In recent years an increasing number of AI products, startups and internal corporate initiatives have been discontinued, shut down or lost their reason to exist as standalone offerings. Causes range from technical hurdles and scaling problems to funding shortfalls, weak user demand, and direct competition from larger platforms.
A brief statistic
S&P Global Market Intelligence estimates that about 42% of corporate AI initiatives are ultimately abandoned by their parent companies. That figure reflects a mix of insufficient funding, technical challenges, competition, scaling difficulty, and lack of product-market fit.
Notable shut-downs and restructurings
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Relay: Relay, an AI-powered workflow automation tool positioned as an alternative to Zapier, shut down entirely in August. The five-year-old product automated email and task workflows using AI agents, but as OpenAI, Google and other major platforms built similar automation into their own tools, Relay increasingly lacked a reason to continue as a standalone product.
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Character.ai: Character.ai’s chatbot platform filed for bankruptcy five years after launching.
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Notion Mail: Notion Mail launched in April 2025 as an AI-focused email product to help organize and automate inboxes. The company found users were using separate AI agents for inbox handling, and Notion Mail is scheduled to shut down on September 22.
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Figgs AI: Operating from 2023 to 2024, Figgs AI allowed users to create and interact with customizable AI characters for role-play and storytelling. The platform reportedly attracted more than 1 million users, but the developers said keeping the service free became too expensive, so they shut it down.
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Yupp: Yupp was a free playground that let users compare responses from hundreds of AI models side by side, vote on replies and earn cryptocurrency. At its peak the platform offered tests of more than 800 models, including ones from OpenAI, Google and Anthropic. According to its founders, Yupp never achieved a strong enough product-market fit and shut down in March 2026.
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Huxe: Founded by former developers of Google’s NotebookLM, Huxe converted written information into conversational, podcast-style audio. The company shut down in May 2026 as larger platforms began to offer similar experiences to broad audiences.
Hardware disappointments and startup failures
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Humane AI Pin: The Humane AI Pin was one of the most publicized AI hardware failures. The wearable device raised $230 million in investment but struggled with performance. The situation worsened when Humane warned customers to stop using its charging case because of a potential battery fire risk. Humane shut down its AI Pin business in February 2025; most of the company’s assets were acquired by HP for $116 million.
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Rabbit R1: Unveiled at CES in January 2024 as an AI companion, Rabbit said it sold 100,000 units shortly after launch. Early reviews described the device as unfinished, with unreliable performance and a limited number of useful integrations. The company has continued updating the R1 and repositioned it as a computer controller capable of agentic tasks, and it announced a new hardware project called “Project Cyberdeck.”
High-profile corporate missteps
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OpenAI: Even the largest players have stumbled. OpenAI’s attempt to turn ChatGPT into a broader “super app” included a July 9 update that combined separate experiences (such as “Chat,” “Codex,” and “Work”) and renamed the familiar interface “ChatGPT Classic.” The redesign drew immediate criticism from users who found the new interface confusing and cluttered, and OpenAI rolled back the change soon after.
OpenAI has also shut down several standalone apps and folded their features directly into ChatGPT, a strategy that in some cases worked better than the redesign. ChatGPT Atlas, a standalone AI-powered web browser, lasted less than a year and was discontinued on August 9, with its most useful features absorbed into ChatGPT. The company similarly curtailed Operator, an AI agent that could browse the web and complete tasks on a user’s behalf, and has increasingly built image-generation capabilities directly into ChatGPT, reducing DALL·E’s role as a separate destination. OpenAI’s video-sharing platform Sora, which faced high operating costs and user-retention challenges, was shut down in March 2026.
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Apple and Siri: When Apple unveiled Apple Intelligence in 2024, a reworked Siri was a key feature, promising better context awareness, cross-app knowledge and effective task execution. Apple repeatedly pushed back the release of the new Siri, citing engineering issues and bugs. Those delays contributed to a $250 million settlement over claims about how Apple marketed the AI capabilities of the iPhone 16. The new Siri appeared in the iOS 27 beta in July, and the AI-powered version began rolling out to English-language users this month; support for other languages is expected to follow.
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Microsoft Recall: Announced at the 2024 Build developer conference, Microsoft’s Recall feature was positioned as an AI-powered “photographic memory” for Windows PCs, periodically taking screenshots of user activity so it could be later searched. The announcement provoked immediate privacy and security backlash: critics warned Recall could create a searchable archive of highly sensitive information, including passwords, private messages and financial details. Microsoft delayed the feature for nearly a year to rethink its privacy and security protections. Even after a redesign, controversy persists: a cybersecurity researcher recently built a tool that could extract and display data Recall had captured, raising questions about whether the underlying issues were truly fixed.
Lessons for the industry
These examples are not just a scoreboard of failures but a record of recurring risks: products can be sidelined when major platforms absorb their core features, when technologies fail to scale securely and reliably, or when users do not find the offerings sufficiently useful. The roughly 42% abandonment rate underscores that AI innovation is high-risk and that many projects will not reach sustainable success.
For companies, the priorities are clear: proper product positioning, robust security and privacy practices, and a realistic assessment of user needs and willingness to pay. Without these, AI projects are at significant risk of joining the growing ‘AI graveyard.’
