OpenAI last week unveiled two new free-to-download tools that are supposed to make it easier for businesses to construct guardrails around the prompts users feed AI models and the outputs those systems generate.
The new guardrails are designed so a company can, for instance, more easily set up contorls to prevent a customer service chatbot responding with a rude tone or revealing internal policies about how it should make decisions around offering refunds, for example.
But while these tools are designed to make AI models safer for business customers, some security experts caution that the way OpenAI has released them could create new vulnerabilities and give companies a false sense of security. And, while OpenAI says it has released these security tools for the good of everyone, some question whether OpenAI’s motives aren’t driven in part by a desire to blunt one advantage that its AI rival Anthropic, which has been gaining traction among business users in part because of a perception that its Claude models have more robust guardrails than other competitors.
The OpenAI security tools—which are called gpt-oss-safeguard-120b and gpt-oss-safeguard-20b—are themselves a type of AI model known as a classifier, which is designed to assess whether the prompt a user submits to a larger, more general-purpose AI model as well as that larger AI model produces meet a set of rules. Companies that purchase and deploy AI models could, in the past, train these classifiers themselves, but the process was time-consuming and potentially expensive, since the developers would have to collect examples of content that violates the policy in order to train the classifier. And then, if the company wanted to adjust the policies used for the guardrails, they would have to collect new examples of violations and retrain the classifier.
OpenAI is hoping the new tools can make that process faster and more flexible. Rather than being trained to follow one fixed rulebook, these new security classifiers can simply read a written policy and apply it to new content.
OpenAI says this method, which it calls “reasoning-based classification,” allows companies to adjust their safety policies as easily as editing the text in a document instead of rebuilding an entire classification model. The company is positioning the release as a tool for enterprises that want more control over how their AI systems handle sensitive information, such as medical records or personnel records.
However, while the tools are supposed to be safer for enterprise customers, some safety experts say that they instead may give users a false sense of security. That’s because OpenAI has open-sourced the AI classifiers. That means they have made all the code for the classifiers available for free, including the weights, or the internal settings of the AI models.
Classifiers act like extra security gates for an AI system, designed to stop unsafe or malicious prompts before they reach the main model. But by open-sourcing them, OpenAI risks sharing the blueprints to those gates. That transparency could help researchers strengthen safety mechanisms, but it might also make it easier for bad actors to find the weak spots and risks, creating a kind of false comfort.
“Making these models open source can help attackers as well as defenders,” David Krueger, an AI safety professor at Mila, told Fortune. “It will make it easier to develop approaches to bypassing the classifiers and other similar safeguards.”
For instance, when attackers have access to the classifier’s weights, they can more easily develop what are known as “prompt injection” attacks, where they develop prompts that trick the classifier into disregarding the policy it is supposed to be enforcing. Security researchers have found that in some cases even a string of characters that look nonsensical to a person can, for reasons researchers don’t entirely understand, convince an AI model to disregard its guardrails and do something it is not supposed to, such as offer advice for making a bomb or spew racist abuse.
Open-source can be a double-edged sword when it comes to safety. It allows researchers and developers to test, improve, and adapt AI safeguards more quickly, increasing transparency and trust. For instance, there may be ways in which security researchers could adjust the model’s weights to make it more robust to prompt injection without degrading the model’s performance.
But it can also make it easier for attackers to study and bypass those very protections—for instance, by using other machine learning software to run through hundreds of thousands of possible prompts until it finds ones that will cause the model to jump its guardrails. What’s more, security researchers have found that these kinds of automatically-generated prompt injection attacks developed on open source AI models will also sometimes work against proprietary AI models, where the attackers don’t have access to the underlying code and model weights. Researchers have speculated this is because there may be something inherent in the way all large language models encode language that similar prompt injections will have success against any AI model.
In this way, open sourcing the classifiers may not just give users a false sense of security that their own system is well-guarded, it may actually make every AI model less secure. But experts said that this risk was probably worth taking because open-sourcing the classifiers should also make it easier for all of the world’s security experts to find ways to make the classifiers more resistant to these kinds of attacks.
“In the long term, it’s beneficial to kind of share the way your defenses work— it may result in some kind of short-term pain. But in the long term, it results in robust defenses that are actually pretty hard to circumvent,” Vasilios Mavroudis, principal research scientist at the Alan Turing Institute, said.
Mavroudis said that while open-sourcing the classifiers could, in theory, make it easier for someone to try to bypass the safety systems on OpenAI’s main models, the company likely believes this risk is low. He said that OpenAI has other safeguards in place, including having teams of human security experts continually trying to test their models’ guardrails in order to find vulnerabilities and hopefully improve them.
“Open-sourcing a classifier model gives those who want to bypass classifiers an opportunity to learn about how to do that. But determined jailbreakers are likely to be successful anyway,” Robert Trager, co-director of the Oxford Martin AI Governance Initiative, said.
“We recently came across a method that bypassed all safeguards of the major developers around 95% of the time — and we weren’t looking for such a method. Given that determined jailbreakers will be successful anyway, it’s useful to open-source systems that developers can use for the less determined folks,” he added.
The enterprise AI race
The release also has competitive implications, especially as OpenAI looks to challenge rival AI company Anthropic’s growing foothold among enterprise customers. Anthropic’s Claude family of AI models have become popular with enterprise customers partly because of their reputation for stronger safety controls compared to other AI models. Among the safety tools Anthropic uses are “constitutional classifiers” that work similarly to the ones OpenAI just open-sourced.
Anthropic has been carving out a market niche with enterprise customers, especially when it comes to coding. According to a July report from Menlo Ventures, Anthropic holds 32% of the enterprise large language model market share by usage compared to OpenAI’s 25%. In coding‑specific use cases, Anthropic reportedly holds 42%, while OpenAI has 21%. By offering enterprise-focused tools, OpenAI may be attempting to win over some of these business customers, while also positioning itself as a leader in AI safety.
Anthropic’s “constitutional classifiers,” consist of small language models that check a larger model’s outputs against a written set of values or policies. By open-sourcing a similar capability, OpenAI is effectively giving developers the same kind of customizable guardrails that helped make Anthropic’s models so appealing.
“From what I’ve seen from the community, it seems to be well received,” Mavroudis said. “They see the model as potentially a way to have auto-moderation. It also comes with some good connotation, as in, ‘we’re giving to the community.’ It’s probably also a useful tool for small enterprises where they wouldn’t be able to train such a model on their own.”
Some experts also worry that open-sourcing these safety classifiers could centralize what counts as “safe” AI.
“Safety is not a well-defined concept. Any implementation of safety standards will reflect the values and priorities of the organization that creates it, as well as the limits and deficiencies of its models,” John Thickstun, an assistant professor of computer science at Cornell University, told VentureBeat. “If industry as a whole adopts standards developed by OpenAI, we risk institutionalizing one particular perspective on safety and short-circuiting broader investigations into the safety needs for AI deployments across many sectors of society.”
Gen Z is sometimes criticized for its proclivity toward slang or its approach to the workforce. But this generation is facing challenges very different from those of their elders. The young adults are slowing down their pursuit of the American Dream of finding “the one,” owning a home, and having kids.
But it’s not because Gen Z doesn’t want to find love, according to a report by Match Group and Harris Poll shared exclusively with Fortune. In fact, their survey results from 2,500 randomly selected U.S. adults shows 80% of Gen Z say they believe they’ll find true love, making them the most optimistic generation about finding love. Yet, only 55% of Gen Z feel like they’re actually ready for partnership.
Therein lies the “readiness paradox,” a phenomenon that paralyzes Gen Z from taking that initial step toward a serious relationship, and subsequently toward marriage and having children. While more than half of Gen Z says they feel lonely despite having online connections, 48% of Gen Z women report feeling additional pressure to enter a relationship for “the right reason,” rather than solely to avoid loneliness. This cycle traps young people in loneliness, which is amplified by social media pressures, like the dread of “hard-launching” a relationship.
“It makes total sense to be stuck in that paralysis of, I want this, I want a relationship, but I don’t feel ready for it, and so I don’t do it,” Chine Mmegwa, head of strategy, corporate development, and business operations at Match Group, told Fortune. “What they’re afraid of is failing. What they’re afraid of is that the other person on the other side isn’t ready.”
Match Group defines this phenomenon as a “self-reinforcing cycle” in which Gen Zers set a high bar for readiness for a relationship, then feel anxious about being alone, then crave new relationships, believe they’re not ready for it and wait longer, experience more loneliness, and then the cycle repeats.
And some of this cycle stems from the fact that Gen Z prioritizes investing in personal growth, therapy, and defining success over other generations. Nearly 60% of Gen Z women say therapy is essential to relationship success, according to the Match Group report, and almost 50% say that setting and respecting healthy boundaries is a prime indication of being ready for a romantic relationship. And as a result, they may be more likely to delay dating.
This report serves as a launchpad for Match Group and other dating app companies to rethink how to best serve Gen Z consumers, some of which had ditched the apps when they did have features they could relate to. But now Tinder has introduced more casual modes for Gen Zers to meet each other, like through its double-date feature and college mode where the generation can meet more people with the same relationship goals in mind.
That’s a step in the right direction for a generation that is reverting back to a desire to meet in real life.
“This is the way Gen Z wants to connect,” Match Group CEO Spencer Rascoff previously said. “They want to vibe their way through meeting people.”
Reprioritizing milestones
Unlike how some other reports about Gen Z love life have portrayed the generation, they’re not rejecting romance. Instead, they’re reshuffling life’s timeline amid economic and social strains.
Match Group’s report shows nearly half of Gen Z say they’re not ready for relationships now, and 75% aren’t rushing into one. But, again, 80% say they believe they’ll find true love.
“They believe that when they work on themselves, their relationships become stronger,” according to the Match Group report. “And they are more likely to wait until they can put their best selves forward to give themselves the highest chance of relationship success.”
Although that may sound like worrisome news for a company trying to appeal to the latest generation, Mmegwa didn’t shy away from the challenge.
Gen Z is “still looking to our products to solve real big issues. And they are still looking to our products and to dating to solve the things that are most important to them” she said. “It’s just a question of when and how they will use our products that [is] very different from prior generations.”
This generation also has a very different view of how happy their own parents’ and grandparents’ relationships are: Only 37% described those relationships as happy, and 34% of Gen Z women also feel working through issues from past relationships indicates readiness, according to the report.
Social media’s vicious cycle
Being highly inundated by and invested in social media has also exacerbated the readiness paradox. While 46% of Gen Z “soft-launch” relationships versus 27% overall, 81% see it as an ironclad agreement, and dread backlash from a public failure.
It’s different from how other generations view making relationships public: “You can also hard launch and then delete the photos the next day, and it’s okay,” Mmegwa said.
But still, for Gen Z, relationship performance pressure creates a cycle: High readiness bars lead to loneliness, which ultimately leads to them pursuing lower-stakes or casual relationships that rarely escalate into something more serious.
Instagram exacerbates the stall. While 46% of Gen Z “soft-launch” relationships versus 27% overall, 81% who hard-launch see it as an ironclad commitment, dreading public failure. Mmegwa highlighted this generational shift: “You can also hard launch and then delete the photos the next day, and it’s okay.” This “performance pressure” creates a cycle: High readiness bars lead to loneliness (over 50% feel it despite online ties), prompting low-stakes connections that rarely escalate.
“For us, the focus is on how we bring people together and encourage them to return to in-person connections,” Hinge CEO Jackie Jantos previously toldFortune. Hinge is part of Match Group, along with Tinder, Match, and OkCupid.
How Match Group plans to address the readiness paradox
Match Group is planning to meet Gen Z where they are: They’ll keep introducing “low-pressure” tools, like Tinder’s Double Dating feature and College Mode.
“The idea here is really around helping our users have the power to control what they’re looking for in a given moment and be able to find that more easily,” Cleo Long, Tinder’s senior director of global product marketing, previously told Fortune.
Using the report as a roadmap for new product plans, future features could include features like readiness signals, Mmegwa said, and more curated matches will be important.
“It’s no longer a speed and volume game,” she said. “It’s [about] truly making our algorithms help you know yourself better, and then help you know the person on the other side of the connection better.”
Good morning. As audit committees confront a rapidly expanding risk landscape, their role in corporate governance is being reshaped. Boards have often turned to current and former CFOs as independent directors, particularly for audit committees, because of their ability to translate complex operational and financial realities into effective oversight.
For example, this month, J. Michael Hansen, former EVP and CFO of Cintas Corporation, was appointed to the audit committee at Paychex. In July, Britt Vitalone, EVP and CFO of McKesson Corporation, was appointed to the audit committee of Align Technology’s board of directors. And in November, Catherine Birkett, CFO of GoCardless, was named chair of the audit and risk committee at Twinkl.
I attended the launch event of the Institute of Internal Auditors’ (IIA) Global Audit Committee Center last week in Washington, D.C., which addressed the challenges and opportunities facing audit committees. The center is designed to be a resource to strengthen the alliance between audit committees of boards and internal audit in a fast-changing risk environment. It offers research, webinars, and events and will ultimately add formal training programs.
“The center has a very strong core belief—well-informed, engaged, and well-supported audit committees are essential to corporate governance,” said Anthony Pugliese, president and CEO of the IIA.
Pugliese emphasized that board audit committees need to turn to internal audit to truly understand what is happening inside an organization. The event drew members from across the U.S. and around the world, including Canada, Europe, Africa, Latin America, and the Middle East, with Abdullah Alshebeili, CEO of the Saudi Authority of Internal Auditors, in attendance.
CFOs, in particular, work with internal audit on risk assessment, internal controls, and audit readiness, and they share information on financial processes and control issues. Finance chiefs also communicate regularly with the board’s audit committee.
AI and analytics reshape how audit committees see risk
During a panel discussion at the event, Ann Cohen, CFO of the IIA, said audit committees are increasingly using AI and advanced technology to connect different types of risk—third-party, financial, operational, cyber, and regulatory. They are using analytics to surface anomalies and emerging risks earlier, support proactive oversight, and run “what if” analyses before risks materialize. “It allows us to be more responsive to risks and provide more robust assurance to stakeholders,” she said.
A major focus is “everyday AI,” said Sarah Francis of the EY Center for Board Effectiveness. “I think audit committees are really also looking at, ‘How do we start to touch, feel, smell, and get used to the products that are out there?’” Directors, many of whom are active executives, are also thinking about how to deploy these tools effectively. “There have to be clear governance frameworks for AI and analytics,” she said, noting that prompts—and the people who craft them—matter. She highlighted the need for experts who can help frame broader questions around ethics within responsible AI frameworks.
Audit committees can and should engage with technology as they work toward a fully defined plan, commented Luke Whorton, executive search and leadership consultant at Spencer Stuart in the firm’s Financial Officer Practice. “How do you create a foundation, but one that’s agile and responsive, because it’s going to continue to change rapidly?” he asked.
“Audit committees need to be curious,” Cohen said. “They need to challenge management on their inputs, on their assumptions and their judgment, and on what they’ve embedded into their AI outputs.”
The committees that challenge assumptions and lean into technology, alongside strong partnerships with internal audit, could be well-positioned to safeguard trust in an uncertain world.
Linda LaGorga will step down as CFO of Entegris, Inc. (NASDAQ: ENTG), an advanced materials science provider, effective Feb. 28. Effective March 1. Mike Sauer, Entegris’ VP, controller and chief accounting officer, will assume the role of interim CFO, in addition to maintaining the responsibilities of his current role. LaGorga will serve as a senior advisor to Entegris through May 15. Entegris has initiated a search process for a permanent CFO with an executive search firm. Sauer has 37 years of experience in finance and accounting roles at Entegris.
Hugo Doetsch was appointed CFO of AuditBoard, a governance, risk, and compliance platform. Doetsch brings over two decades of financial leadership and strategic operating experience to AuditBoard. Most recently, he served as CFO at symplr, an enterprise health care operations software provider. Before that, he was CFO at NetDocuments, a cloud-based content management platform. Doetsch also held senior leadership roles at Ping Identity, where he assisted the company in a 2019 initial public offering.
Big Deal
The 2026 Fortune World’s Most Admired Companies list was released this morning. The annual ranking of corporate reputation is based on a poll of some 3,000 executives, directors, and analysts.
Apple has been No. 1 for 19 consecutive years. Amazon and Microsoft have filled out the top three for seven years in a row. Berkshire Hathaway (No. 6) and Alphabet (No. 8) have each been in the top 10 for well over a decade. Berkshire, the conglomerate nurtured by Warren Buffett, holds the distinction of having been on the All-Star list every single year since it launched in 1998; it shares that honor with Microsoft, Coca-Cola, Toyota Motor, and Johnson & Johnson.
Going deeper
“Who Gets Replaced by AI and Why?” is a report in Wharton’s business journal. New research from Wharton’s Pinar Yildirim explores how AI can impact employee motivation when it is implemented in the wrong part of a team’s workflow. The research addresses topics such as how managers should deploy AI capacity in teams and which positions are most vulnerable to being displaced by AI.
Overheard
“Working closely with David Ellison and this exceptional management team made the decision to resign from the board and jump in fully as CFO an easy one.”
—Dennis K. Cinelli wrote in a LinkedIn post on Tuesday regarding his appointment, effective Jan. 15, as CFO of Paramount, and his resignation from the company’s board. Most recently, Cinelli served as CFO of Scale AI, and he previously held senior finance and operational roles at Uber.
I love watching “Next Man Up” basketball, where the spotlight rotates unpredictably. One night it’s the bench guard dropping 30, the next it’s the role player posting a triple-double.
CapitalG’s Jill Chase—who captained her college basketball team at Williams College—says this logic actually applies to Alphabet’s growth firm. When I ask her what basketball team is most like CapitalG, she lists the WNBA’s Golden State Valkyries.
“Everybody has a different skill set, and everybody is willing to drop anything to help each other win,” said Chase. “It’s a different person every night who wins the game. And I think that’s really consistent with the way CapitalG is building its culture.”
For the first time since the firm was started in 2013, it’s promoting two general partners, Chase and Alex Nichols, Fortune has exclusively learned. Chase, who joined CapitalG in 2020 specifically with a thesis around AI, has backed Abridge, Baseten, Canva, LangChain, Physical Intelligence, and Rippling.
Nichols, meanwhile, joined CapitalG in 2018 as an associate and was promoted to partner just two years ago. He previously worked with managing partner Laela Sturdy on the firm’s investments in Duolingo, Stripe, and Whatnot, and recently led CapitalG’s investment in Zach Dell’s energy startup BasePower. At a moment where there’s mounting angst around data centers and what it will take to power them, Nichols has a surprising take on how AI will affect energy—that both batteries and solar are getting cheaper and better at something like Moore’s Law speed. Those twin cost curves, over time, should actually drive energy prices down.
“I’m actually very optimistic about the future of energy prices,” he said. “You look at the history of energy consumption versus GDP. And cheap energy means more production, more income, and means a higher standard of living.”
At a moment when venture is perhaps more competitive than ever—and there are certainly some solo GPs out there making their mark—there’s an argument that as lines blur between disciplines in an AI-ified world, venture is by necessity a team sport.
Sturdy—who’s been CapitalG’s managing partner since 2023 (and also captained her college basketball team)—and Chase both have clearly taken some learnings from their time on the court. Chase sees venture overall as becoming more team-oriented: “Historically, it used to be like ‘you made general partner, go out and win your deal.’ To me, that’s not the right way to be successful in venture ever.”
Sturdy adds that in basketball, like venture, “We have to look at the scoreboard every once in a while, and you have to get back up when you get crushed… And, of course, coming together is better than playing alone.”
Term Sheet Podcast…This week, I spoke with Exelon CEO Calvin Butler. As resource-hungry data centers continue to sprout across the country, many are questioning whether the nation’s utility network can keep pace with such large-scale demand. Butler says it can. Listen and watch here.
Joey Abrams curated the deals section of today’s newsletter.Subscribe here.
VENTURE CAPITAL
– humans&, a San Francisco-based AI lab, raised $480 million in seed funding. SVAngel and GeorgesHarik led the round and were joined by NVIDIA and others.
– Emergent, a San Francisco-based platform designed for AI software creation, raised $70 million in Series B funding. Khosla Ventures and SoftBank led the round and were joined by Prosus, Lightspeed, Together, and Y Combinator.
– Exciva, a Heidelberg, Germany-based developer of therapeutics designed for neuropsychiatric conditions, raised €51 million ($59 million) in Series B funding. Gimv and EQTLifeSciences led the round and were joined by FountainHealthcarePartners, LifeArcVentures, and others.
– Pomelo, a Buenos Aires, Argentina-based payments infrastructure company, raised $55 million in Series C funding. Kaszek and InsightPartners led the round and were joined by IndexVentures, AdamsStreetPartners, S32, and others.
– Cloover, a Berlin, Germany-based operating system designed for energy independence, raised $22 million in Series A funding. MMCVentures and QEDInvestors led the round and were joined by LowercarbonCapital, BNVTCapital, BoschVentures, and others.
– Statusphere, a Winter Park, Fla.-based influencer marketing technology platform, raised $18 million in Series A funding. VolitionCapital led the round and was joined by HearstLab, 1984Ventures, and HowWomenInvest.
– DominionDynamics, an Ottawa, Canada-based defense technology company, raised $21M CAD ($15.2M USD) in seed funding. Georgian led the round and was joined by BessemerVenturePartners and BritishColumbiaInvestmentManagementCorporation.
– Cosmos, a New York City-based image collection and discovery platform, raised $15 million in Series A funding. ShineCapital led the round and was joined by Matrix and others.
– Mave, a Toronto, Canada-based real estate AI company, raised $5 million in seed funding from StaircaseVentures, RelayVentures, N49P, and AlatePartners.
– Stilla, a Stockholm, Sweden-based developer of an AI designed to accommodate entire teams, raised $5 million in pre-seed funding. GeneralCatalyst led the round and was joined by others.
– AsymmetricSecurity, a London, U.K. and San Francisco-based cyber forensics company, raised $4.2 million in pre-seed funding. SusaVentures led the round and was joined by HalcyonVentures, OverlookVentures, and angel investors.
PRIVATE EQUITY
– ConnectWise, backed by ThomaBravo, acquired zofiQ, a Toronto, Ontario-based agentic AI technology company designed to automate high-service desk operations. Financial terms were not disclosed.
– GrantAvenueCapital acquired 21stCenturyHealthcare, a Tempe, Ariz.-based vitamins, minerals, and supplements company. Financial terms were not disclosed.
– HighlanderPartners acquired Tapatio, a Vernon, Calif.-based hot sauce brand. Financial terms were not disclosed.
– PlatinumEquity acquired CzarnowskiCollective, a Chicago, Ill.-based exhibit and events company. Financial terms were not disclosed.
– UnitedBuildingSolutions, backed by AEIndustrial, acquired DFWMechanicalGroup, a Wylie, Texas-based HVAC solutions company. Financial terms were not disclosed.
IPOS
– PicPay, a Sao Paolo, Brazil-based digital bank, now plans to raise up to $435.1 million in an offering of 22.9 million shares priced between $16 and $19 on the Nasdaq. The company posted $1.7 billion in revenue for the year ended September 30. J&F International and BancoOriginal back the company.
– EthosTechnologies, a San Francisco-based online life insurance provider, plans to raise up to $210 million in an offering of 10.5 million shares priced between $18 and $20. The company posted $344 million in revenue for the year ended Sept. 30. GeneralCatalyst, HeroicVentures, EricLantz, and others back the company.
FUNDS + FUNDS OF FUNDS
– BlueprintEquity, a La Jolla, Calif.-based growth equity firm, raised $333 million for its third fund focused on enterprise software, business-to-business, and tech-enabled services companies.
PEOPLE
– Area 15 Ventures, a Castle Pine, Colo.-based venture capital firm, promoted AdamContos to managing partner.
– BullCityVenturePartners, a Durham, N.C.-based venture capital firm, hired CarlyConnell as a principal.
– HarvestPartners, a New York City-based private equity firm, promoted LucasRodgers to partner, MatthewBruckmann and IanSingleton to principal, and ConnorScro to vice president on the private equity team.
– Wingman Growth Partners, a Greenwich, Conn.-based private equity firm, hired CheriReeve as CFO. She previously served as principal and CFO at AtlasHoldings.
Politics8 years ago