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AI, IN PERSPECTIVE

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Understand the AI developments that matter, starting with original sources.

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Former Joonko CEO Pleads Guilty to Securities Fraud: False Customer and Revenue Statements Result in Personal Liability for the Founder

Joonko’s former CEO, Ilit Raz, pleaded guilty in October 2026 to federal securities fraud for misrepresenting to investors about the company’s customers, revenue, and AI capabilities, thereby fraudulently securing approximately $27 million in funding. He faces up to 20 years in prison. This case underscores that falsifying key business metrics can result in personal legal liability, and that directors and officers (D&O) insurance provides limited coverage in instances of established fraud.

When Traction Becomes Personal Exposure: What The Joonko Guilty Plea Means For FoundersWhen Traction Becomes Personal Exposure: What The Joonko Guilty Plea Means For Founders

Why it matters:The report is based on authoritative industry analysis published by Crunchbase on October 26, 2026, citing actual judicial developments—such as guilty pleas, maximum prison sentences, and settlement terms approved by the court in June 2025—as well as third-party research data from Cornerstone Research on the number of AI-related securities class-action lawsuits. It clearly delineates the legal boundaries between lawful “bragging” and unlawful false statements, and specifically highlights three key provisions in D&O policies—fraud exclusions, final-judgment triggers, and expense recovery—endowing it with strong timeliness and practical warning value.

Timeline and related coverage

AI Graveyard: A Continuously Updated List of Failed AI Projects and Startups

TechCrunch reported on October 25, 2026, reviewing several AI projects from 2023 to 2026 that failed to meet expectations, including startups and products such as Relay, Character.ai, Sora, and Humane AI Pin, as well as failed attempts or major adjustments by major companies like OpenAI, Apple, and Microsoft.

The AI graveyard: a running list of projects and startups that didn’t make it

Why it matters:This report provides an industry‑wide, phenomenon‑driven overview, with broad coverage and a clear timeline (including specific shutdown or delay dates), and cites S&P Global Market Intelligence data to substantiate the high attrition rate—42%—of enterprise‑level AI projects. It combines detailed case studies with structural analysis, making it a highly valuable reference.

Timeline and related coverage