Tesla is reportedly considering cleaving off its entire business in China to grease the wheels of a merger with SpaceX, according to the Wall Street Journal.

The newspaper reports that “some Tesla executives have been told to prepare for a separation of the China business,” which could include a “spinoff, sale or closure,” citing unnamed sources. The company reportedly would be able to do this fairly quickly because CEO Elon Musk had already tasked executives to prepare for a split in the event that Beijing invades Taiwan.

Separating China from Tesla’s global operations could make it easier to integrate the company into SpaceX, which is a defense contractor that has to follow strict rules around citizenship and national security. That would also be a major concession. China has grown to dominate Tesla’s business, not only as a market for its vehicles, but as a production hub that serves Asia more broadly, and also Europe.

Ellis AI announced Thursday its emergence from stealth with $10 million in seed funding from investors including First Round Capital, 645 Ventures, Harlem Capital, Khosla Ventures, Thrive Capital, Slow Capital, and Ariel Alternatives CEO Mellody Hobson.

Ellis uses AI agents to tackle the fragmented workflow private credit managers deal with, including managing documents, spreadsheets, and correspondence. The company was founded by Ryan Williams, best known for co-creating the real estate investment platform Cadre alongside Josh and Jared Kushner back in 2014. That company raised more than $160 million in funding and, at its peak, was valued at $800 million before being sold for an undisclosed sum to the alternative investment company Yieldstreet in 2024.

“At Cadre, I saw the next major constraint,” Williams said. “Even as the front end of private markets became more modern and accessible, the operating infrastructure underneath it remained fragmented.”

He started working on Ellis last year. The company seeks to connect and centralize all the scattered software, accounting information, and documents a private credit firm would use into one easily accessible platform. The system can flag discrepancies in the data and uses AI agents to help perform tasks like portfolio monitoring and preparing reports.

For example, Williams promises the agents can help close a fund’s books at the end of the month.

“A team may have to download files from several systems, reformat the data, compare balances, investigate discrepancies, and re-enter information by hand. In many firms, Excel becomes the operating system,” he continued. “Ellis connects to the systems and documents a firm already uses rather than forcing it to rip everything out and start over.”

It keeps a human in the loop, too, he says. “Material decisions and actions remain with the human experts,” he said.

“I expect the human loop to become narrower, but not disappear,” he continued, when asked if he sees a day when the AI works fully autonomously. “Our goal is not to replace human judgment; it’s to help people cut through the noise and make educated decisions faster.” 

Cybercriminals are using AI to move faster, and companies are paying a premium when those attacks lead to data breaches.

IBM found that AI played a role in one in four malicious breaches examined for its 2026 Cost of a Data Breach Report, a 56% increase from the previous year. These incidents cost organizations an average of $6 million — about $1 million more than the global average breach cost of $4.99 million.

Conducted by the Ponemon Institute, the study examined breaches experienced by 602 organizations between March 2025 and February 2026.

The findings also reveal a growing imbalance for security teams: Many organizations are using AI to detect attacks already underway, but far fewer are deploying it to find vulnerabilities before attackers can exploit them.

“What’s changing is the economics of cyberattacks. AI is making attacks faster and cheaper, while breaches keep getting more expensive,” said Suja Viswesan, vice president of IBM Security Software. “When organizations have an extended gap between discovery and remediation, that imbalance shows up directly in breach costs.”

Companies are using AI, but not where attackers are moving fastest

Organizations that used AI and automation extensively in security operations reported breach costs averaging $1.93 million less than organizations that did not use the technologies, according to IBM.

However, IBM found that many companies are still using AI mainly after attacks begin. More than half of breached organizations reported using AI agents for threat detection and containment, but only 18% used agents for vulnerability management.

That gap could become increasingly consequential as attackers use AI to accelerate vulnerability discovery and exploitation.

IBM found that more than 20% of organizations experienced breaches involving AI models or applications. The most common causes were weaknesses around AI systems rather than the models themselves, including compromised APIs, applications or plug-ins, as well as cloud misconfigurations affecting AI workloads.

Critical industries face higher AI-related risks

Critical infrastructure organizations experienced the majority of reported AI-driven attacks, accounting for 62% of incidents. Financial services and energy companies saw some of the highest concentrations of AI-related attacks.

Financial services breaches averaged $6.3 million, while energy breaches averaged $5.2 million, highlighting the potential for cyber incidents to affect essential services, supply chains and broader economies. Healthcare remained the most expensive industry for breaches for the 13th consecutive year, with average costs reaching about $6.6 million, according to IBM’s findings.

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AI governance remains a weak point

While companies are increasing AI adoption, many are struggling to control how the technology is used internally. Shadow AI — the use of AI tools or systems without organizational approval or oversight — was involved in 43% of the incidents IBM studied, more than twice the previous year’s share.

IBM also found that 92% of organizations affected by AI-related breaches lacked proper access controls for their AI systems. The finding suggests that weak identity management, limited governance and poor oversight may be leaving AI systems unnecessarily exposed.

The report also identified gaps in basic data protection. Only 37% of breached organizations said they encrypted sensitive data both at rest and in transit, while many lacked a complete inventory of encryption keys, certificates and other cryptographic assets.

Security teams face a race against AI-powered attackers

The report suggests that businesses cannot rely only on traditional security improvements. AI is speeding up attacks, but it can also help organizations respond faster if deployed correctly.

The challenge is deciding where AI should be applied. Many companies are using AI to investigate alerts after suspicious activity appears, but fewer are using it to proactively identify vulnerabilities before attackers find them.

Also read: The Biggest Data Breaches of 2026, Ranked by Impact.