Under this plan, the OpenAI nonprofit will own a minority stake in the for-profit company, Reuters reported Wednesday (Sept. 25), citing unnamed sources.

The plan has not been finalized and the timeline for its implementation is uncertain, according to the report.

Asked about the report by Reuters, an OpenAI spokesperson said: “We remain focused on building AI that benefits everyone, and we’re working with our board to ensure that we’re best positioned to succeed in our mission. The nonprofit is core to our mission and will continue to exist.”

The planned restructuring will make the company more attractive to investors, as it would operate more like a typical startup, the report said. OpenAI is also working to remove a cap on returns for investors that it currently has, according to the report.

In addition, the plan would give CEO Sam Altman equity in the for-profit company, per the report.

OpenAI was founded in 2015 as a nonprofit AI research organization and added a for-profit entity called OpenAI LP in 2019 as a subsidiary of the nonprofit, according to the report.

Two of its rivals, Anthropic and Elon Musk’s xAI, are registered as benefit corporations, per the report.

It has been reported in recent weeks that OpenAI is seeking $6.5 billion in funding and a valuation of $150 billion in the funding round. Earlier reports said that the funding round is being led by venture capital firm Thrive Capital; that Microsoft, which has already invested $13 billion in OpenAI since 2019, is expected to participate; and that Apple and Nvidia are in talks to invest in the company as well.

On Sept. 15, it was reported that OpenAI’s $150 billion valuation will depend on whether it can change its corporate structure and remove the profit cap for investors.

The report said that the conditions on the $6.5 billion in funding show the extent of OpenAI’s evolution from a research-based nonprofit and signify the changes it’s willing to make to woo investors to fund its costly efforts in the field of artificial general intelligence (AGI).

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“I’m stepping away because I want to create the time and space to do my own exploration,” Murati said in a Wednesday post on X. “For now, my primary focus is doing everything in my power to ensure a smooth transition, maintaining the momentum we’ve built.”

Murati served as interim CEO of OpenAI for a time in November 2023 when OpenAI co-founder and CEO Sam Altman was briefly ousted from the company by its board.

When announcing that move, the company said: “[Murati] brings a unique skill set, understanding of the company’s values, operations and business, and already leads the company’s research, product and safety functions.”

Three other executives have left the artificial intelligence (AI) firm in recent months.

John Schulman, one of OpenAI’s co-founders, said in August that he was departing the company to join one of its competitors, Anthropic.

“This choice stems from my desire to deepen my focus on AI alignment, and to start a new chapter of my career where I can return to hands-on technical work,” Schulman said at the time. “I’ve decided to pursue this goal at Anthropic, where I believe I can gain new perspectives and do research alongside people deeply engaged with the topics I’m most interested in.”

In May, Ilya Sutskever, who was OpenAI’s lead scientist and co-founder and who took part in the unsuccessful effort to remove Altman in 2023, announced his resignation from the firm.

“After almost a decade, I have made the decision to leave OpenAI,” Sutskever said at the time. “The company’s trajectory has been nothing short of miraculous, and I’m confident that OpenAI will build AGI [artificial general intelligence] that is both safe and beneficial under the leadership of [Altman, President Greg Brockman and Murati].”

Jan Leike, who co-led OpenAI’s superalignment team, which focused on “scientific and technical breakthroughs to steer and control AI systems much smarter than us,” per the company, also left OpenAI in May and joined Anthropic.

Murati’s announcement comes at a time when OpenAI is reportedly aiming to raise $6.5 billion at a $150 billion valuation.

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The tech giant reported that over 400 million people use Meta AI monthly, with 185 million engaging weekly across its products. Meta claims its AI assistant will become the most used globally by the end of the year.

“AI-generated images and captions can supercharge social media marketing. Brands can make content that feels custom-made for each user, at a large scale,” Mike Vannelli, an industry expert, told PYMNTS. He added, “AI can analyze what users like and help businesses make targeted campaigns. This leads to more engagement and better returns on investment.”

Meta announced Llama 3.2, a big advancement in its open-source AI model series, alongside its consumer-facing updates. This new release includes small and medium-sized vision language models (11B and 90B parameters) and lightweight, text-only models (1B and 3B parameters) designed for edge and mobile devices.

The vision models can analyze images, understand charts and graphs, and perform visual grounding tasks. The lightweight models, optimized for on-device use, support multilingual text generation and tool-calling abilities, enabling developers to build personalized applications supposedly prioritizing user privacy.

Features Could Drive Engagement

New features include voice interaction capabilities. Users can now talk to Meta AI on Messenger, Facebook, WhatsApp and Instagram DM and get spoken responses. Meta is rolling out various voice options, including AI voices of celebrities like Awkwafina, Dame Judi Dench, John Cena, Keegan Michael Key, and Kristen Bell.

Owais Rawda, senior account manager at Z2C Limited, told PYMNTS, “Voice-interactive AI creates a more personal customer experience. It gives quick answers, making shopping easier.”

Users can also share photos with Meta AI for analysis and editing. The AI can identify objects in images, answer questions, and edit pictures on command. For example, users can ask Meta AI to identify a flower in a hiking photo or get cooking instructions for a dish they’ve photographed.

Meta AI’s new editing capabilities allow users to request photo changes, from altering outfits to replacing backgrounds. The company is also testing an AI translation tool for Reels that automatically translates audio and synchronizes lips in videos, starting with English and Spanish.

Meta is expanding its business AI tools to companies using click-to-message ads in English on WhatsApp and Messenger. These AI agents can chat with customers, offer help, and assist with purchases.

The company said ad campaigns using AI features got 11% more clicks and 7.6% more conversions than regular campaigns. Over a million advertisers are using these tools, making 15 million ads in the past month.

Vannelli highlighted changes in customer service: “Meta AI makes shopping smoother. Customers don’t have to switch between pages or wait for a human to respond.”

Meta is also enhancing its Imagine feature, allowing users to create AI-generated images of themselves as superheroes or in other scenarios directly in their feeds, Stories and Facebook profile pictures. These images can be easily shared and replicated by friends.

As Meta refines its AI offerings, its approach to data use, transparency, and user control will be crucial in shaping the adoption and success of these new features. These AI advances represent a big step in Meta’s strategy to integrate AI into its core products, potentially reshaping how businesses and consumers interact in the digital marketplace.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

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The move marks the first time a major tech company has directly invested in nuclear power generation to fuel its artificial intelligence (AI) operations. As the AI sector booms, it’s creating unprecedented demand for stable, high-capacity power sources. 

“Microsoft’s decision to restart operations at the Three Mile Island nuclear facility highlights the massive energy needs that come with scaling AI advancements,” Labhesh Patel, CEO, and co-founder of Autonomys, a company building decentralized AI infrastructure, told PYMNTS. “As AI systems become more integral to the economy and technological progress, their energy demands are rising.”

The 835-megawatt reactor at Three Mile Island operates independently from Unit 2, which melted down in the 1970s.

A New Energy Market?

The partnership between Microsoft and Three Mile Island could herald a wave of deals between tech giants and energy companies. Benjamin Lee, an engineering professor at the University of Pennsylvania, suggested that tech companies are turning to nuclear power as renewable energy struggles to meet growing data center demands.

He told PYMNTS, “There is an increasing realization … that renewable energy installations cannot keep pace with data center construction, raising questions about whether net zero is possible.”

Lee explained that intermittency issues with wind and solar energy are driving interest in nuclear power: “Because large batteries and rescheduling computation is daunting, data center operators are increasingly considering carbon-free nuclear energy.”

However, he cautioned that nuclear power faces economic challenges: “Companies in the United States rarely build new nuclear power plants and, when they do, these projects are significantly delayed and over budget.”

Looking ahead, Lee is “pessimistic about investments in wind and solar alone,” suggesting, “Data centers would benefit enormously from technological advances in energy storage and batteries as well as efficient, modular, and safe nuclear reactors.”

This trend extends beyond just one company. “As fields like healthcare and logistics grow more dependent on AI technologies, their energy usage spikes,” Patel said. “Meanwhile, the urgency to cut carbon emissions and combat climate change intensifies.”

With global AI spending projected to reach $300 billion by 2026, according to IDC, the race for energy resources among tech companies could become as fierce as the competition for AI talent and market share.

Growing Demand

Recent studies have shed light on the energy consumption of large language models (LLMs), which are at the forefront of AI advancements. For example, training GPT-3, a predecessor to the current GPT-4, was estimated to consume around 1,287 MWh, equivalent to the annual energy usage of about 120 U.S. households. More recent models like GPT-4 are believed to consume even more, though exact figures aren’t publicly available.

However, AI is also being leveraged to optimize energy consumption. DeepMind’s AI system, when applied to Google’s data centers, reduced the energy used for cooling by up to 40%. Similarly, Microsoft has been using AI to improve the energy efficiency of its data centers, achieving power usage effectiveness (PUE) ratings as low as 1.12, where 1.0 is perfect efficiency.

Microsoft’s plan to reopen Three Mile Island for AI energy needs highlights broader challenges in powering advanced technologies, Donatas Karčiauskas, CEO of Exergio, a company that creates AI solutions for energy performance, told PYMNTS. 

“Data centers are still one of the biggest contributors to global carbon emissions, at a scale similar to the aviation industry,” he said. He said nuclear power alone cannot meet AI’s growing energy demands. “We will need to find other energy sources, from geothermal to hydrogen, and other ways to reduce energy waste.”

Karčiauskas noted the urgency of the situation, explaining, “It’s not a surprise Microsoft is looking for ways to reopen certain power plants, as new ones take more than 10 years to build.”

However, he sees potential in AI to address these challenges: “The latest machine learning algorithms are also used to reduce energy waste up to 20%,” suggesting a “huge potential gap for AI-based energy saving solutions in data centers.”

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

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The law enforcement sweep, dubbed “Operation AI Comply,” targets companies that use “AI hype” or sell AI technology that can be used in deceptive and unfair ways, the regulator said in a Wednesday (Sept. 25) press release.

“Using AI tools to trick, mislead or defraud people is illegal,” FTC Chair Lina M. Khan said in the release. “The FTC’s enforcement actions make clear that there is no AI exemption from the laws on the books.”

One action targeted DoNotPay, a company that the FTC alleged said it offered “the world’s first robot lawyer” but did not test its capabilities or hire or retain any attorneys. DoNotPay agreed to a proposed settlement that would require it to pay $193,000, warn consumers who subscribed to the service about its limitations, and not make unsubstantiated claims about its ability to substitute for any professional service, according to the release.

Reached by PYMNTS, a DoNotPay spokeswoman provided an emailed statement saying: “DoNotPay is pleased to have worked constructively with the FTC to settle this case and fully resolve these issues, without admitting liability. The complaint relates to the usage of a few hundred customers some years ago (out of millions of people), with services that have long been discontinued.”

The FTC also filed a lawsuit against an online business opportunity scheme that has operated under many names, including Accelerated eCom Ventures, alleging that it falsely claimed its AI-powered tools would help consumers earn thousands of dollars a month by opening online storefronts. A federal court has put this scheme under the control of a receiver, and the FTC’s case against the scheme is ongoing.

Accelerated eCom Ventures did not immediately reply to PYMNTS’ request for comment.

A third action targeted Ecommerce Empire Builders, which the FTC alleges falsely claimed to help consumers build an AI-powered eCommerce business but failed to deliver the sort of income it promised in ads. A federal court has put this scheme under the control of a receiver, and the FTC’s case against the scheme is ongoing.

Ecommerce Empire Builders could not be reached for comment, as its website was offline.

The regulator also targeted Rytr, a firm that it alleges has marketed and sold an AI “writing assistant” that could write testimonials and reviews, among other things, but generated false and deceptive content for consumer reviews. A proposed order settling this complaint would bar the company from selling services dedicated to generating reviews.

Rytr did not immediately reply to PYMNTS’ request for comment.

The fifth law enforcement action announced Wednesday by the FTC focused on a business opportunity scheme called The FBA Machine that the regulator alleges falsely promised consumers the ability to make guaranteed income through AI-powered online storefronts. A federal court has put this scheme under the control of a receiver, and the FTC’s case against the scheme is ongoing.

The FBA Machine could not be reached for comment, as an email sent to the address on its website was returned as undeliverable.

Some experts say AI hype has reached a fever pitch, obscuring the reality of the technology’s current capabilities, PYMNTS reported in April. One of the main issues with this hype is that it creates unrealistic expectations among the public and investors.

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The company will add these capabilities across its platforms and products, including Intuit TurboTax, Credit Karma, QuickBooks and Mailchimp, Intuit said in a Wednesday (Sept. 25) press release.

“Agentic AI represents a transformative leap in technology, with the potential to unlock unprecedented levels of efficiency for our customers, human experts and developers,” Alex Balazs, chief technology officer at Intuit, said in the release.

The new agentic AI systems will work on behalf of consumers and businesses while providing personalized insights and recommendations and offering access to human tax and bookkeeping experts whenever needed, according to the release.

The systems will complete tasks autonomously via specialized AI agents, with human direction and oversights, thereby eliminating the need for consumers and businesses to perform routine tasks, the release said.

Examples of the agentic AI use cases include automating accounts receivable (AR) and accounts payable (AP) tasks, streamlining the onboarding of small business customers who are new to Intuit’s products, and providing personalized answers and insights about Intuit’s products or the small business customer’s operations, per the release.

“Given Intuit’s decade-long investments in data and AI — and our GenOS GenRuntime agent framework — we’re well on our way to delivering on the promise of seamless, connected, done-for-you customer experiences,” Balazs said in the release.

Agentic AI is positioned to take the capabilities of an automated software program to the next level — a request-action architecture — by conducting business from start to finish without the need for human intervention, PYMNTS reported in February.

When applied to payments, for example, agentic AI software can automate routine and repetitive tasks like invoicing processing, data entry and transactional reconciliation, while reducing the likelihood of errors associated with manual processes.

Intuit has already rolled out some other AI-driven offerings, including a generative AI-powered financial assistant that delivers personalized financial insights. This AI assistant is available to millions of consumers and about 1 million small and mid-market businesses.

“This is enabling us to disrupt the categories in which we operate,” Intuit CEO Sasan Goodarzi said in August during the company’s quarterly earnings call.

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According to The Wall Street Journal (WSJ), Shazeer, who co-authored research that helped popularize artificial intelligence (AI), left Google in frustration after the company refused to release a chatbot he had developed.

He started his own company, Character.AI, which became known for its AI chatbots that could replicate a range of personalities and fictional characters. Earlier this year, Google announced that Shazeer would be coming back to the company as part of a major licensing deal.

The price tag of that deal was around $2.7 billion, the WSJ said, citing sources with knowledge of the arrangement. They say that deal included another stipulation: Shazeer agreed to return to Google. It’s a situation, the report adds, that sits at the heart of a debate about whether tech giants are spending too much in their race to build cutting-edge AI.

“Noam is clearly a great person in that space,” said Christopher Manning, director of the Stanford Artificial Intelligence Laboratory. “Is he 20 times as good as other people?”

The report also notes that Shazeer’s return to Google came after he publicly stated that the company had become too timid about developing AI. Now, he’s one of the leaders of Google’s Gemini AI project.

One of the sources said Shazeer made hundreds of millions from his stake in Character as part of the deal, a sum the WSJ said is unusually high for a founder who didn’t sell their company or take it public.

PYMNTS has contacted Google for comment but has not yet gotten a reply.

Meanwhile, Google announced this week that its generative AI solutions are now being used by more than 2 million developers.

“We’re inspired by what customers are building and excited how quickly they’ve been able to move ideas from experimentation into production with our Vertex AI platform,” Thomas Kurian, CEO of Google Cloud, wrote in a blog post.

“We’re also seeing major boosts in productivity through Gemini for Google Workspace, with customers saving an average of 105 minutes per user, per week, according to our recent study of enterprise customers.”

The company also shared some examples of use cases of Google’s generative AI solutions and the benefits they are delivering. For instance, the Indonesian FinTech GoTo Group developed an AI-based voice assistant that helps users of its GoPay app find and use features just saying what they wish to do.

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“While you’ve been patiently waiting, we’ve added Custom Instructions, Memory, five new voices, and improved accents,” the company said in a Tuesday (Sept. 24) post on X.

The feature is not yet available in the European Union, the United Kingdom, Switzerland, Iceland, Norway and Liechtenstein, OpenAI added in another post.

Users can now choose from nine “lifelike output voices” for ChatGPT, with different tones and characters like “easygoing and versatile” and “animated and earnest,” according to the company’s Voice mode FAQ.

It was reported July 30 that OpenAI was rolling out the alpha version of Advanced Voice Mode to a select group of ChatGPT Plus subscribers at that time and planned to begin a broader rollout to all premium users in the fall.

To mitigate potential misuse of the feature, the company said at the time that it limited Advanced Voice Mode to preset voices created in collaboration with paid voice actors, so that it can’t be used to impersonate specific individuals or public figures; implemented guardrails to block requests for violent or copyrighted content; and included filters to block requests for generating music or copyrighted audio, a move likely influenced by music industry legal actions against artificial intelligence (AI) companies.

OpenAI had planned to roll the voice feature out in alpha in late June but said June 25 that it needed another month to do so.

“For example, we’re improving the model’s ability to detect and refuse certain content,” the company said at the time. “We’re also working on improving the user experience and preparing our infrastructure to scale to millions while maintaining real-time responses.”

Many U.S. consumers are willing to pay for smart, reliable voice assistants, according to the PYMNTS Intelligence report, “How Consumers Want to Live in the Voice Economy.”

Twenty-two percent of Gen Z consumers are “highly willing” to pay more than $10 per month for a voice assistant that is as smart and reliable as a real person, per the report.

The report also found that 54% of consumers would prefer using voice technology because it is faster than typing or using a touchscreen.

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Nicole Argentieri, principal deputy assistant attorney general for the criminal division of the Department of Justice (DOJ), said this on Monday (Sept. 23) while outlining changes to the DOJ’s Evaluation of Corporate Compliance Programs (ECCP), the Wall Street Journal (WSJ) reported Tuesday (Sept. 24).

This DOJ guidance is important to lawyers and compliance officers because compliance programs that adhere to its guidelines are eligible for more lenient treatment when a compliance breakdown occurs, according to the report.

In prepared remarks for a speech delivered Monday, Argentieri said that under the updated ECCP, prosecutors will consider AI and other technology a company uses to conduct business, whether the company has conducted a risk assessment of the use of that technology, and whether it has taken steps to mitigate that risk.

“For example, prosecutors will consider whether the company is vulnerable to criminal schemes enabled by new technology, such as false approvals and documentation generated by AI,” Argentieri said. “If so, we will consider whether compliance controls and tools are in place to identify and mitigate those risks, such as tools to confirm the accuracy or reliability of data used in the business. We also want to know whether the company is monitoring and testing its technology to evaluate if it is functioning as intended and consistent with the company’s code of conduct.”

In the second of three major changes to the ECCP outlined in her speech, Argentieri said prosecutors will consider companies’ commitment to whistleblower protection and treatment of employees who report misconduct.

The third update outlined in the speech covers a compliance program’s access to data and technology, and whether the company is putting the same resources into compliance as it puts into other parts of the business.

The ECCP was first issued in 2017 to lay out a series of factors for prosecutors to consider when assessing the effectiveness of corporate compliance programs as part of making charging decisions and negotiating resolutions.

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The professional networking giant’s recent User Agreement and Privacy Policy update, which will take effect on Nov. 20, has caused concern in the business community. LinkedIn admitted it has been using users’ data to train its AI without consent, and while users can opt out of future training, there’s no way to undo past data use. This revelation has warned experts of growing tension between AI innovation and user privacy.

“Data is the new oil. When the data being sifted through contains personal information, that’s where privacy questions come into play,” David McInerney, commercial manager for data privacy at Cassie, told PYMNTS.

LinkedIn’s move could force businesses to reconsider their digital footprint, balancing the need for professional connectivity against the risk of compromising sensitive information. McInerney emphasized the stakes: “A whopping 93% [of consumers] are concerned about the security of their personal information online.”

Opting Out

While LinkedIn offers an opt-out setting for generative AI training, the company noted that it will not use data from users in the European Economic Area, Switzerland and the United Kingdom for AI training. This geographic distinction highlights the disparity between European data protection standards and the less regulated U.S. landscape.

As LinkedIn’s parent company, Microsoft, navigates this controversy, McInerney pointed out a fundamental challenge: “Businesses like Microsoft can say they trained their AI, and it made an automated decision. But a fundamental piece of GDPR is your right to challenge an automated decision.” This principle, he noted, becomes problematic when “nobody at a company knows how the algorithms work because they’ve become so complicated.”

The debate underscores a broader trend in the tech industry, where companies are racing to leverage AI capabilities while grappling with ethical considerations and user trust.

“Compliance is good — ethics are better,” McInerney said. “By prioritizing your customers, it’s proven to create stronger relationships, increased brand loyalty and higher sales.”

Right to Privacy?

Concerns over privacy in AI training data have grown as AI systems become more powerful and widespread. Central to this issue is how AI models, especially with large language models like OpenAI’s GPT-4 or Google’s Gemini, are trained on vast amounts of publicly available information scraped from the internet, including websites, social media and databases, often without explicit consent.

In a recent lawsuit, authors like George R.R. Martin and Sarah Silverman filed complaints against OpenAI and Meta, claiming that their copyrighted works were used to train AI models without permission. This raised alarms about how AI companies collect and use personal and proprietary data. The central argument is that AI companies have scraped this data en masse, sidestepping intellectual property rights and individual privacy.

Controversy erupted when Clearview AI, a facial recognition startup, was discovered to have been scraping billions of images from social media platforms to train its AI system without users’ knowledge. Privacy advocates expressed concern that such practices could lead to violations of personal privacy, particularly when sensitive information is used to profile or track individuals.

The European Union’s AI Act specifically addresses these concerns by regulating high-risk AI applications and requiring transparency in data usage. This regulatory framework may be a harbinger of more stringent laws as lawmakers recognize the need to protect personal data from being used without consent in AI.

As the Nov. 20 deadline approaches, businesses and individual users alike are left to ponder the implications of their professional data potentially fueling AI systems and whether the benefits of enhanced services outweigh the privacy concerns in an increasingly AI-driven world.

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