AI in buyer behavior in 2026: Is it here to stay?

The buyer journey isn’t what it used to be. Remember the days when potential customers discovered brands through TV ads, in-store promotions, or a friend’s recommendation? Well, those days are long gone.

These days, way more tech-savvy methods win, and AI leads the way. In recent years, AI has proven itself as not just another tool in the marketing tech stack, but a whole new approach to marketing operations that is fundamentally changing how brands attract, engage, and convert their audiences. 

In this article, we’ll review the role of AI at each stage of the buyer journey, assess its key impact areas, and explore practical use cases you can apply to your marketing efforts.

The traditional buyer journey vs. the AI-enhanced buyer journey

Looking back at the traditional buyer journey, it was linear, static, and manual. To move prospects through the funnel, businesses relied on broad content or standard demos. Everyone received the same materials, regardless of their role, buyer intent, or industry. Personalization, if it existed at all, required heavy lifting.

AI fundamentally reshapes this experience. For example, buyers no longer have to search for information. Instead, they are now guided by intelligent systems anticipating their preferences and needs. Even post-sale, AI can ensure users stay engaged. As a result, there’s a smarter, faster buyer journey built around the individual, not the pipeline.

But is all of this a fantasy or a far-fetched future — or are these solutions already real and working today?

AI in the awareness stage: Reaching the right audience

At the top of the funnel, AI can help marketers cut through the noise and reach the right people in a faster, smarter way. 

Now, with the help of AI, brands can connect with their audience from the very first touchpoint. This results in a stronger brand connection — and thus, higher conversion potential.

We suggest trying out these top 3 use cases:

• Predictive ads

Use AI to analyze customer data, thus predicting who’s most likely to convert. Focus on past behavior, demographics, time on site, and other relevant factors.

Tools: Meta Advantage+, Google Performance Max, Madgicx

• Personalized content recommendations

Leverage AI to adjust your content or product suggestions based on user preferences or browsing history.

Tools: Adobe Target, Optimizely, OneSpot

• AI-powered search

Intelligent search identifies intent, learns from user input, and analyzes the context. This way, you can empower users to find exactly what they need, even before they know it.

Tools: Algolia, Klevu, Elastic Enterprise Search

AI in the consideration stage: Building trust and nurturing leads

Once a prospect is aware of your brand or product, the real challenge lies in turning interest into intent. AI doesn’t just support this stage — it supercharges it. Let’s review exactly how AI can achieve this and what specific results it can deliver at this stage.

Check out these 3 handy application areas:

• AI chatbots

Allow conversational AI to respond to buyers' product-related inquiries and provide relevant product recommendations.

Tools: Intercom, Drift, Tidio, HubSpot Chatbot Builder

• Lead scoring algorithms

Streamline user analysis and prioritization of sales-ready leads, including automated detection of low-intent prospects.

Tools: HubSpot, Salesforce Einstein, Freshsales

• Behavioral nurturing campaigns

Trigger AI-led nurture flows based on how users interact with your content or site. Hence, no more second-guessing the right message, format, and timing for each prospect.

Tools: HubSpot, Iterable, Marketo Engage (Adobe Sensei)

AI in the decision stage: Turning engagement into conversions

We all know it well: at this stage, even small frictions can potentially lead to drop-offs. This is where AI helps seal the deal. So, how and where can it help? Let’s explore.

• Personalized product recommendations

Use AI to identify when users are deciding what to buy — based on browsing history, purchase behavior, real-time context, or other signals.

Tools: Dynamic Yield, Adobe Target, Salesforce Commerce Cloud

• Dynamic pricing engines

Implement AI models that adjust prices in real time based on multiple factors: demand, location, user behavior, inventory, competitor activity, you name it. 

Tools: Prisync, Omnia Retail, PROS Smart Price Optimization

• Optimized user experience

Use AI to adapt on-site experiences in real time, including such areas as layout changes, smart CTAs, checkout flow refinement, and other.

Tools: Monetate, Intellimize, Optimizely

How to start using AI in your buyer journey: Considerations and best practices

While AI adoption in marketing is still a new and evolving field, some core practices are likely to remain relevant for years to come. Therefore, if you’re a novice in exploring AI-powered marketing, they’re the best place to begin.

Tip #1. Identify high-impact areas first

Look for stages in your funnel where there are gaps in personalization, automation, or data management. Those might be where your content feels too generic to attract the right audience or where leads drop off.

Tip #2. Choose the right tools

Start with tools that integrate easily with your CRM or ad platforms. For example, HubSpot offers built-in, easy-to-use AI features across its marketing, sales, and service hubs. They include predictive lead scoring, AI-driven email personalization, chatbot builders, and more.

Tip #3. Focus on data quality

AI is only as good as the data you feed it. Therefore, ensure you clean your CRM, segment leads, and continuously improve model accuracy.

Tip #4. Combine AI with human touch

Remember this: AI can scale personalized experiences, but the human touch still matters. Hence, it’s best to use AI for surfacing insights or automating routine tasks, but not to give it full control over your campaigns.

Pick and go: Campaign checklist for AI-powered lead nurturing workflow

Conclusion

Ready or not, AI is already here. As we've covered in this article, every stage of the buyer journey is being reshaped as new AI capabilities continue to emerge. And, considering nearly 70% of mid-sized enterprises currently allocate funding for AI-powered software directly from their central IT budgets, there's undoubtedly much more to come. 

Considering marketing is in the top 5 domains with the highest number of listed apps, the field is dynamic, ever-evolving, and might even feel disruptive at times. However, you don’t have to fear: there’s no need to overhaul your entire marketing operation to get started. Start small, measure impact, and scale what works.