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Amazon blocks AI bots from major tech companies amid commerce battle

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Amazon has intensified its campaign to block artificial intelligence companies from accessing its e-commerce platform, according to updates discovered on August 21, 2025, to the retail giant’s robots.txt file. The company recently added six more AI-related crawlers to its publicly available restrictions, targeting bots from Meta, Google, Huawei, Mistral and other technology firms.

According to independent analyst Juozas Kaziukėnas, who first spotted the changes, Amazon’s updated code now explicitly prohibits these companies from scraping data from the world’s largest online marketplace. “Amazon is desperately trying to stop AI companies from training models on its data,” Kaziukėnas wrote in a LinkedIn post on Thursday.

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The August 21 update expands previous restrictions Amazon implemented at least a month earlier against crawlers from Anthropic’s Claude, Perplexity, and Google’s Project Mariner agents, according to The Information. These robots.txt files function as standard website instructions for automated crawlers, though restrictions operate on an advisory basis rather than as enforceable barriers.

Amazon maintains a $56 billion advertising business built around shoppers browsing its marketplace. The company generates revenue through sponsored product listings, display advertisements, and video content across its ecosystem. Third-party AI tools that bypass Amazon’s storefront could potentially undermine both website traffic and advertising revenue streams.

Kaziukėnas suggested the timing of these restrictions may be too late to prevent AI model training. “I think it is too late to stop AI training — Amazon’s data is already in the datasets ChatGPT and others are using,” he noted. “But Amazon is definitely not interested in helping anyone build the future of AI shopping. If that is indeed the future, Amazon wants to build it itself.”

The restrictions come as Amazon develops its own artificial intelligence shopping tools, including Rufus, a chatbot currently testing advertising features according to Adweek reporting from last year. Amazon has also been testing its own “buy-for-me” feature that can purchase items from third-party websites for customers, positioning the company to control how AI integrates with shopping on its platform.

Industry experts view these developments through the lens of competitive dynamics in AI-powered commerce. Eric Seufert, analyst at Mobile Dev Memo, argued on social media platform X that blocking AI agents serves Amazon’s business interests. “The fundamental flaw with ‘agentic commerce’ or ‘agentic advertising’ is that it violates the motivations of retail outlets to 1) control the customer relationship and 2) monetize their first-party data with advertising,” Seufert wrote on August 29.

Seufert emphasized that retail platforms lack commercial motivation to allow unrestricted third-party agent access. “Amazon and Shopify are blocking AI agents because they want to retain ownership of discovery,” he explained. “This natural inclination has surfaced repeatedly in history: walled gardens operate with more attractive economics than open advertising ecosystems because first-party privileges confer such significant commercial advantages.”

Advertising technology expert Karsten Weide offered a contrasting perspective on the long-term effectiveness of these blocking strategies. “Ultimately, blocking personal shopping bots will be a losing defensive battle,” Weide posted on X on August 30. “First it’s going to be drip drip drip in niches, giving competitive advantages to smaller, specialized retailers, but eventually it’ll turn into a stream, then a torrent.”

Weide predicted fundamental changes in consumer commerce patterns driven by AI agents. “A lot of consumer commerce will go through agents. Why would I spend a hour on the machine just to find the best offer for Brooks sneakers size 10?” he questioned. According to Weide’s analysis, brands will lose direct customer relationships but gain connections with “machine servants” that execute purchases on behalf of consumers.

The shift toward AI-mediated commerce could reshape advertising strategies, according to industry observers. Weide suggested that “D/R advertising will fade. Brand advertising will gain in importance as we want to influence consumers before they tell their agent what to do.” This transformation would prioritize brand awareness campaigns over direct response advertising formats that currently dominate digital marketing spending.

Shopify, Amazon’s primary competitor in e-commerce technology, has taken a different approach to AI agents. According to Modern Retail reporting from July, Shopify introduced warning language to merchants’ robots.txt files rather than outright blocking specific companies. Shopify’s “Robot & agent policy” requires “buy-for-me” agents to include human review steps and directs developers to integrate Shopify’s checkout technology into their tools.

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The e-commerce platform has also pursued partnership opportunities with AI companies. Shopify has partnered with Perplexity and reportedly is preparing to integrate with OpenAI to enable transactions through AI chatbots, according to The Financial Times. This collaborative approach contrasts with Amazon’s more restrictive stance toward third-party AI tools.

PPC Land previously reported that over 35% of leading websites now block OpenAI’s GPTBot, with varied blocking rates for other AI crawlers. The trend began shortly after OpenAI announced GPTBot on August 7, 2023, with major sites including Amazon, Quora, The New York Times, and CNN implementing blocks within two weeks.

Other major retailers have not followed Amazon’s approach to AI bot restrictions. Walmart and eBay have not made changes blocking AI bots from their sites, according to a review of their robots.txt files conducted by Modern Retail. This divergence suggests different strategic approaches to balancing competitive positioning with potential benefits from AI-powered shopping tools.

Recent analysis by HUMAN Security found that 80% of companies utilizing the cybersecurity firm’s platform chose to block known large language model user-agents outright. The report, published in July 2024, analyzed over one quadrillion online interactions throughout 2023, revealing widespread wariness among businesses toward AI-powered web crawlers.

The implications extend beyond immediate competitive concerns to fundamental questions about data ownership and monetization in the AI economy. As Seufert noted, “Retail platforms have no commercial motivation to allow third-party agents, broadly and without restriction, to browse their catalogue or to make purchases directly. If agentic commerce takes shape, it’s likely to occur through narrowly-scoped, explicit partnerships that tilt in favor of the platforms.”

Amazon’s approach reflects broader tensions in the technology industry over AI training data access. McKinsey’s Technology Trends Outlook 2025 identified agentic AI as the most significant emerging trend for marketing organizations, representing a shift toward autonomous systems that can independently manage complex workflows.

The effectiveness of robots.txt restrictions depends entirely on voluntary compliance from AI companies. Well-behaved crawlers typically respect these advisory blocks, but enforcement mechanisms remain limited. As Kaziukėnas observed, “Amazon is a treasure trove of e-commerce data. It is notable that Amazon seems to be the only one actively fighting this.”

Amazon’s stance becomes more significant considering the company’s own artificial intelligence investments. The company reported 22% growth in advertising revenue to $15.7 billion in Q2 2025, with substantial investments in AI-powered tools that optimize campaign performance while reducing operational complexity for advertisers.

The timing of Amazon’s expanded AI bot restrictions coincides with increasing regulatory attention on AI companies’ data collection practices. US Attorneys General from 44 jurisdictions recently warned artificial intelligence companies about accountability for exploitation of children through predatory AI products, demonstrating growing governmental oversight of AI development practices.

For the marketing community, these developments signal potential disruption to existing digital advertising models that rely on open data access and traditional customer acquisition funnels. As PPC Land has documented, the intersection of AI technology and advertising continues evolving rapidly, with platforms implementing new tools and restrictions that reshape how brands reach consumers.

The battle over AI access to e-commerce data reflects deeper questions about the future of online shopping and advertising. Whether Amazon’s defensive approach proves successful in maintaining its competitive position, or whether alternative pathways emerge for AI-powered shopping tools, will likely determine how consumers interact with digital commerce in the coming years.

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PPC Land explains

Robots.txt: A standard protocol file that websites use to communicate instructions to web crawlers and automated bots about which parts of their site should or should not be accessed. While these instructions operate on an advisory basis rather than enforceable restrictions, well-behaved crawlers typically respect these guidelines. Amazon’s robots.txt file serves as the primary mechanism for blocking AI companies from accessing its e-commerce data, though compliance depends entirely on voluntary cooperation from the crawlers.

AI Crawlers: Automated software programs deployed by artificial intelligence companies to systematically browse and collect data from websites for training large language models and other AI systems. These crawlers, such as OpenAI’s GPTBot, Anthropic’s Claude bot, and Google’s various AI agents, identify themselves when accessing websites, allowing site owners to make informed decisions about blocking or allowing access to their content.

Agentic Commerce: An emerging model where artificial intelligence agents autonomously conduct shopping activities on behalf of consumers, including product research, price comparisons, and purchase decisions. This concept represents a fundamental shift from traditional e-commerce where consumers directly interact with retail websites, potentially disrupting established customer acquisition and advertising models that depend on direct consumer engagement with brand websites.

E-commerce Data: The comprehensive information generated by online retail platforms, including product listings, pricing, customer reviews, inventory levels, and purchasing patterns. For Amazon, this data represents both a competitive advantage and the foundation of its advertising business, making it a valuable resource that AI companies seek to access for training models and developing shopping assistance tools.

First-party Data: Information that companies collect directly from their own customers through owned channels such as websites, mobile apps, and retail locations. Amazon’s first-party data includes shopping behaviors, preferences, and transaction history that enables targeted advertising and personalized experiences. This data becomes more valuable when companies can prevent third-party access and maintain exclusive relationships with customers.

Advertising Business: Amazon’s rapidly growing revenue stream that generated $15.7 billion in Q2 2025, representing 22% year-over-year growth. This business model relies on brands paying for sponsored product listings, display advertisements, and video content placement across Amazon’s ecosystem. The advertising business faces potential disruption if AI agents bypass Amazon’s storefront and reduce the platform’s ability to monetize customer discovery and purchase decisions.

Shopping Chatbot: AI-powered conversational interfaces that assist consumers with product discovery, recommendations, and purchase decisions. Amazon’s Rufus represents the company’s entry into this category, currently testing advertising features that could generate revenue while maintaining customer relationships. These tools compete directly with third-party AI shopping agents by providing similar assistance within the platform’s controlled environment.

Walled Gardens: Closed digital ecosystems where platforms maintain exclusive control over user data, advertising inventory, and customer relationships. Amazon operates as a walled garden by restricting third-party access to its customer data while developing internal tools that compete with external services. This approach generates more attractive economics compared to open systems because first-party privileges provide significant commercial advantages in advertising and data monetization.

Web Scraping: The automated process of extracting data from websites using software programs that systematically access and download information. AI companies use web scraping to collect training data from e-commerce platforms, though this practice faces increasing restrictions as websites implement blocking mechanisms. The effectiveness of scraping depends on whether target websites implement technical barriers and whether scrapers respect voluntary restrictions like robots.txt files.

Customer Relationship: The direct connection between brands or retailers and their customers, encompassing data collection, communication channels, and influence over purchase decisions. Amazon’s blocking of AI agents reflects concerns about losing customer relationships to intermediary services that could reduce the platform’s ability to collect first-party data and monetize customer interactions through advertising and personalized experiences.

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Summary

Who: Amazon, the world’s largest e-commerce platform, implementing restrictions against AI companies including Meta, Google, Huawei, Mistral, Anthropic, and Perplexity.

What: Amazon added six more AI-related crawlers to its robots.txt file on August 21, 2025, expanding previous restrictions to prevent artificial intelligence companies from scraping e-commerce data from its marketplace.

When: The latest updates were discovered August 21, 2025, building on restrictions implemented at least a month earlier targeting other AI companies’ crawlers.

Where: Changes apply to Amazon’s publicly available robots.txt file that provides instructions to automated web crawlers attempting to access the retail giant’s sprawling website and marketplace.

Why: Amazon seeks to protect its $56 billion advertising business built around shoppers browsing its site while developing its own AI shopping tools like Rufus chatbot and “buy-for-me” features, preventing third-party AI tools from bypassing its storefront and undermining both traffic and ad revenue.



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Globevisa CEO Unveils its AI Strategy, Transforming Traditional Services Into a Tech-Driven Powerhouse

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August 31, 2025

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HongKong, China, August 31, 2025 — In a decisive move set to redefine the future of service industries, Globevisa Group CEO and co-founder Henry Fan has launched a groundbreaking artificial intelligence (AI) transformation strategy that embeds AI at the core of the company’s operations. This bold initiative is not only improving efficiency and customer service but also positioning Globevisa as a global innovator in tech-driven business leadership.

Rather than relegating AI to a standalone IT function, Henry established an in-house AI Empowerment Center—a “special forces” unit that reports directly to him. This reflects his belief that AI is a business-wide opportunity, not a departmental add-on. As the architect of this transformation, Henry serves as strategist, change agent, and internal evangelist, overseeing a company-wide shift in how AI is deployed, adopted, and embraced.

The Strategist: Defining a Clear Vision for AI

Henry’s leadership begins with a clear vision for an “AI-driven Globevisa,” which he positions as the company’s North Star. This vision guides every decision, from budget allocation to the selection of core technologies. Henry ensures that AI efforts are tightly aligned with Globevisa’s business objectives, such as revenue growth, operational efficiency, and brand enhancement.

His approach is pragmatic and phased, focusing on high-value pilot projects before scaling up. He champions a “showcase to full coverage” strategy, quickly demonstrating tangible results in areas like marketing, customer service, and human resources. By tying AI initiatives directly to measurable business outcomes, such as reducing document processing times, increasing content production efficiency, or improving sales conversion rates, Henry ensures that Globevisa’s AI efforts are not just theoretical but practical and impactful.

Tackling Operational Inefficiencies with AI

Henry’s journey into AI began with a recognition of inefficiencies in the company’s internal processes, which were bogged down by repetitive, manual tasks. He saw AI not as a buzzword but as a tool to address these core operational challenges.

1.Document Processing

Globevisa’s success involves processing countless client documents, such as bank statements and passports, a task prone to human error and delays. To combat this, Henry spearheaded the development of an AI document extraction and auditing tool. This technology scans documents, extracts key information, and cross-checks it against system requirements, significantly reducing manual review time and errors. The result is faster, more accurate processing, enabling the team to handle a higher volume of clients.

2.Customer Service

Globevisa’s customer service team was overwhelmed by repetitive inquiries, leaving little time for complex, high-value interactions. Henry’s team introduced a 24/7 AI-powered chatbot capable of handling up to 80% of standard queries. This freed human staff to focus on nuanced, emotional, and complex client concerns, enhancing overall customer satisfaction.

3.Marketing Content Creation

The process of generating marketing content was slow and often lacked variety. Henry addressed this by deploying an “AI Content Factory” that generates blog posts, social media updates, and ad copy from simple keywords. This tool dramatically increased content production efficiency while reducing costs, ensuring Globevisa remains competitive in its digital marketing efforts.

The Breaker of Barriers: Overcoming Organizational Challenges

While implementing AI solutions, Henry quickly realized that the biggest obstacles were not technological but organizational and cultural. Resistance to change, data silos, and fears of job displacement were among the challenges he faced.

1.Breaking Data Silos

With 110,000 successful cases in hand, Globevisa sits on a treasury of data. However, many departments at Globevisa operated in isolation, hoarding data and refusing to share it. For instance, the AI team often needed years of sales data to train models, but obtaining access required navigating internal politics. Henry personally stepped in as a “Breaker of Barriers,” reframing data-sharing as an investment in the company’s future rather than a threat. He emphasized that AI would provide departments with sharper tools to achieve their goals, fostering a spirit of collaboration.

2.Addressing Job Displacement Fears

Employees, particularly senior staff such as copywriters, were initially hostile toward AI, viewing it as a potential replacement for their roles. Henry tackled this by redefining their positions and elevating their value. He assured employees that AI would handle 80% of mundane tasks, allowing them to focus on the remaining 20% of creative, high-value work. Copywriters, for example, were rebranded as “AI Creative Strategists” and “Final Quality Controllers,” responsible for refining and overseeing AI-generated drafts. This reframing not only eased fears but also inspired employees to embrace AI as a tool for professional growth.

3.Adjusting KPIs to Reward Adoption

In traditional service industries, departments often cling to outdated KPIs, which can hinder the adoption of new technologies. Henry addressed this head-on by personally revising performance metrics for teams involved in AI pilots. For example, customer service teams previously measured on “calls handled per hour” were now evaluated on metrics like “complex problem-solving rates” and “customer satisfaction scores.” This ensured that employees were rewarded for adopting new behaviors, not for sticking to inefficient practices.

The Chief Evangelist: Fostering a Culture of Innovation

Henry understands that technology alone cannot drive change; it requires a cultural shift. As Globevisa’s “Chief Evangelist,” he regularly communicates the importance of AI initiatives through all-hands meetings, internal newsletters, and personal demonstrations. By openly using AI tools, such as leveraging AI for meeting summaries, he leads by example, fostering a company-wide culture of innovation.

His leadership style is characterized by inclusivity and transparency. Instead of imposing top-down mandates, he actively involves employees in the transformation process, ensuring that AI is seen not as a threat but as an enabler. This human-centric approach has been instrumental in building trust and enthusiasm for AI across the organization.

A Model for the Future of Services

Henry’s approach provides a replicable roadmap for other service-based companies navigating digital transformation. His model centers on measurable value, cultural readiness, and human-AI collaboration, proving that even traditional industries can lead in a tech-first economy.

About Globevisa

Globevisa Group is a global leader in immigration and relocation services, with over 110,000 successful cases worldwide. Committed to service excellence and innovation, the company helps individuals and families navigate complex immigration processes with confidence.

Contact Info:
Name: Lena Huang
Email: Send Email
Organization: GLOBEVISA GROUP (HONG KONG) LIMITED
Website: https://www.globevisa.com/

Release ID: 89168612

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Oak Lawn Community High School to implement AI gun detection tech – NBC Chicago

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4 hours ago

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August 31, 2025

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A high school in suburban Chicago was awarded a grant to implement AI-powered gun detection technology.

Oak Lawn Community High School District 229 was one of 50 recipients selected nationwide for the Omnilert Secure Schools Grant Program, the school said in a recent announcement.

The district was awarded a three-year license for Omnilert Gun Detect, an “advanced AI-powered gun detection technology” — at no cost.

The AI system identifies firearms “in real-time through existing security camera infrastructure,” the announcement said.

Once a potential threat is identified, the AI system activates a rapid response process by alerting school officials and law enforcement, ultimately ensuring that threats can be addressed “as quickly and effectively as possible,” the announcement said.

The implementation of the AI system aligns with District 229’s security strategy, that includes a combination of physical safety measures, emergency preparedness and mental health resources, the announcement said.

The school said staff training and safety drills will be done to ensure the technology is used effectively and responsibly.



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