CNBC Technology Summit 2026: AI news and live updates

There is plenty of debate around which AI firm will be at the top of the mountain as the technology continues to be deployed across the economy and society.

But from the perspective of Calix CEO Michael Weening, for companies like his that are using those models to deliver platforms to customers, it’s critical that organizations design their systems to be ready for any future.

“If we keep all the things that are valuable, which is we have the knowledge, we have all the workflows, we have the trust and security … as they commoditize, we can actually just flip the open-weight model out and put a new one in, and just keep flipping them in and out as these guys go to war,” Weening said. “We’re going to go take the best of the best at all times.”

Weening said he is increasingly betting that the future is based in open-weight models after what he said would be a “mass commoditization” of AI.

“We firmly believe that you’re going to see a mass commoditization, and that there is no value in AI because these are self-learning systems, and therefore they’re going to be commodities,” he said. “We wanted to be able to take advantage of what’s the best commodity on the market today.”

Calix Chief Product Officer Shane Eleniak said it’s becoming clear that the problems that the company is trying to solve, like many other companies, won’t be solved “with a generalist, centralized approach. It’s going to need to be specialized.”

“You just look at the scale of the problem. It’s no different than saying, why do we have brain surgeons and car mechanics? They’re very, very different skill sets. You start looking at security. You start looking at some of the bigger distributed problems. You’re not going to solve that with the centralized approach,” he said.

— Ian Thomas

Rapidly evolving technology has the potential to create a sort of whiplash for companies and workers alike. CNBC’s Susan Caminiti asked Paychex CHRO Mason Argiropoulos and Crum & Forster CHRO Barbara Katz if the firm has seen signs that employees are getting overwhelmed by the pace of change.  

Argiropoulos said he has actually seen that “folks are pretty hungry for it,” asking questions like when they’d be able to use certain tools. “I think we’ve got a lot more folks probably leaning in than you might originally think,” he said.  

He thinks the biggest challenges will be at the enterprise level. “We want individuals to kind of do what they can in their power to help them be more efficient, more effective at the work that they’re doing. But we have to think about, what does that mean for an entire company,” he said.  

Katz said, similarly, that she thinks workers are embracing the technology, but acknowledged that some have a level of fear, “particularly in pockets of jobs that we know are the most vulnerable to replacement,” she said.  

“I think my worry really has more to do with what the workplace of tomorrow looks like, what are the skills that we’re hiring for, and how do I get my leaders to understand that they’re not hiring for the same things anymore, and that in itself is is really a mountain to climb,” Katz added.  

— Colleen McKown 

Companies are dealing with the challenge of harnessing AI while balancing the needs of their employees. 

When asked how she is dealing with the pace of change, Crum & Forster CHRO Barbra Katz, told CNBC’s Susan Caminiti, “I think it’s about taking into account the people before the technology and really taking the time to understand what the process is that we want to address.”  

“For me, the message is really just slowing down, and really all the voices at the table being there,” said Katz, a member of the CNBC Workforce Executive Council.  

“It’s very important for us as HR leaders to also understand the tech, so that we can understand the impact on people,” she said.  

Paychex CHRO Mason Argiropoulos, also a member of CNBC’s Workforce Executive Council, added that it’s important to recognize that people are in different places when it come to understanding AI.  

For instance, while developers and engineers can find the technology exciting, others in the organization see the technology as “still is a little bit scary … there is a worry that if I get too good at this, does that mean I’m going to be out of a job?”

It’s important for HR leaders, Argiropoulos said, to “meet people where they are.”  

Katz said at Crum & Forster, they have tried to make AI fun for employees. For instance, they recently created a bot of CEO Marc Adee.

“Everything he’s ever said on a Friday is captured in what we call the Marc Bot, and so for our employees, it’s become a great tool,” she said.   

“Before someone meets him for the first time, they go on and they ask Marc Bot some questions,” she explained. “So they’re able to sit there and say, ‘on January 12, you said this, and I was thinking about it.’ So it’s become a a great tool to understand his perspective and perspectives about the business.”  

— Colleen McKown 

The debate around slowing down AI development to address safety issues is only growing as bleeding edge AI researchers from OpenAI and Anthropic publicly urging for it over self-improving AI and its risks.

But while continued AI development is critical for enterprises that are looking for AI ROI, this news cycle is not as critical for the way they’re using it.

CNBC’s Jon Fortt noted to Publicis Sapient CEO Nigel Vaz that there is “this idea that a really powerful general model is always going to get to the answer eventually better than any specialized model or expert … it doesn’t seem to necessarily work that way with safety,” Fortt said. “Maybe it’s going to find its way toward an answer, but it might break your kneecaps on the way getting there, right?”  

Vaz acknowledged that safety is one dimension, but said, “As much as organizations talk about safety and it’s important to everybody, the first thing that hits you is the cost. And let me start with that. Like that’s the equivalent of basically saying, ‘Hey, I need to hang a picture on my wall. But is the best use to hang the picture on the wall a sledgehammer or a little hammer?'”  

“When you actually talk about a large language model getting to the answer eventually better than a small language model, the context matters a whole hell of a lot because the choice of which model, how it actually gets there, and whether you even need it to get there,” Vaz said.  

Vaz said that the conversation about models being paused is “almost irrelevant to most enterprises.” 

“It doesn’t matter. They haven’t even leveraged the models that exist today to the fullest extent that they can,” he said.  

— Colleen McKown 

During an appearance at the Stanford Graduate School of Business, OpenAI CEO Sam Altman said that the growing AI-powered cybersecurity crisis is far from over.

“This cybersecurity…I don’t even know a dramatic enough word to use, but the problem coming towards us, I think, is still something that we have not, as organizational leaders or countries or individuals, taken seriously,” Altman said, according to Gizmodo.

At the CNBC Technology Executive Council Summit, Forum AI Founder and CEO Campbell Brown said that she sees a “rocky six months” ahead in this space, especially as the general public becomes more aware of the hacks and leaks that are occurring.

However, Calix CEO Michael Weening and CPO Shane Eleniak said they see the problem not only getting significantly worse but that the potential risk is even higher than anyone is forecasting.

“We haven’t seen anything,” Weening said. “The pace of change that we’re going through societally is something humankind is not ready for.”

Eleniak said to this point, these sort of large-scale AI-driven attacks have been a “nation-state problem” so far, largely due to the cost it would take to form such an attack.

But he said as open-weight models and economical GPUs become more accessible to bad actors, “something is going to happen; we’re all going to read about it.”

“You can take an open-weight model today, train it, and you can train it to be malignant, and you can run it on GPUs, and you can start to attack things,” he said. “That’s the security problem we’re going to be facing in ’27.”

Eleniak said the only way to combat this as things move forward is to have “container- trained models that their day job is to react to a dynamic attack and fix them.”

— Ian Thomas

Companies have been grappling with the challenge of harnessing AI in the hiring process. Barbara Katz, Crum and Foster CHRO, expressed skepticism when it comes to leveraging the technology that currently exists.  

“We’ve looked at technology to identify or to help you to identify the fraudulent candidates, and frankly, I wasn’t comfortable with a lot of the tech that’s out there. Some of the companies really don’t have a good business case. They haven’t been in business long enough,” Katz, a member of the CNBC Workforce Executive Council, said.  

Katz said she still prefers an “old school” approach. “My recruiters are like detectives; they’re doing a whole dossier on people before they hire them, they’re searching to figure out where people went to school and coming up with trick questions to see if they know who the mascot is,” she said.  

Mason Argiropoulos, Paychex CHRO, said he is taking a similar approach, “wading cautiously into the new tech landscape.”  

“At the end of the day, companies are collections of people,” he said. “We’re going to be doing interviews face to face when we can.”  

— Colleen McKown 

Pointing to the lights above the stage at the 2026 CNBC Technology Executive Council Summit, Publicis Sapient CEO Nigel Vaz told CNBC’s Jon Fortt that one of the issues that is plaguing companies when it comes to AI use is thinking about usage like lighting.

“So many conversations around tokens are like if I said to you if you could pay me for three watts,” Vaz said. “The question you want to know is will that turn on that light bulb or not, because what I care about is paying you for a unit of work.”

Vaz took the lighting metaphor a step further when Fortt asked him how AI ROI measurement should work then.

“Most employees want to see that they’re creating value through the work that they’re generating. So effectively deploying AI as like a dimmer switch to make everybody just a little brighter,” he said. “We are already past that phase.”

Vaz said AI usage needs to be grounded in outcomes that workers can understand, “and then contextualized about how it’s going to change their lives in that context.”

“The other way around, which is I think where a lot of AI projects started was, ‘Let’s deploy AI more broadly across the enterprise. Let’s give lots of people access. Let’s run a lot of experiments,'” he said. “I think you get value, but you make everybody just a little bit brighter. You may not meaningfully move the needle on a specific outcome.”

— Ian Thomas

Factual accuracy and political bias remain significant issues for AI consumer-focused outputs.

Forum AI Founder and CEO Campbell Brown said recent research by her firm suggests that 40% of all outputs had at least one major mistake or got one claim wrong.

“That’s not great,” she told CNBC’s Scott Wapner.

That is being amplified in the lead-up to the midterm elections, when people turn to chatbots or AI-powered search engines to ask where their polling places are, when they need to register, or what topics are on the ballot.

“You get those questions wrong, and you are taking away someone’s right to vote,” she said.

On top of that, Brown said that Forum AI’s research found instances of Anthropic’s Claude “pulling from the Chinese Communist Party website to answer questions about a U.S. election that had nothing to do with China.

“This, to me, is low-hanging fruit,” she said.

Wapner asked Brown whether AI labs are currently incentivized to correct that accuracy, or whether the focus on enterprise applications of AI is taking precedence.

“It’s been a low priority,” she said. “They’re making so much money from coding … this is a room full of CTOs, you know what they’re doing, and that’s where the emphasis has been. The consumer use cases have been less important.”

A TEC member asked Brown if she saw a future where the consumer becomes a priority for AI outputs, especially given the heavy adoption split so far between enterprise and consumer revenue generation.

“I don’t think the consumer is going to be a priority for a while; they’re just making too much money on the enterprise side, and they really don’t talk about political evals or election evals until we get public research and it gets picked up by the press,” Brown said. “It’s just not a priority and won’t be for a while until something happens.”

Brown pointed to how AI labs have reacted amid concerns around mental health, which she said has been “a wake-up call for them.”

“They sort of unleashed this and didn’t realize what a big use case that was going to be, especially with teenagers, and then you have these horrible incidents happening and litigation flooding into the labs,” she said. “So now they’re bringing in clinicians and people who actually know what they’re talking about … it goes back to the importance of having real expertise in the process.”

AI is creating new, fundamentally different operating models for businesses. But often AI engineers are not understanding the business in which they are operating, creating multiple issues when tracking ROI and success of the technology.

Nigel Vaz, Publicis Sapient CEO, told CNBC’s Jon Fortt that he was at a breakfast before the CNBC Technology Executive Council Summit where he met with a group of clients that his firm works with.

The CIO of an investment bank that Publicis Sapient works with told Vaz that the bank recently brought in some engineers from Anthropic.

“The client said, ‘I have 50,000 developers, and they gave me six incredible AI engineers from Anthropic. But they don’t understand investment banking. They don’t understand the bespoke coding language we use in the bank,'” Vaz said.

The client was highlighting something, Vaz said, that he continuously hears which is that people need to think about AI beyond the context of the technology, “because a technology or a tool given to an enterprise is just one part of the problem.”

“You need some people who understand the context of the business, not in terms of how it operates today, but who have a perspective on how it’s going to operate tomorrow because they’ve got to get somebody from here to there,” he said.

— Colleen McKown 

In a Wall Street Journal op-ed published in June, Forum AI Founder and CEO Campbell Brown argued that as the world becomes more reliant on AI, there needs to be a more critical lens applied to AI’s output.

“Already it is so good its mistakes don’t look like mistakes,” Brown wrote.

Speaking with CNBC’s Scott Wapner at the CNBC Technology Executive Council Summit in New York City on Wednesday, Brown said the issue remains that “when you read an answer generated by AI, it’s presented with such confidence and clarity that it is hard to question it and identify where the mistakes may be.”

“I think that’s what’s particularly dangerous,” she said.

Brown, the former head of global media partnerships at Meta, said this issue is increasingly worrying as people turn to AI for political or election information, and that speaks to how the information is not only presented but where it is sourced.

“There’s a real critical piece to this that has been somewhat frustrating for me: the labs are not engaging as much as I think they should be with real subject matter expertise,” she said. “Human expertise in domains is essential to getting this right.”

— Ian Thomas

Yesterday, CNBC’s Workforce Executive Council held its annual Summit, and the discussion of how human resources professionals help workers adapt to this new AI age was at the top of the agenda.

Walmart, the biggest private employer in the world, asked its 2.1 million associates in June that exact question for the first time, trying to get a sense of how one of the most diverse workforces is experiencing AI.

What it found, based on more than 1.7 million survey responses, is that while workers have different levels of familiarity and comfort with AI, training and experience with the technology matters.

Seventy-seven percent of Walmart’s office-based associates said are excited about AI’s potential to improve their work, Walmart Chief People Officer for Associate Experience and Digital Maren Waggoner told CNBC’s Leslie Picker at the WEC Summit.

And as for Walmart’s U.S. frontline associates, 84% said they are confident using digital tools, a reflection of the AI-powered tools that many of them are now using in their roles, she said.

“We’ve given them certificates, we’ve given them training programs and tools, and so they’re using it in their day-to-day,” Waggoner said.

Jill Bruning, chief technology officer of Amentum and a member of the CNBC Technology Executive Council, said at the WEC Summit that strategy should be evolved to be humans in the lead.

“There’s an AI curve, and we see it. It’s going up and it’s going fast and has a lot of attributes to it; it’s quicker than anything we’ve seen before,” Bruning told CNBC’s Susan Caminiti. “So when you think about people on that curve … that gap is getting bigger every day.”

Bruning said she doesn’t know if leadership is adapting fast enough to the technology, and that is creating additional challenges with upskilling as well as what tasks are being delegated to AI.

“So your delegation skills are different, and then how do we tell the agents what to do? How do we define that role? She said. “That’s human over the loop, not in the loop. We’re still in charge.”

For more from the CNBC WEC Summit, you can see the full live blog here.

— Ian Thomas

Here are some of the top tech-focused headlines from CNBC this morning:

• Google alters its cloud playbook, enlisting partners to sell more AI chips. Google started working on in-house silicon in 2013, but didn’t begin selling its tensor processing units (TPUs) to outside customers until the second quarter of this year. Now the company is tapping Oracle’s cloud as another avenue for selling TPUs as it tries to bolster competition with Nvidia in the AI chip market.
• Anthropic’s cash pile towers over nearly every U.S. company. Anthropic had $112.4 billion in cash and cash equivalents and $19.3 billion in short-term investments as of June 30. That exceeded every non-bank U.S. company in CNBC and S&P Capital IQ data except Berkshire Hathaway and Alphabet.
• Amazon’s anti-tokenmaxxing memo says engineers should be pickier about using AI. Amazon discouraged teams from relying solely on token usage or code generation as measurements of AI adoption, calling them “deeply flawed” metrics in an internal memo. The memo revises how the company defines the role of software development engineers and managers in the age of AI.

— Ian Thomas

This year’s TEC Summit is focusing on what is coming next in AI, whether that’s how companies are adapting their strategies based on the advancement in the technology to how they’re controlling the costs related to that build out.

Discussions will also center on AI regulation, agents, how workers are using the technology and where this acceleration of AI is taking society.

Speakers include:

• Campbell Brown, Forum AI Founder & CEO: Brown will be discussing AI regulation, independent evaluation, what that looks like and how companies can use AI that can be trusted.
• Nigel Vaz, Publicis Sapient CEO: Vaz is at the center of how companies are rethinking their business models amid the AI age, and why that’s harder than learning how to use the technology itself.
• Calix CEO Michael Weening and CPO Shane Eleniak: Members of the team at Calix will pull back the curtain on how strategic AI decisions are made and implemented across the organization.
• Keia Cole, Brooklyn Sports & Entertainment Chief Digital Officer: Technology is also transforming the sports industry, and Cole will discuss how AI is being used at the Barclays Center and within the Brooklyn Nets and New York Liberty teams to make sports fans more connected and in touch.
• Jason Gowans, Levi Strauss Chief Digital & Technology Officer: Organizations are aiming to empower workers and customers with AI tools. Gowans will be sharing his approach to embedding AI into the everyday shopping experience.
• Jeetu Patel, Cisco President & Chief Product Officer: Rogue AI agents show no signs of slowing down, but Patel said companies need to think about them like they are teenagers. He’ll discuss ways companies can safely harness the power of agents and what it means to parent them.  

— Ian Thomas