AI predictions for 2026: 11 trends digital leaders should know.

Updated July 15, 2026: AI's role in digital experiences has moved faster than most 2025 predictions anticipated. This post has been expanded from four predictions to eleven, incorporating new data on how digital leaders are tracking AI-driven traffic, managing data quality and security risks, and preparing for customer journeys that no longer follow a predictable path. New sections cover emerging priorities including first-party data strategy, cross-functional alignment, consumer trust, and what it actually takes to measure AI's business impact beyond traffic volume.

Many of us discussed AI at the start of 2025, but how many were actually using it to shop, browse for vacation ideas or even get financial advice? Not to mention imagining a world where AI completes actions on our behalf.

Ready or not, this shift is already underway. AI is influencing how customers browse, compare, and buy. It’s starting to recommend products, complete tasks, and, in some rare cases, make purchasing decisions autonomously. The fact is, AI will be connected to almost every digital experience by the end of 2026, but simply investing in AI won’t guarantee success. The brands that win will be the ones who can measure it, secure it and design for it. Below are the top four digital predictions for 2026 — and practical steps digital teams should take now to get ahead.

1. AI-driven sales growth will depend on attribution and AI traffic tracking.

Digital leaders overall expect AI’s contribution to sales to grow significantly in 2026. Our findings show that while AI accounts for less than 10% of overall sales today, by the end of 2026 most leaders expect AI to drive more than a quarter of revenue.

That growth won’t be evenly distributed. It will depend on whether brands can accurately track and attribute AI-driven traffic.

• For the 64% of brands that reported tracking both AI-referred and AI agent traffic, we can expect to see sales growth as they adapt to new patterns in customer and agent behavior.
• But for the 21% not tracking AI traffic, sales will likely stagnate as agents steer shoppers toward better-performing sites or consumers bounce when experiences fall short.

AI-driven sales will also depend on whether sites are designed for both humans and AI agents. With 1 in 5 consumers ready to have an agent shop on their behalf, it's critical to think about how this changes the design of digital products. Winning teams need continuous visibility into AI-referred, human, and agent sessions—not just volumes, but behavior patterns, friction points, and conversion outcomes.

2. Data quality and security will define which brands can scale AI safely.

As AI adoption accelerates, concerns about the quality and security of the data feeding these models are rising. As many have already discovered, garbage in means garbage out and poor results can directly undermine trust in AI-powered decisions. This directly influences how digital teams invest in AI-powered solutions, both for backend systems and customer-facing experiences. Nearly half (45%) of digital leaders say they are concerned about increased risks with AI tied to data quality and security.

What should digital brands be preparing for?

• This shapes how teams build digital experiences and whether they’re acting on complete, trustworthy data. Context is key. If digital teams are only working with half the story, they’ll likely lose to competitors.
• The other piece is how AI is being invested in for customer-facing products. Two in three digital brands added or updated an AI chatbot this year, yet only 35% have guardrails to prevent harmful, biased, or misleading recommendations.

For AI to find real value and success, it needs the right depth and breadth of data that helps teams understand not just why customers behave the way they do, but also how they use AI-powered products and services to shape their experience.

3. A/B tests for loyalty and retention will help navigate new consumer habits.

As AI drives greater volumes of traffic and sales for brands, it will completely disrupt how brands have traditionally established loyalty with customers. Paired with more than half of consumers prioritizing value and practicality, digital brands have greater fears about retention in 2026. In fact, 60% of digital leaders have cited it as a top concern.

Where will brands invest most? Our research shows personalization and engagement tools, especially AI chatbots, will lead the way.

• For those who have invested in or updated an AI chatbot this year, 63% saw increased engagement with consumers and 52% saw higher average order values and conversions rates.
• Consumers are also demanding more personalized experiences with 63% noting they prefer personalized deals over blanket discounts.

This is where a strong testing strategy becomes critical—helping teams identify which recommendations, offers, or content build trust and repeat engagement. As AI makes switching easier, every human interaction must feel tailored and meaningful.

4. AI integrations will spark a new ‘bot partner’ ecosystem, similar to streaming wars.

What’s next for ChatGPT and other AI-powered chatbots? Integrations with digital brands. We’ve already seen it start as Target and others announce partnerships with ChatGPT. In our latest survey, 80% of digital brands said they are considering AI integrations in 2026. What stood out: most won’t rely on a single chatbot provider. Our findings showed 80% will look to ChatGPT, while 63% focus on integrations with Gemini and 21% focus their attention on Claude or Perplexity.

And as new AI chatbots show up, we’ll likely see greater splits in where brands choose to partner or how many partnerships they have. This brings up two important reminders.

• Brands will need deeper segmentation and full-journey visibility, not just traffic volumes from each chatbot, but intent, product interest, and purchase value.
• Teams will also need the ability to monitor every experience, AI-driven or not. A great partnership can flatline if it directs consumers to a 404 error or is unable to complete a purchase on ChatGPT. Understanding how integrations perform will be key to success.

AI presents enormous opportunities, but it also introduces new measurement, security, design, and experimentation challenges. The digital teams that win in 2026 will be the ones that:

• Intentionally track AI behavior
• Invest in data quality and guardrails
• Build for agent and human journeys
• And test personalization with retention, not just short-term conversion, in mind.

In a world where AI touches nearly every digital interaction, clarity and data trust becomes the competitive advantage.

5. AI traffic will require new success metrics.

As AI becomes another source of traffic, traditional website metrics won't tell the full story. Traffic volume alone won't explain whether AI-driven visits are creating meaningful engagement or business value.

Instead, digital teams will need to measure how AI-referred visitors behave compared to other audiences. Do they convert at higher rates? Do they spend more time researching? Do they return after their first visit? Understanding these patterns will help teams determine which AI channels are creating long-term value rather than simply generating visits.

The organizations that adapt their measurement strategies early will have a much clearer understanding of AI's true business impact.

6. Customer journeys will become less predictable.

For years, marketers have optimized around relatively linear customer journeys. A user searched, visited a website, compared products, and eventually made a purchase. AI is already changing that process.

Customers may discover products through an AI assistant, continue their research on a brand's website, ask follow-up questions in another chatbot, and complete a purchase somewhere else entirely. Those journeys won't always follow the same path, making visibility across every interaction increasingly important.

Understanding how these journeys evolve will help digital teams identify new friction points and uncover opportunities that may have gone unnoticed in more traditional analytics.

7. AI will raise expectations for digital experiences.

As AI becomes more capable of delivering immediate answers and personalized recommendations, customer expectations will continue to rise.

People will increasingly expect websites to be fast, intuitive, and relevant from the first interaction. Slow pages, confusing navigation, or broken functionality won't simply create frustration. They may encourage users or AI agents to move on to another option before a purchase is ever considered.

Delivering consistent digital experiences will become just as important as introducing new AI capabilities.

8. First-party data will become even more valuable.

As organizations invest more heavily in AI, the value of reliable first-party data will continue to grow.

Customer interactions, behavioral patterns, and product usage data provide the context that AI models need to generate more relevant recommendations and insights. The more accurate and complete that data is, the more confidently organizations can personalize experiences and make business decisions.

For many brands, improving data quality won't just support AI initiatives. It will become a competitive advantage.

9. Cross-functional collaboration will become a competitive advantage.

AI is no longer just an engineering or innovation initiative. Successfully adopting AI requires product, marketing, analytics, customer experience, and technology teams to work toward the same goals.

When these teams share data and collaborate around customer insights, they're better positioned to identify opportunities, respond to issues quickly, and create more consistent digital experiences.

Organizations that break down data silos will be better equipped to adapt as AI continues reshaping customer behavior.

10. Consumer trust will become a key differentiator.

As AI takes on a larger role in digital experiences, trust will become just as important as innovation.

Customers want AI to provide useful recommendations and simplify their experience, but they also expect transparency and reliable outcomes. Inaccurate responses, inconsistent recommendations, or poor digital experiences can quickly reduce confidence in both the AI and the brand behind it.

Organizations that prioritize accuracy, reliability, and customer trust will be in a stronger position as AI adoption continues to accelerate.

11. Preparing for AI starts with understanding customer behavior.

Many organizations feel pressure to move quickly with AI, but successful adoption starts with understanding the customer experience.

Before introducing new AI capabilities, digital teams need a clear view of how customers already interact with their products, where friction exists, and which experiences have the greatest business impact. Without that foundation, it becomes much harder to evaluate whether AI is actually improving outcomes.

Organizations that combine AI innovation with a strong understanding of customer behavior will be better positioned to deliver experiences that create long-term value.