Wikipedia, the internet’s beloved encyclopedia and a bedrock of online knowledge for more than two decades, is facing a crossroads. As the digital landscape shifts at breakneck speed, the ways people seek information are changing—and Wikipedia’s role is changing right along with them. Recent data from the Wikimedia Foundation, reported on Friday, revealed an 8% drop in human pageviews between May and August 2025 compared to the same period last year. While that number might sound like a simple technical hiccup, it points to a much deeper transformation in how people find answers online.
According to the Wikimedia Foundation, the drop in traffic can be partially traced to updates in its bot detection systems, which reclassified a surge of visits from Brazil as automated rather than genuine human activity. After deploying new standards in May 2025, Wikimedia discovered that “bad bots”—automated scripts scraping and crawling the site—accounted for a whopping 37% of total traffic, up from 32% in 2023. That’s a lot of non-human eyes on Wikipedia’s pages! But even after accounting for these bots, the foundation acknowledges that people are simply visiting less often. Why? The answer lies in the rise of artificial intelligence and the so-called “answer economy.”
Platforms like ChatGPT, Gemini, and Perplexity AI now serve as the first stop for millions of information seekers. Rather than clicking through to Wikipedia and reading an article, users are getting summaries, explanations, and even product recommendations directly from AI-powered chatbots. “People still rely on Wikipedia but now, it’s often indirectly,” a Wikimedia representative explained. “AI systems ingest our content, summarize it, and serve it back through chat interfaces. The credit and traffic don’t always flow back to us.”
This shift is not just about Wikipedia. According to Mark Drasutis, Head of Value for Asia Pacific and Japan at Amplitude, large language models (LLMs) have upended the way people find information and answers. “Google is no longer the default choice when researching a topic, as LLMs give users comprehensive, research-based responses, directly where they’ve asked instead of a list of links to navigate.” As Drasutis points out, this new landscape means users want fast, direct answers rather than doing the detective work of sifting through search results. The expectation is clear: instant, personalized responses, not endless scrolling.
For Wikipedia, this means it has become more of a silent backbone for the AI age—a vast, meticulously curated database that powers the answers people receive from their digital assistants, rather than a destination in itself. The Wikimedia Foundation’s commercial licensing arm, Wikimedia Enterprise, was launched in 2021 to formalize relationships with high-volume reusers like search engines and AI developers. The service offers 99% uptime guarantees, structured data delivery, and bulk access via APIs. Confirmed partners include Ecosia, ProRata.ai, and Gist.ai, but when it comes to the tech giants—OpenAI, Anthropic, Google—the foundation is tight-lipped. There’s no public confirmation on whether these major AI platforms pay for access to Wikipedia’s treasure trove of knowledge.
This lack of transparency has sparked questions about the long-term sustainability of Wikipedia’s model. If more and more users are getting their information secondhand, through AI summaries, can the foundation continue to fund its operations with fewer direct visitors? Analysts wonder whether revenue from Wikimedia Enterprise can offset the decline in human engagement. It’s a tricky balance: Wikipedia wants to remain open and accessible, but it also needs to ensure it’s fairly compensated for the data that powers the world’s digital brains.
Meanwhile, marketers and brands are scrambling to adapt. In this new “answer economy,” as Drasutis calls it, content strategies are being turned upside down. Marketers no longer optimize just for keywords—they have to think about the specific questions their audiences are asking and tailor their content to provide direct, actionable answers. “Users want to ask an LLM a question and get the information or product recommendation without all the detective work,” Drasutis notes. The focus has shifted from creating generic, SEO-driven content to building topical authority and brand mentions that AI systems will surface most often. In other words, it’s not just about being found on Google anymore; it’s about being the name that appears in an AI-generated answer.
To keep up, marketers are treating traffic from LLMs as its own distinct channel, just like search or social media. They’re using tracking links to identify when users arrive via an AI engine and creating content that’s easier for LLMs to understand and summarize. Measuring how often a brand is cited in AI results, and tracking any increases in search volume after major announcements, are now key marketing metrics. The goal is to become the authoritative source that AI platforms trust and reference.
Wikipedia isn’t standing still, either. Recognizing that younger audiences—especially Gen Z—are less likely to visit traditional web encyclopedias, the foundation is experimenting with new outreach efforts. As of October 2025, Wikipedia is exploring short-form educational content on platforms like YouTube and TikTok. The hope is to re-engage users who prefer visual learning and creator-led explainers over dense text. This mirrors broader trends in digital education, where bite-sized videos and interactive content often outperform lengthy articles.
But even as Wikipedia adapts, the fundamental challenge remains: AI has rewritten the path between curiosity and knowledge. LLMs allow customers to make decisions based on complete, contextual information. Marketers are now starting with their customers’ questions and working backward, analyzing feedback to create personalized content that anticipates needs before users even express them. This approach builds trust and drives deeper engagement, but it also means that the traditional gatekeepers of information—like Wikipedia—are no longer front and center.
According to McKinsey and Company, AI is revolutionizing customer experience across Australia and New Zealand, with personalization, efficiency, and proactive service becoming the new gold standard. Brands that fail to adapt risk being left behind as the divide widens between those who embrace the answer economy and those who don’t. For Wikipedia, the challenge is to remain relevant, visible, and sustainable in a world where it’s often the invisible engine behind the answers people receive.
In the end, Wikipedia’s journey mirrors the broader transformation of the internet itself. As AI tools become default companions in classrooms, offices, and on smartphones, the encyclopedia’s role may evolve from destination to indispensable data source—a quiet powerhouse shaping the future of knowledge, even if fewer users realize it.
