AI Stocks Plummet as CEOs Agree to Slow Development

Key Takeaways

• Anthropic CEO Dario Amodei, OpenAI CEO Sam Altman, and Elon Musk agreed to slow down AI development, causing global AI stocks to fall.
• Shares of Nvidia, Intel, ASML, SK Hynix, and SoftBank dropped sharply on September 14, 2026.
• President Donald Trump criticized the call for a slowdown, stating it would hurt US competition against China.
• Google, Anthropic, and OpenAI are discussing forming their own AI industry standards body since July.
• Nvidia and Palantir raised financial guidance and continue to lead AI sector growth.
• Nvidia holds a $99 billion investment portfolio in AI companies including Cerebras Systems, Databricks, and H2O.ai.
• Cerebras Systems partners with Amazon Web Services to support OpenAI's GPT-5.6 Sol at ten times the speed.
• Anthropic is preparing for an initial public offering to raise billions for data center construction.
• Zip Security joined CrowdStrike's Project QuiltWorks to provide AI security to small businesses.
• Secern AI secured a 2.45 billion won contract to build a secure coding platform for the Republic of Korea Air Force.

AI stocks drop after CEOs call for development slowdown

Global stocks tied to artificial intelligence fell on Monday after Anthropic CEO Dario Amodei urged a slowdown in AI development. Major tech leaders including OpenAI CEO Sam Altman and Elon Musk agreed with the proposal to pace the frontier. Shares of companies like Nvidia, Intel, ASML, SK Hynix, and SoftBank dropped sharply in trading across Asia, Europe, and the US. Investors worry that slowing development could hurt future earnings and chip purchases. The move follows a debate sparked by researchers warning about potential risks from rapidly improving AI models.

Tech stocks sink globally as leaders back AI pause

AI-linked stocks fell across Asia, Europe, and the US after top CEOs supported a call to slow down AI progress. Anthropic CEO Dario Amodei started the conversation, and OpenAI CEO Sam Altman and Elon Musk publicly agreed with his view. This decision comes after researchers raised concerns about safety, with one suggesting a high chance of AI causing harm within a decade. President Donald Trump rejected the slowdown, arguing it would hurt US competition against China. Analysts warn that a coordinated pause could make it hard to predict company earnings and stock values.

AI shares fall after tech bosses unite on safety

Global artificial intelligence stocks declined on September 14, 2026, after Anthropic CEO Dario Amodei called for a slower pace in AI development. Competitors like OpenAI CEO Sam Altman and SpaceX CEO Elon Musk backed the idea to monitor AI risks more closely. In Europe, stocks for ASML, Nokia, and Infineon dropped significantly, while US companies like Micron and Intel also saw sharp losses. President Donald Trump criticized the call for regulation, stating that strong leadership is enough to control AI. Experts note that while training might slow, the demand for running AI models remains very high.

Big AI firms discuss forming their own standards group

Anthropic, Google, and OpenAI have been talking about creating their own industry standards body for artificial intelligence. These discussions have been ongoing for several months to address concerns about a lack of regulation and oversight. The goal is to ensure AI technologies are developed and used in a transparent and accountable way. A spokesperson for Anthropic did not comment, while OpenAI representatives said they are exploring various options for setting standards. Google did not respond to requests for information about these talks.

Google OpenAI and Anthropic explore AI standards group

Representatives from Google, Anthropic, and OpenAI have met regularly since July to discuss forming an AI industry standards body. This idea follows a proposal by Anthropic CEO Dario Amodei to slow down AI development and create voluntary safety standards. OpenAI CEO Sam Altman supports the idea but believes major companies must lead the effort without government backing. The discussions aim to bring transparency and accountability to the fast-growing AI sector. Recent research also shows that companies using AI in many different functions are seeing better financial results than those using it in just one or two areas.

Investors worry AI costs may outweigh future profits

Investors are concerned that the high costs of developing powerful AI models might not be covered by future profits. Companies like Anthropic are preparing for an initial public offering to raise billions for their spending. These funds will support development and the construction of massive data centers for their energy-hungry AI systems.

Secern AI wins defense coding project in Korea

Secern AI won a project to build an AI coding and security platform for the Republic of Korea Air Force. The Ministry of National Defense will use the on-premises solution called IntraGenX, which was launched in March. The project has a budget of 2.45 billion won and involves partners like Sejong University and CodeMind. The system uses a 30-billion-parameter model and works in isolated networks to keep data secure.

NVIDIA and Palantir lead AI growth despite no off switch

NVIDIA and Palantir have both raised their financial guidance and sped up their growth in the AI sector. These companies are earning money at different levels of the technology stack used to build AI. Experts suggest that understanding which company holds the most valuable position matters more than comparing their stock prices.

Marquette Business hosts free AI training for leaders

Marquette Business will host a free AI training session on Wednesday, Sept. 30 in O'Brien Hall. The event is co-sponsored by HumanSkills.ai and the Metropolitan Milwaukee Association of Commerce. Todd McLees from HumanSkills.ai will lead a discussion on how organizations use AI agents to create value. Attendees will also watch a live demonstration by Regal Rexnord showing how to build AI agents for sales and customer service.

CBRS expands AI reach and faces competition from NVIDIA

Cerebras Systems plans to double its system speed annually and increase throughput significantly over the next few years. The company partners with Amazon Web Services and supports OpenAI's GPT-5.6 Sol at ten times the speed. However, NVIDIA remains a major competitor with its Vera Rubin platform that offers higher throughput and lower costs. Alphabet is also increasing pressure with its Tensor Processing Units and expanding Gemini capabilities.

Zip Security Joins CrowdStrike Project QuiltWorks

Zip Security has joined CrowdStrike's Project QuiltWorks to help small businesses protect themselves from advanced AI risks. This partnership focuses on companies that lack a security team, a CISO, or the budget to hire staff. Zip provides a managed platform that sets up security tools, manages protection around the clock, and creates compliance reports automatically. The project combines CrowdStrike's AI technology with services from Amazon Web Services and cyber insurers to offer enterprise-grade security to smaller organizations. This expansion in August 2026 brings high-level protection to businesses that previously could not access it.

Nvidia Holds 99 Billion Dollar AI Investment Portfolio

Nvidia holds a massive portfolio of investments worth 99 billion dollars in public and private companies focused on artificial intelligence. At the end of its second fiscal quarter, the company identified three top companies within this group. Cerebras Systems develops powerful AI chips called the Wafer-Scale Engine that can process 1.5 exaflops of data per second. Databricks offers a cloud platform used by major firms like Microsoft and Google to build and run AI models. H2O.ai creates software tools that make it easy to develop and deploy machine learning solutions efficiently.

New Model Maps Cloud Identities Using Behavior

Security researchers created a new behavioral clustering model to map the roles of identities in expanding cloud environments. The team analyzed the activity of over 40,000 identities across 125 cloud environments over a two-month period. This approach helps organizations identify functional roles like administrators and DevOps users even when standard labels are misleading. The model uses unsupervised machine learning algorithms called UMAP and HDBSCAN to find patterns in cloud audit logs. Palo Alto Networks customers can use this method to improve threat detection without running heavy machine learning pipelines continuously.

Sources

• AI stocks slide after major CEOs unite to urge slowdown
• AI stocks are sinking globally after top tech CEOs back a slowdown in development
• AI stocks fall after CEOs unite behind calls for slowdown
• Top AI companies have discussed creating their own standards body
• Google, OpenAI and Anthropic Float Idea of AI Standards Body
• Slow the AI race? Investors weigh the potential cost
• Secern AI Wins Defense AI Coding, Security Automation Project
• There Is No Off Switch for AI Capability Growth. Here Is Who Benefits Most From That.
• Marquette Business to host free AI training session for business leaders
• CBRS Expands AI Inference Reach: Can It Challenge NVDA & GOOGL?
• Zip Security Joins CrowdStrike's Project QuiltWorks to Secure SMBs Against Frontier AI Risk
• Here Are the Companies in Nvidia's $99 Billion Artificial Intelligence (AI) Portfolio. These 3 Are the Best of the Bunch
• Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection