Are small brands ready for agentic search?

The next big step in how we search the Internet and navigate websites could eliminate the need for searching the Internet or navigating sites altogether. 

Welcome to the world of agentic AI.

This goes far beyond just AI-assisted searches. Agentic AI is capable of acting autonomously and completing tasks on your behalf. Instead of AI just helping you find what a user is looking for, AI agents will be able to complete the tasks you ask them to do.

Google, OpenAI, Microsoft, and more are busy working their products around this new ‘agentic search’ paradigm, pouring billions into the transition. For startups and niche businesses with tight budgets, the pivot looks intimidating, but it’s not hopeless. 

This article explains how agentic search works, showcases the pioneers who are already reaping the benefits, and closes with practical tactics to help smaller brands stay competitive.

Understanding agentic search: Principles and mechanics

An AI agent is far more than a polite chatbot. At its core sits a large language model, often several of them, connected to short-term working memory, optional long-term user memory, and a tool-calling interface. When given a goal, the agent breaks down the task into steps, reasons internally, calls APIs or browser sessions, evaluates the results, and repeats the process until the task is completed. 

Let’s say a user is looking to book a vacation. In a traditional search on a hotel website, the user would search for the location (‘Hawaii’) and the dates they’re looking for (‘July’), and the search function would then crawl the site to find pages or products that match those keywords, without actually knowing if there’s availability in the dates the user is looking for. 

AI-assisted search can be more specific and remember user preferences, such as ‘family-friendly’ or their budgets. It can check product data feeds for the actual availability and prices of the things a user is looking for. So, in this case, it would only return results for hotels that have rooms available.

Agentic search goes further. The user could ask an AI agent, ‘Find a family-friendly hotel for a week in July that costs no more than $500 per night for a family room and book it for me and my family.’ When granted sufficient autonomy, an AI agent can complete all these steps with minimal or no input from the user.

This obviously has huge benefits for e-commerce in enhancing user experiences. But when this streamlined approach to site browsing becomes commonplace, users could end up choosing to avoid sites that still require ‘old-school’ searching and browsing. Let’s take a look at a few other use cases for agentic search.

Revolutionizing customer experiences on websites with agentic search

Because agents think in goals, they collapse the customer journey. A shopper hunting for a sustainably sourced velvet sofa no longer opens twenty tabs and pastes measurements into a spreadsheet. They tell an AI agent their fabric preference, budget, dimensions, and delivery window. The agent combs dozens of catalogues, summarises the top three matches, checks live stock, applies discount codes, and, if authorised, completes checkout. 

Google says early tests of AI Mode cut the average furniture purchase path from eighteen clicks to four.

There are plenty of other applications in travel as well.  Demos have shown that AI agents are capable of purchasing a cross-country flight after just two clarification questions and can even seamlessly reschedule when the user changes the return date mid-conversation. This process typically requires multiple comparison-site visits and repeated data entry. 

Early adopters and examples of agentic search in action

Visa’s new Intelligent Commerce APIs hand over the entire checkout flow to an agent that validates identity, selects the best card, and settles the bill, allowing a voice command to become a completed sale without ever displaying a payment form. Mastercard’s Agent Pay embeds the same magic inside recommendation engines, allowing a styling bot to both suggest a jacket and split the payment in chat, without requiring redirects.

Fintechs are also using agents to manage support queues. Klarna’s AI Assistant now resolves two-thirds of its 2.5 million monthly queries, cutting average response time from eleven minutes to two and doing the work of roughly 700 human agents. 

On Instacart, a shopper can tell an Operator-powered agent, ‘plan an Italian dinner for six’, and watch the cart auto-populate, swap out-of-stock items, and schedule delivery in under a minute. 

Travel is embracing agentic search wholeheartedly. Expedia’s Trip Matching lets travellers DM any Instagram Reel to Expedia and receive a ready-to-book itinerary, including flights, hotels, and activities, right back in the same thread.

And that’s just scratching the surface. As technology evolves and its use becomes more widespread, we can expect to see even more applications that streamline customer experiences.

Challenges and opportunities of agentic search for smaller businesses

Running an AI helper on your website isn’t free. Even if you rent a ready-made language model from a cloud provider, the meter keeps ticking for every word it reads or writes. A recent pricing round-up reveals that once real customers start using the tool, monthly bills range from $500 to $10,000, and that’s before adding storage or security extras. In addition, smooth ‘real-time’ replies need special GPU servers. NVIDIA says its low-latency micro-services cut waiting time for shoppers, but doing so means paying for dedicated hardware that shared web hosts can’t supply.

Building a tailor-made agent from scratch is pricier still. Cost breakdowns put a simple Q&A bot at $25,000–$50,000, a smarter search-and-recommend assistant at $100,000–$250,000, and a full multi-agent planner well above $200,000, all before the monthly usage fees kick in. Off-the-shelf kits like CrewAI drop the headline price, but you still pay the cloud for every prompt and need someone on staff to keep prompts, logs, and data safe.

Money isn’t the only hurdle. Research suggests that 62% of small firms hold back on AI because they don’t feel they understand it well enough, and many lack developers who can wire an agent into checkout or stock systems. However, with 1 in 5 business leaders stating that chatbots are the most valuable AI features for websites, it’s only a matter of time before they embrace agentic AI as the next evolution.

Strategies for smaller businesses with lean budgets

In time, agentic AI is likely to become more accessible for smaller businesses. However, you don’t always have the luxury of waiting for prices to become affordable. There are strategies you can put in place to stay competitive until the day comes when you must invest in agentic AI.

Make your site machine-readable

While you might not be able to host an AI agent on your own site, you can ensure your products can be picked up by other AI agents. That means if someone uses a Google-powered agent to browse and purchase products in your vertical, you can ensure the AI will find your products and share accurate information with the user.

This means you need to make sure your site is machine-readable. Use the correct data schemas, such as product, FAQ, and localBusiness, to ensure the AI can recognize the information it wants to share with users. The same applies to making sure your stock levels and prices are presented with structured data.

Low-code platforms like Shopify, Squarespace, and HubSpot can allow you to identify and enact these opportunities relatively simply and cost-effectively. 

Invest in your brand 

When an agent presents three sofas with near-identical specifications, humans still choose the one with the brand name they trust. Storytelling, community engagement, and encouraging positive user reviews will make your brand stand out and stay top of mind with users.

Agentic search might be right for your business

Agentic search is a wholesale rethink of how people accomplish goals online, as momentous as the leap from desktop to mobile. Smaller brands that can’t afford to host AI agents on their own sites can still find ways to benefit from their power with the right strategies.