Bots Surpass 50% of Internet Traffic, Inflating Tech Valuations as Dotcom Bubble Warnings Resurface
2min read
Aime SummaryThe AI boom is reshaping the digital landscape at an unprecedented pace, yet its momentum is increasingly fueled by non-human activity. Automated bots—software programs designed to perform repetitive tasks—now account for over half of global internet traffic, according to Imperva, a cybersecurity firm. This surge in bot-generated activity has outpaced human interactions, raising concerns about the integrity of metrics that underpin tech company valuations. The implications are profound: bots are inflating key web analytics, such as pageviews, clicks, and user sessions, creating a distorted view of online engagement.
Historically, bots have been both a tool and a threat. From ELIZA, a 1966 chatbot developed at MIT, to Microsoft’s controversial “Clippy,” the line between helpful automation and malicious manipulation has blurred over time. Today’s bots, however, operate on a scale that dwarfs their predecessors. Imperva’s 2024 report highlights that 20% of bot traffic consists of “bad bots” engaged in activities like ad fraud and fake reviews. These programs generate revenue for advertisers by simulating user behavior, even though the interactions are entirely artificial. The annual cost of such fraud is estimated in the hundreds of billions of dollars, according to cybersecurity firms.
The impact extends beyond ad networks. Startups and tech firms increasingly rely on “vanity metrics” such as user sign-ups or app downloads to attract investors. These figures, often unverified and self-reported, can be inflated by bot traffic. Investors use such data to assess company value, creating a feedback loop where artificial growth metrics drive real capital. This dynamic mirrors the dotcom bubble of the 1990s, but with a critical difference: the current AI-driven boom may be even more overvalued. Apollo Global Management’s Torsten Slok, a prominent economist, recently highlighted that the top 10 S&P 500 companies are more overvalued today than during the dotcom era. While Slok did not explicitly address bots, the question remains: if the AI boom is built on bot-driven metrics, how sustainable is it?
Ask Aime: Can the AI boom be sustained given inflated metrics driven by bots?
Regulators are beginning to respond. The Federal Trade Commission (FTC) has introduced rules banning fake AI-generated reviews and testimonials, targeting both traditional and modern bots. A 2024 final rule imposes civil penalties on businesses that disseminate misleading content, whether created by bots or humans. Additionally, the BOTS Act, strengthened in 2025, prohibits the use of automated bots to circumvent ticket-purchasing limits—a practice that has frustrated consumers during high-demand events. These measures aim to curb deceptive practices and restore trust in online markets.
Yet challenges persist. Bots are a decades-old technology, evolving alongside the internet. Their role in distorting metrics may become a normalized, if undesirable, feature of digital ecosystems. Companies dependent on bot-driven growth could face sharp valuation corrections when real-world demand fails to match inflated data. Market consolidation is likely, with investors favoring firms that demonstrate genuine user engagement over those relying on artificial metrics. Third-party verification of analytics and advanced bot-detection tools are expected to grow in demand, though their effectiveness remains to be seen.
The AI revolution’s long-term trajectory hinges on how society balances innovation with accountability. While bots have enabled remarkable technological progress, their misuse threatens to undermine the very foundations of digital trust. As the line between human and machine-generated activity blurs, the need for transparent, auditable metrics becomes ever more urgent. The lessons of the dotcom crash—where speculative hype outpaced real value—serve as a cautionary tale. For now, the bot-driven boom shows no signs of slowing, but its sustainability will depend on whether the market can distinguish between genuine innovation and algorithmic illusion.
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