Google is a ‘bad actor' says People CEO, accusing the company of stealing content

Neil Vogel, CEO of People, Inc., a major U.S. publisher, has accused Google of "stealing" content for its AI models by using a unified crawler for both search indexing and AI training, while simultaneously reducing traffic to publishers (People, Inc. saw Google traffic drop from ~65% to high 20s). To counter this, People, Inc. is blocking non-Google AI crawlers to compel licensing agreements, reporting progress with "large LLM providers." This conflict highlights the escalating battle over content monetization and intellectual property in the AI era, with industry observers like Cloudflare's CEO predicting Google will eventually be forced to pay content creators for AI training data.

Analysis

A significant conflict is escalating between content publishers and Google (GOOGL) over the use of proprietary data for AI training. The CEO of People, Inc. accuses Google of being an "intentional bad actor" for using a single web crawler for both its search index and its AI models, effectively forcing publishers to allow content scraping for AI to maintain their search traffic. This has tangible consequences, as People, Inc. reports its Google-driven traffic has fallen from approximately 65% to the "high 20s." In response, the publisher is leveraging Cloudflare's (NET) technology to block other AI crawlers, a strategy that is reportedly forcing "large LLM providers" into licensing negotiations. The situation highlights a critical strategic vulnerability for Google, which faces reputational damage and a potential future financial liability. Notably, Cloudflare's CEO predicts that competitive and regulatory pressures will compel Google to begin paying for content used in its AI models within the next year, signaling a potential fundamental shift in the cost structure for AI development.

Key Decisions for Investors

• Investors in Alphabet (GOOGL) should closely monitor for developments regarding content licensing negotiations and potential antitrust or regulatory actions, as a shift toward paying publishers for AI training data would introduce a significant new, and currently unpriced, operational cost.
• The successful use of crawler-blocking technology presents a potential upside for publishers with extensive, high-quality content libraries, as they gain leverage to create new revenue streams from AI licensing; this also positions technology enablers like Cloudflare (NET) as beneficiaries of this trend.
• This conflict underscores that the value of proprietary data is a critical and contentious factor in the AI arms race, suggesting that a company's long-term competitive advantage in AI may hinge significantly on its ability to secure training data ethically and cost-effectively.