The State of Agentic AI: Disrupting Publishing and Reshaping Ecommerce

• Agentic AI is revolutionizing web interactions, changing how people shop, search, and consume content.
• AI-driven traffic is growing rapidly, with a 200% increase in 2025, and is disrupting traditional publishing and ecommerce business models.
• The impact on ecommerce varies by industry: Travel has reacted positively, while retail faces challenges, such as missed upsell opportunities.
• Publishers and online forums face significant revenue threats as AI agents reduce page views and ad revenue.
• Organizations can use Akamai's bot and abuse solutions to detect agentic traffic and protect against abuse.

Lately, we have been hearing a lot about AI bots, agentic AI, and the emerging field of agentic commerce. AI platforms offer a new way for users to interact with the internet, promising to make consumers’ lives easier by helping them find information faster and streamline their shopping experience. 

When discussing AI bots, the conversation typically revolves around Perplexity, ChatGPT, Gemini, Claude, and other well-known AI platforms. As new AI platforms emerge and user adoption grows, Akamai has observed a steady increase in traffic originating from AI platforms, targeting both web content and APIs (Figure 1).

Before we take this discussion any further, let’s define what an AI agent is. 

According to Anthropic, "Agent can be defined [...] as fully autonomous systems that operate independently over extended periods, using various tools to accomplish complex tasks.” Agents may be autonomous when it comes to figuring out how to execute and solve a task, but let's be clear: The task is always initiated by human interaction with the AI platform.

In contrast, the same complex interaction can be performed manually through a browser, albeit more slowly, and would require the human brain to summarize and arrive at the necessary answer. It’s essential to understand this context to demystify the role of AI agents and AI platforms. Figure 2 shows the typical interaction between the user, the AI agent, and public websites.

AI agents often use headless browser technology to render and ingest the content they collect or execute actions on the targeted site on behalf of users. They are not designed with malicious intent. 

However, this doesn’t mean that a user cannot trick them into performing malicious activity. (Guardrails must be in place on the AI platform to prevent such things, but that topic is beyond the scope of this blog post.)

AI platforms also scrape the internet to train their models, which enables their agents to perform. Going back to the prompt from our earlier example — “Give me a summary of the major events that happened around the world within the last 24 hours?” — part of the answer may be available in the data used to train the model, but the AI agent may also need to visit the websites it trained on in real time to get the latest information. 

The trained model will help the agent determine which site to consult to get all the necessary data to formulate an answer, then produce a summary. 

AI agents disrupt established modes of interaction with websites and internet revenue models. Figuring out how to deal with AI bots is becoming an existential problem for publishers. For merchants, AI bots don’t pose an imminent threat but rather represent an opportunity. The internet is still figuring out how to adapt to this mode of interaction.

Despite initial wariness in the market about AI agents and the knee-jerk reaction to block this new type of bot that collects massive amounts of data, ecommerce website owners have quickly reversed course and are now looking to optimize their infrastructure to cater to AI agents.

The travel industry has so far reacted positively to agentic traffic. The decision to use an AI agent to book a trip may vary depending on whether you’re booking a business trip or a vacation. 

I could see myself, for instance, asking ChatGPT to book my airfare and hotels for a recurring business trip to Akamai’s headquarters, where I usually take more or less the same flight and stay at the same hotel. 

However, I don’t know if I could trust ChatGPT for a more complex task like booking a family vacation for me. Since, in this case, it’s not just about the overall cost and the destination, but it’s also about discovering the destination and figuring out the itinerary, possible activities, and points of interest to see. 

In other words, I don’t think I can trust AI to know what I’m looking for and book the right hotels in a location that my family would enjoy. A complex task like this would require me to provide very detailed descriptions to ensure the agent makes the right choices.

For retailers, introducing an AI application to offer a personal shopper assistant experience probably makes sense, provided the customer knows exactly what they’re looking for. Buying groceries seems like a straightforward proposition for agentic commerce, but shopping for other items may be a different story. Shoppers like me generally only have a vague idea of what we want until we see a specific item. 

In some cases, describing what we want to the AI system may be challenging. However, one can imagine an AI agent that serves as a personal shopper, asking the user about their tastes, offering different product options for the user to select, and, through trial and error, learning the user's preferences over time.

On the surface, agentic commerce doesn’t seem to be a problem for ecommerce and may help attract more customers to a brand. However, in a pure agentic interaction, merchants may miss out on upsell opportunities. If someone is interested in buying a specific item, AI bots can select products or services that match the criteria and immediately handle the checkout process. 

Although this system is efficient, end users will not see the recommended products and services that the website’s marketing team went to great lengths to position, so it potentially limits the dollar amount a user will spend.

For hype event sales — such as limited-edition sneaker drops, concert tickets, Pokémon card restocks, or Labubu doll releases — AI agents pose a different challenge. 

For years, custom bots have been developed to automate the purchase of limited-availability items, a practice that the industry has fiercely opposed in an effort to prevent scalping and price inflation while also ensuring consumer fairness. 

AI agents can now easily perform all the tasks that custom bots were previously designed to handle. Traditional bots may soon be replaced by AI agents tasked with monitoring the release of specific items and purchasing them when available. This will require retailers to adopt different policies regarding AI agents for products with limited availability.

The adoption of AI agents is already strong for web search. I often use them when researching various topics. 

I appreciate the convenience of receiving a summary of the subject (often technical and related to internet protocols), the option to ask more pointed questions if I want to delve deeper, and the occasional check of the original material used to formulate the answer. 

Unfortunately, this new behavior poses a problem for publishers or online forums that only offer information and depend on online ad revenue and affiliate marketing to generate revenue. Today’s users don’t always visit the sites where the original data was collected to generate the answer. 

If someone wants the latest news or tomorrow’s local weather forecast, they may instead ask ChatGPT or similar platforms for the highlights. Similarly, as an engineer, I can be satisfied with the code example Claude from Anthropic provides and no longer need to visit forums like Stack Overflow.

This drop in page views reduces revenue for sites that depend on online advertising and/or subscriptions. Online ads and, to some extent, the collection of user data have allowed a significant part of the internet to remain free and keep publishers in business. The new mode of interaction through AI agents poses a threat to this business model.

Agentic AI is transforming how users and automation interact with the web — changing how people shop, search, and consume content. As AI-driven traffic continues to rise, it’s disrupting traditional publishing business models and reshaping online commerce.

Akamai’s bot & abuse solutions give organizations the visibility and control to understand this shift by helping them detect agentic traffic, protect against abuse, and prepare for what’s next.

Stay tuned for our next post in this series, in which we’ll explore how bot management must evolve to meet these changes.