By Global Tech & Digital Economy Desk
Published: February 2026

Main Facts

The internet as humanity has known it for the past three decades is undergoing a fundamental structural transition. According to recent projections shared by Automattic—the driving force behind powerhouse web infrastructure platforms like WordPress.com and WooCommerce—more than 60% of all traffic hitting its vast network could originate from automated bots by the end of 2026.

This staggering revelation was made public during an in-depth interview between José Ramón Padrón, Automattic’s Head of Spanish-Speaking Communities and Growth, and José Carlos Cortizo for the Product Hackers podcast. The discussion shed light on a transformative era in digital architecture: the shift from a web optimized exclusively for human browsers to a hybrid digital ecosystem heavily navigated, analyzed, and transacted upon by Large Language Models (LLMs), automated indexers, and autonomous AI agents.

Key takeaways from Automattic’s forecast include:

• The Bot Dominance Timeline: Automattic forecasts that non-human traffic will cross the 60% threshold by late 2026 across its extensive infrastructure footprint.
• Dual-Audience Publishing: Digital publishers and merchants must now design content and systems capable of serving two distinct consumers: human readers and algorithmic entities.
• Evolution of E-Commerce: Through initiatives like AI Storefront, WooCommerce is preparing online shops for "agentic commerce," where AI agents make purchases on behalf of human users.
• Infrastructure Integration: Automattic is leveraging the Model Context Protocol (MCP) to seamlessly connect WordPress data and data warehouses with conversational AI architectures.

Chronology: The Evolution of Automattic in the Age of AI

To understand the weight of Automattic’s 2026 prediction, it is vital to trace how the company has evolved from an open-source blogging pioneer into a foundational layer of the modern internet.

• 2005: Matt Mullenweg and Little Mullenweg co-create WordPress, establishing an open-source software project that would eventually power over 40% of all websites globally. Shortly after, Automattic is founded to provide commercial and managed services around the ecosystem.
• The 2010s Expansion: Automattic aggressively diversifies its portfolio, acquiring platforms like Tumblr, WooCommerce (transforming open-source e-commerce), Newspack (tailored digital publishing tools for modern journalism), and WordPress VIP (enterprise-grade hosting and services).
• Late 2023 – 2024 (The Generative AI Boom): As OpenAI’s ChatGPT and other foundation models capture global attention, web traffic patterns begin to shift. Traditional search engine optimization (SEO) yields declining returns as users increasingly rely on generative zero-click answers.
• 2025 (The Integration Phase): Automattic accelerates internal and external AI adoption. The company rolls out AI-driven tools within WordPress VIP and Newspack to assist media organizations with archival mining and visibility analysis. Simultaneously, internal teams begin utilizing advanced MCP (Model Context Protocol) integrations to interrogate data warehouses using natural language.
• Late 2026 (The Projected Turning Point): Automattic estimates that automated bot traffic—ranging from LLM scrapers to task-executing agents—will formally surpass human browsing traffic, accounting for over 60% of total ecosystem requests.

Supporting Data & Context: Understanding the Numbers

The statistic cited by Padrón is not a generalized sweeping claim about the entire global internet, but rather a targeted projection derived from Automattic’s unique vantage point across millions of domains. Powering roughly 41% of all active websites on the web, Automattic processes an astronomical volume of HTTP requests, server logs, and user sessions daily.

Breaking Down the Traffic Shift

For years, digital analytics measured success through a simple binary metric: unique human visitors and page views. Today, server logs reveal an entirely different reality. Traffic is increasingly segmented into:

1. Traditional Human Browsers: Users interacting directly via Chrome, Safari, Firefox, and mobile apps.
2. Indexing & Scraping Bots: Automated crawlers dispatched by OpenAI, Anthropic, Google, and independent startups attempting to ingest the entire textual and visual history of the web to train foundation models.
3. Autonomous Agents: Next-generation systems programmed to execute complex, multi-step workflows—such as comparing prices, verifying inventory, filling out forms, and executing checkout routines without direct human intervention at every stage.

Padrón noted during the Product Hackers interview that while third-party reports have long tracked the rise of automated scraping, Automattic’s internal data modeling points explicitly toward this dramatic tipping point by the close of 2026.

Official Responses and Strategic Adaptations

Automattic is not sitting passively as the traffic landscape shifts beneath its feet. With a globally distributed workforce of approximately 1,450 employees, the company is fundamentally restructuring both its internal operations and its outward-facing software products.

Internal Transformation and Employee Upskilling

Recognizing that artificial intelligence requires a cultural shift, Automattic has instituted comprehensive AI literacy programs for its entire 1,450-person staff. Operating as a fully remote organization, the company coordinates hybrid working retreats (such as alternating weeks between home offices and their New York hub) where cross-functional teams undergo practical training on LLM capabilities, agentic workflows, and process automation.

Employees are encouraged to dedicate weekly hours to identifying repetitive operational workflows that can be augmented or automated by AI, ensuring the organization scales efficiently alongside the technology it champions.

Leveraging the Model Context Protocol (MCP)

One of the most profound technical disclosures from the interview centers on Automattic’s implementation of Model Context Protocol (MCP). By connecting AI models directly to external tools and structured data sources under strict governance and permission frameworks, Automattic has transformed how its growth and data teams operate.

Rather than relying on traditional SQL queries and technical data analysts for customer segmentation, team members can now query data warehouses using natural language. For instance, a growth manager can ask the system to segment WordPress.com users based on domain purchases, traffic volume, and support interactions instantly—accelerating cross-selling and service expansion strategies while maintaining airtight data privacy.

Implications for the Digital Economy

The implications of Automattic’s forecast extend far beyond server bandwidth and hosting costs. They threaten to upend digital publishing, e-commerce, and the fundamental economics of the open web.

1. The Death of Traditional SEO and the Rise of "AI Readiness"

For two decades, digital media outlets and content creators relied heavily on search engine algorithms—primarily Google—to capture eyeballs and monetize via programmatic advertising. However, when an AI assistant answers a user’s prompt directly, the user has zero incentive to click through to the original source article.

Padrón stresses that publishers must pivot away from a singular reliance on search traffic toward direct audience relationships—leveraging newsletters, community events, and sustainable subscription models. Furthermore, websites must optimize for AI readiness, ensuring that content structures, metadata, and context are easily digestible by machine-reading algorithms.

2. WooCommerce and the Era of "Agentic Commerce"

Online retail is facing a parallel revolution. In a future dominated by agentic commerce, a consumer will no longer browse dozens of individual e-commerce storefronts searching for the best deal on red running shoes. Instead, they will instruct an AI agent to locate, vet, and purchase the optimal product.

To prepare online retailers for this paradigm, Automattic is developing AI Storefront, a suite designed to make WooCommerce stores fully discoverable and interactable by autonomous agents. This includes managing zero-result product searches gracefully and deploying automated regression review pipelines to ensure that rapid AI-driven updates do not degrade core store functionality.

3. WordPress as the "Operating System of the Open Web"

Ultimately, Automattic’s grand vision positions WordPress as the ultimate operating system for the open web. By integrating native building tools directly into platforms like ChatGPT (via MCP and custom applications), the company aims to ensure creators maintain ownership of their data rather than being trapped inside closed, proprietary walled gardens.

Frequently Asked Questions

What percentage of traffic does Automattic expect to come from bots?

José Ramón Padrón estimates that by the end of 2026, more than 60% of the traffic hitting Automattic’s infrastructure could originate from automated bots. This is a targeted forecast based on internal modeling rather than a sweeping statistic for the entire internet.

What does it mean to prepare a website for AI agents?

Preparing a website for AI agents involves formatting data, metadata, and site architecture so that automated systems can easily find, interpret, and act upon information. In e-commerce (such as WooCommerce), this means optimizing product catalogs and checkout pathways so autonomous shopping agents can navigate and transact smoothly on behalf of human consumers.

What is the Model Context Protocol (MCP) in WordPress?

The Model Context Protocol (MCP) is an open standard that connects artificial intelligence models securely with external tools and data sources. Automattic utilizes MCP to let LLMs interface directly with WordPress tools, content repositories, and internal data warehouses via natural language queries.

How is Automattic adapting WooCommerce for AI?

Automattic is actively building AI Storefront tools designed to make WooCommerce product data completely transparent and accessible to AI agents. These systems allow automated agents to query inventories, evaluate product offerings, and execute transactions securely within open-source online shops.