AI Search Behaviour: How Can Businesses Adapt?

AI is reshaping not just how companies work, but also how potential customers find and choose a product or service. The shift is most visible in the buyer journey and search journey, from the first bit of research to the final choice of vendor.

Before AI search, that journey usually began with a traditional search engine like Google or Bing. People would type in a few keywords, click through several pages of results, and piece together their own conclusions.

Now, they skip all that and put their question straight to an AI assistant. Instead of a list of links, they get a summary, complete with reasoning, comparisons, and recommendations.

So what does this mean for businesses? With AI offering a shortcut for early research, a vendor shortlist can take shape before a potential customer has visited a single website. Ranking on the first page of Google is no longer enough. Businesses also need to be featured, cited, and recommended in AI-generated answers.

This article explains what AI search behaviour is, how it differs from traditional search behaviour, and what businesses can do to adapt and stay visible to users. So, let’s get into it!

About the Search and Buyer Journey

A search journey is the series of steps a user takes to find information, from asking a question and comparing sources to finally making a choice.

It rarely ends after a single search. Users might change their keywords, shift direction, or return to the same page again and again, depending on how complex their needs are and how many options are on the table.

The buyer journey looks at the same process from a purchasing perspective. It is usually split into three stages:

• Awareness: The user realises they have a problem or need.
• Consideration: The user compares different options.
• Decision: The user makes a choice and completes the purchase.

Remember, neither journey is linear. Potential customers can jump between stages, circle back to an earlier one, or gather information from several channels at once. We can say the search journey is how users search, while the buyer journey is why they search and how far along they are towards a purchase.

How Is AI Search Changing the Buyer Journey?

If you run a business, there’s no need to worry, as AI isn’t going to erase the buyer journey. The awareness, consideration, and decision stages are all still there. What has changed is where each stage plays out, and who helps shape the shortlist before a potential customer ever touches a website.

The most fundamental change is at the starting point. Not long ago, almost every research journey began with a search engine. Now, some users prefer to ask an AI directly. A Similarweb study in the United States (January 2026) found that 35% of consumers begin product discovery with AI, compared with just 13.6% who start with a search engine.

Indonesia is seeing a similar shift. A Jurnal Globresco survey from March 2026 found that 74.6% of respondents had used AI to research products. Research by Macromill South East Asia, covering 4,114 respondents in Indonesia, backs this up, showing that AI is used most in the pre-purchase stage, for comparing products, asking for recommendations that fit their needs, and checking a brand’s credibility.

More importantly, AI is no longer just a tool for finding information. It is also influencing decisions. In a survey by Jurnal Globresco, 52.3% of Indonesian respondents said they were swayed by brands mentioned by AI, and 79.8% felt AI sped up their decision-making.

In other words, AI now plays a major role in the consideration stage and also affects the outcome of the decision stage. At the consideration stage, it summarises, compares, and recommends all in a single answer, so buyers no longer need to open websites one by one.

Read also: Content Structure for AI Search Optimization, Try Now!

Traditional vs AI Search Behaviour: What’s the Difference?

AI is changing not only the buyer journey but the search journey too. So, how is AI changing the way we search? Before AI was built into search, the journey started with keywords that translated a user’s need. Now, in the era of AI search, buyers arrive with the full context of their problem, written in everyday language and often at considerable length.

So what is searching in AI? AI search is when users look for information by asking an AI assistant such as ChatGPT or Gemini directly. Instead of a list of links to open one by one, they receive an answer summarised from multiple sources.

This difference at the starting point carries through the rest of the search process. Here are the five key differences:

1. How Questions Are Asked

On a search engine, users tend to type short keywords like “corporate video production services Jakarta.” With AI search, buyers can spell out the type of project, the size of their company, the deadline, and even the experience they expect from a vendor.

As a result, the answers feel more personalised, because the shortlisted candidates match the buyer’s specific situation.

2. How Candidates Are Found

With a search engine, building the candidate list falls to the buyer. They open the top results one by one, assess each website, and note down the vendors that look worthwhile. Google offers the options, and the buyer does the choosing.

With AI, the order is reversed. The answer already includes several vendor names along with the reasons behind them. In other words, AI makes the recommendation, so the shortlist is formed before a single website is opened.

3. How Users Interact

Traditional search is usually a series of standalone queries. To narrow down their options, buyers pick new keywords and start the search over from scratch.

AI search, on the other hand, works as an ongoing conversation. Once they have a few vendor names, buyers can immediately ask which one has the most experience in a particular area, then request a comparison of price ranges, without having to repeat the context.

4. What Determines Who Shows Up

In traditional search, rankings are decided by page relevance and links from other sites (backlinks), so vendors compete through website optimization. In AI search, recommendations are shaped by how often and how consistently a brand is mentioned across different sources, such as media outlets, directories, review sites, and industry associations.

5. Where Potential Clients Are in Their Journey on Arrival

Visitors from search engines usually arrive with limited knowledge, so the website has to answer every question and win them over from zero. Visitors who come after researching with AI, however, are generally better informed and ready to move into the decision stage.

Read also: What Is AI Brand Authority? Here’s How to Measure and Build It!

So, Is AI Search Behaviour Bad for Business?

Not at all. Businesses can still be found by potential customers as long as they show up in AI answers. AI search doesn’t remove visibility, it just changes its form. 

In traditional search, visibility means rankings and clicks. In AI search, visibility comes in the form of AI mentions and AI citations. Both put a business in front of potential buyers, especially while the vendor shortlist is being formed.

In both systems, visibility doesn’t come automatically. However, the way to build it in AI search differs a little from traditional search. It’s not only about page rankings, but also about how clearly, credibly, and consistently a brand is talked about, both on its own website and on third-party sources.

That’s why every business needs a strategic, tailored approach to optimization if it wants to make the most of its AI visibility.

How Businesses Can Adapt and Make the Most of AI Search

As AI search becomes the norm, businesses must adapt or risk falling behind and losing visibility. cmlabs offers services to help optimize your content and website, from content structure to technical aspects such as entity optimization, citation gap analysis, and schema optimization.

With AI search optimization services by cmlabs, you’ll have an expert partner to help you adapt to this shift by building a practical and measurable strategy as customer search behaviour changes in the age of AI.

Here are several ways cmlabs can help you make the most of AI search for your business:

1. Run an AI Visibility Audit

Before any optimization begins, find out where your business stands today: which questions bring up your brand in AI answers, which competitors appear when you’re not mentioned, and which of your content gets cited.

The results can serve as a baseline for evaluating your optimization efforts over time. There’s no need to audit manually, as you can use FREE AI Visibility Audit by cmlabs. You’ll receive your results within 3–5 working days, completely free and with no contract.

2. Structure Content in an Answer-First Format

To make your content perform well in AI search, phrase headings and subheadings as questions, then open each section with a short, direct answer. The rest of the explanation can go into comparison tables and bullet lists, so every part is easy for AI to pick up and cite. Use Q&A blocks to cover any follow-up questions the main paragraph doesn’t answer.

3. Build Topical Authority with Topic Clusters

Create one main page that covers the topic at a high level, then use supporting pages to go into detail on things like definitions, comparisons, and how to choose. Link them all together so that AI recognises your topical authority.

4. Optimize Schema Markup and Technical Access

Add relevant schema markup (such as FAQ, Article, and Organization) so machines can easily understand the context of your content, and make sure AI crawlers aren’t blocked from your website.

Read also: AI Search Optimization vs Traditional SEO: Which Matters More?

5. Strengthen Your Entity and Credibility Signals

To strengthen your entity, make sure your brand name, service descriptions, and author profiles are consistent across all platforms. Also show authors’ credentials and a content update history.

6. Provide the Evidence AI Looks For

Publish data-driven case studies, original research or benchmarks, testimonials, and clear service information. This kind of evidence is what helps AI recommend your business to users.

7. Earn Mentions Beyond Your Own Website and Close the Citation Gap

Build mentions through industry media, review sites, directories, and associations. Then check which sites AI refers to when it mentions your competitors, and aim to have your business featured on those platforms too, so you can close the citation gap.

8. Monitor and Evaluate Regularly

Track how often AI mentions and cites your brand, and how that contributes to conversions, against the baseline from your initial audit, rather than looking only at clicks from search engines.

Optimize your business now, because every time your business is absent from an AI answer, another brand gets the chance to be mentioned and considered by customers, and the longer you wait, the more often those brands are named.

The cmlabs team is ready to help you understand where your business stands in AI search today and choose the optimization strategy that best fits your needs. Contact us now to learn more about AI search optimization services by cmlabs.