that and then tailoring the software stack on top of them for a particular product use case, you can do many, many things today in the AI space without having to train your own models at all, and without even having to host the model,” Grainger computer science professor Vikram Adve told IT Brew.

MIT’s report found that tools like ChatGPT and Copilot are “widely adopted.” Over 80%of organizations have explored or piloted them, but these tools “primarily enhance individual productivity,” not profits and losses. A further 60% of orgs evaluated enterprise-grade systems, the report revealed, but only 20% reached pilot stage and just 5 percent reached production.

Chyla sees the failure as “misalignment with the business.”

“IT is catching a lot of pressure from board of directors, lines of business, executive management to say, ‘We need to do something about AI, without necessarily the support of having an AI strategy in place, [or] having clear use cases defined from business units,” Chyla said.

Collaged images of AI training cluster, binary code, and hands installing hardware equipment. (Credit: Illustration: Anna Kim, Photos: Adobe Stock)

How to find the right amount of hardware (or software) for the AI job

IT pros share how to prevent AI hardware from becoming shelfware.

Look, up in the cloud! It’s a bird! It’s a plane! It’s a…petaflop?

Supercomputers have come a long way since the days of Deep Thought. Today’s mainframes have processing power that was a fantasy just decades ago, and the advent of new technologies such as AI may only boost their capabilities in coming years.

Petaflops are a unit of measurement for processing power. “Flop” refers to “floating-point operations,” Nvidia Product Leader Dion Harris explained, and “peta” indicates a quadrillion of those per second. It’s a huge number.

The petaflop supercomputer has existed for nearly two decades, and it’s capable of incredible feats. Harris analogized it to using a computer to build a plane.

“You have to simulate the wing, and then you’ll simulate the nose cone, and you’ll simulate the landing gear,” Harris said. “But if you had enough computational power, theoretically, you could simulate the entire plane at the same time with the same level of fidelity.”

Currently, the most powerful petaflop supercomputer in the world 

 at US Department of Energy-funded Lawrence Livermore National Laboratory in California.

The federal government isn’t the only organization with access to that sort of power. Just in the last year, the technology has seen an explosion in accessibility, with smaller petaflop-capable supercomputers hitting the market from Nvidia, Asus, Dell, and others. That increase in access has come as AI capabilities have skyrocketed. As Nvidia CEO Jensen Huang 

: “AI has transformed every layer of the computing stack. It stands to reason a new class of computers would emerge—designed for AI-native developers and to run AI-native applications.”

Today’s supercomputers have gone beyond petaflops and into exaflops. If a petaflop is 10 to the 12th power, an exaflop is 10 to the 18th.

One big change that occurred in the last decade to make that leap possible, Harris told IT Brew, is mixed precision, which allows users to determine which aspects of the computer’s calculations can be executed with less precision—freeing up capacity to do more.

“Think of it like a hammer and a chisel—in other words, the fine-grained elements use it for what you need,” Harris said. “But there are some areas where you can just use a hammer to get down to the crude, fundamental building blocks before you need to do the fine-detail level work that requires more precision.”

AI’s input in the supercomputer process has accelerated the space. What comes next is anyone’s guess, but Jim Piazza, VP of AI, Machine Learning, and Predictive Systems for Ensono, wonders if we might see laypeople rather than scientists and engineers running ultra-complicated simulations. That’s just one potential advancement as the underlying technology continues to evolve.

“Over the last 10 years, we saw an 80%-ish increase in petaflop performance,” Piazza said, adding, “if we follow that curve, and even if you expect that, there’s some point where we won’t see quite as many gains. I do think that we’ll see 5,000-plus petaflops of performance over the next couple of years.”

As supercomputing becomes ubiquitous, Piazza said, advancements could come quickly. It’s a question of access to the technology, he added, that can open the door to working through difficult problems. Piazza told IT Brew he could potentially see changes coming in the next three to five years.

“It’s a good thing for us as humans on the planet to have that technology be accessible to a wider audience,” Piazza said. “Now, obviously you could play devil’s advocate and say there’s also the opportunity for bad actors to creep into that space. But I’m a positive person by nature, and I’d like to believe that people are going to use that power for good, in solving real world problems in that time frame.”

Supercomputers accelerated with petaflops, and AI promises to push the technology further.

Supercomputers accelerated with petaflops, AI promises to push the technology further

“It’s a good thing for us as humans on the planet to have that technology be accessible to a wider audience,” one expert says. 

Brianna Monsanto

In a country so divided, one thing unites us all: the USB-Type C connector.

 USB-Type C, also known as USB-C or just Type-C, is the connector with the small oval-shaped port that seemingly comes with all of your electronic devices these days. And by all, we mean 

“Airplanes, automobiles, cell phones, desk lamps, displays, electronic toothbrushes, medical electronics, power tools, wall sockets. It’s literally everywhere,” Jeff Ravencraft, president and COO of the USB Implementers Forum (USB-IF), a nonprofit organization that looks after the standards for USB technology, told IT Brew.

For the average person, the USB-C connector may be the reason why forgetting a phone charger at home is less of a headache these days: Just ask anyone around, and chances are good someone is carrying one. The widespread shift to USB-C in the past decade marked a significant turning point in the hardware industry.

 USB-C connectors first hit the scene in 2014 when the USB-IF released Type-C specification 1.0. At the time, the tech industry was ripe for a new connector, several hardware experts told IT Brew. One big reason was the desire for a jack-of-all-trades connector that was capable of charging, transmitting high-performance data, and supporting high-performance display, said Ben Hacker, general manager of Intel’s client connectivity division.

“Typically, for the highest performance things, that would be a dedicated connector just for that,” Hacker said. “So, just the best display connector, maybe just the best data connector, and then charging, historically, had been separate.”

Hacker, who joined Intel as a full-time staffer in 2004, added that the tech industry yearned for a singular connector that could be used beyond just the PC market.

Around this time, Ravencraft added, the industry was at an inflection point. Smaller form-factors were emerging, including mobile phones, MP3 players, digital cameras, and more. While Mini-B and the Micro USB connectors were available, these predecessor connectors weren’t designed to support large devices.

“They were originally designed specifically to support cell phones and they were not really robust enough for larger devices,” said Ravencraft, who worked as a senior technology strategist at Intel for more than two decades before becoming the president of the USB-IF in 2010.

Abdul R. Ismail, senior principal engineer at Intel and chairman of the USB-IF, said the quest for a new connector was also driven by the changing function of USB technology and power demands.

“It used to be [that] keyboards and mice and hubs were the number one thing that people were using USB for,” Ismail said. “That transitioned to power. People were using it for charging all the time.”

USB-C connector caught the attention of the tech sector. According to Ismail it successfully combined the three functions that previously required a variety of connectors to accomplish. USB-C specification 1.0 was able to support up to 100 watts of power. In comparison, Micro USB can support up to 7.5 watts.

“You plug your laptop and you just have one cable going into it and you can do power, you can do your video out, and you can do all your other data as well,” Ismail said.

The USB-C connector also had a reversible design, meaning that it didn’t matter which way you plugged it in. Kevin Koestler, business lead of USB-C controllers at Texas Instruments, said this was previously a large pain point for USB-A users.

“You have a 50/50 chance of making sure the Type A port is plugged in,” added Koestler, who joined Texas Instruments in 2017.

USB-C connector was kind of a big deal because it “changed the paradigm” of how people thought of USB; traditionally, USB cords had a different connector at each end of the cable (for instance, one side may plug into your computer while the other into your phone). However, USB-C introduced the new concept of having both ends have a Type C connector.

“That was kind of a new experience for customers and users and people who are just buying the technology and aren’t deep in the weeds of engineering,” Hacker said.

While the USB-C connector had an attractive design and advanced functionality, it was an open question whether the industry would embrace the newcomer. Ravencraft said a connector transition is one of the “hardest transitions a company can make.”

“A connector change is the most difficult change you can make in the industry, second to none,” Ravencraft said. “It affects the consumer. The consumer doesn’t necessarily want to get rid of a product that they paid good money for and it still works fine.”

Despite this, Ismail called the transition to USB-C the “fastest-adopted change in connected technology” the USB-IF has worked on.

So, how exactly did USB-C connectors become ubiquitous in today’s tech landscape? Koestler said the transition happened in three waves. The first occurred within the PC, notebook, and laptop industry.

“It was a natural evolution,” Koestler said. “They had Type A. They wanted something that was reversible, that had higher data, higher power, and so that transition was pretty seamless.”

He recalled Google’s Chromebooks as one of the first devices to take the big leap to Type C. In March 2015, Google 

 that its new Chromebook Pixel would have a USB-C port.

That next month, Apple released its first MacBook with a USB-Type C port and went so far as to make USB-Type C the sole port for the device. Hacker called the move “bold” and said it garnered a lot of 

“That’s a testament to how much they thought that connector was really gonna take over the world, which eventually it has,” he said.

Koestler said the next big wave occurred when the European Union made a successful push for a single connector in a bid to reduce e-waste and provide convenience to customers. In 2022, the EU Parliament voted in favor of requiring phones and small devices to have USB-C ports, giving companies two years to comply. Koestler said this ultimately led to USB-C ports being added to phones, with Apple leading this wave. Apple’s iPhone 15 family of phones sported the Type-C ports. The Galaxy Note 7, released in 2016, was the first Samsung phone to have the new port.

The last and current wave has occurred among a wider range of equipment and industries, Koestler said.

“Not only is it consumer electronics, but now we’re starting to see another wave of industrial equipment…appliances, e-bikes, wireless speakers, server racks, even access points, [and] routers,” he said.

Today, USB-C connectors and ports have become ubiquitous. In fact, the connectors are so universal that manufacturers are taking note.

“We’re starting to see some interesting trends where the customers that we deal with don’t want to ship a charger at all,” Koestler said. “Because it’s so universal, now our customers can just make their end product and then they just assume that the consumer, us, would have a USB-C charger.”

Ravencraft, who says he has dedicated most of his life to USB technology, said USB-C has “hit the high-end sweet spot on power.” The latest specification of USB-C technology allows it to support up to 240 watts of power.

“We believe for where we’re at with data performance as well as power, that we have plenty of headroom with this connector,” Ravencraft said.

Close up of a USB-C plugged into a laptop.

How USB-C stole the heart of the hardware industry

Mobile phones, desk lamps, displays, electronic toothbrushes, power tools…if it needs power, chances are good it has a USB port. How did that happen?

In 2011, Prakash Arunkundrum took a trip to the Logitech office for a videoconference meeting with a participant in another part of the world. Today, the task may seem mundane, but back then, getting on a videoconference call could feel like something it took a village to do.

“Either the bandwidth won’t work, or you wouldn’t know which button to press, or you had a bunch of controllers and you didn’t know which controllers to use,” Arunkundrum said, adding that he ultimately waved his white flag and called for IT help the day of his videocall.

Arunkundrum, now president of Logitech for Business (L4B), Logitech’s enterprise solutions arm, said things are much different now, partly because of the company’s early efforts to simplify workplace technology.

Since 2011, L4B, formerly known as Logitech Video Collaboration, has had big dreams for enhancing videoconference communication. The BCC950 ConferenceCam, one of the first products in L4B’s lineup, aimed to deliver high-quality audio and video through an easy-to-use interface. The device propelled Logitech—which Arunkundrum said was once known predominantly as a “mouse company”—into the unified communications category.

Those bets paid off. Today, one in three meeting rooms and desk solutions use Logitech’s workplace tech, according to data shared by the company.

“We are in finance. We are in boardrooms. We are in startups. We are at your coffee shop,” Arunkundrum said.

Logitech’s early foresight helped propel it to become a leader in enterprise technology as the pandemic transformed workplace norms.

Prior to Logitech’s enterprise product line taking off, Moor Insights & Strategy VP and Principal Analyst Melody Brue said Logitech was known for its selection of computer peripherals.

“They’re known for their keyboards, their webcams, headsets, conferencing systems, and then more consumer gaming accessories,” Brue said.

Arunkundrum said Logitech had wanted to simplify conference room tech, which he noted was “super complex” in the early 2010s. While the BCC950 was the business group’s first product, Arunkundrum called Logitech MeetUp, an all-in-one conference camera device first released in 2017, L4B’s “breakthrough” product because of how it simplified the conference experience.

“We’ve sold over a million units of those over the years, and it’s the fastest-growing meeting room category,” Arunkundrum said. “So, we essentially super-simplified that whole experience.”

 And then, just like that, Covid-19 happened.

When the pandemic hit and forced many workers to adopt hybrid and remote working styles, Arunkundrum said demand for Logitech products surged, both on the video collaboration side and the personal workspace front.

“I’d say there was a Goldilocks moment where some of our foresight actually got fast-forwarded because of Covid,” he said. Webcams on Logitech’s website quickly sold out “due to high demand” during the peak of the pandemic.

 announcing the tech company’s Q4 financial results for the 2021 fiscal year, former Logitech CEO Bracken Darrell said the company had its best year yet. Logitech brought in $5.25 billion in sales that year, an unprecedented amount for the company.

“Our powerful and resilient capabilities allowed us to both deliver remarkable performance in a challenging FY 2021, and at the same time, invest in compelling plans for the future,” Darrell, who departed Logitech in 2023, said at the time. “The world has just caught a glimpse of what Logitech will become.”

The company’s growing traction didn’t end there. Crawford Del Prete, president of IDC, said the pandemic’s lasting impact on the office continued to aid Logitech’s success.

“We’ve all read the stories of the companies that say everybody’s got to come back,” Del Prete said. “Well, the reality is people now work from both places, and because they work from both places, that’s been a tailwind to Logitech’s business.”

Arunkundrum said L4B currently makes up 40% of Logitech’s overall revenue. While the pandemic may now be a not-so distant memory, the business group still has big plans for workplace tech.

In January, the tech company announced Logitech Spot, an office sensor capable of tracking a room’s stats like occupancy, temperature, and humidity in order to make automated changes (e.g., automatically making a room available to book for meetings if its current meeting ends early). In the same month, Logitech also announced Rally Board 65, an “all-in-one portable videoconference solution” that quickly equips the room or small space it occupies with the tools needed for a collaborative conference room.

Arunkundrum said L4B is focused on solutions that enhance the workplace experience as the IT professional role increasingly evolves to support the needs of employees and their workplace environment.

“Facilities, IT, and HR are working closer together than I’ve ever seen, and I think this is certainly something that we are helping equip as part of our technology,” he said.

Del Prete said the new era of products reflects Logitech’s ability to pivot its focus to new areas and innovations.

“They see these opportunities and they move to them and then that becomes a category expander for them,” Del Prete said. “And I think that’s really one of the marvelous features about the company.”

Update: An earlier version of this article referred to the acronym for Logitech for Business as “LOB.” Internally, it is called “L4B.” 

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