Ecommerce Trends: 3 AI-related problems retailers are trying solve

As artificial intelligence (AI)-powered solutions bring new opportunities to some of the largest online retailers in the world, AI-related problems for retailers have created their own markets for help. Some of these issues stem from adoption by third-party actors with bad intentions — but others can result from unsuccessful deployments or poor strategy.

But which problems are causing the biggest headaches for online merchants?

In 2026, studies have shown that even as AI enables retailers to scale aspects like content, personalization and other elements of customer experience, they are noticing challenges that emerge as a result. Those issues span security, trust and customer experience.



AI-related security and fraud problems for retailers

In June, Cisco published new survey results based on answers from 3,400 senior technology and networking leaders, 292 of whom worked in retail. In those results, Cisco found that 68% of retail leaders believed AI adoption in their companies had led to new blind spots for security. Their organizations faced pressure. In fact, 44% said AI upgrades were happening to stay ahead of competitors. Nevertheless, 78% of retail leaders participating said AI made attack surfaces for their companies bigger within the last year.

And that situation has resulted regardless of the new AI tools that cybercriminals have adopted in the meantime as large language models (LLMs) have improved. Visa noted rising interest in AI tools for malicious purposes in a year-end report from 2025. That same report documented a 25% increase in malicious bot-initiated transactions worldwide.

Still, AI has become an answer in retail as well. 73.7% of merchants who experienced friendly fraud — where cardholders dispute legitimate transactions — within the past three years saw their problems worsening, according to a June report published by Chargebacks911. In many of those cases (26.7%), merchants also said they were leveraging AI tools to combat that rise. Another 37% had plans to use AI-powered anti-fraud tools in the future.

Preserving consumer trust as AI-generated content proliferates

A majority of U.S. shoppers (86%) trust the product reviews they read online, according to January 2026 findings published by the marketing platform Omnisend. In fact, 33% of those surveyed said they trusted online product reviews more than they did two years earlier. But that trend is on a collision course with another development. 86% of those surveyed indicated that they had concerns about AI-generated product recommendations they saw.

When it comes to seeing recommendations provided directly from AI platforms or — worse — in places where AI-produced writing is used to imitate reviews from human shoppers, skepticism is strong. So what can retailers do? The same report noted that shoppers were more inclined to actively use and rely on AI recommendations when steps such as ensuring data privacy or clearly explaining why products were being recommended were taken.



Ensuring customer experience quality

At a fundamental level, AI tools face a problem that all ecommerce technologies run into: working in predictable, useful ways. As retailers turn to AI solutions for everything from customer service to payments and checkout, the results they see can vary widely, based on the context, data and guardrails they implement to determine how AI systems operate.

Researchers affiliated with Massachusetts Institute of Technology (MIT) and the University of Cambridge found in 2025 that growing autonomy for AI systems was outpacing an increase in governance. In the meantime, the researchers saw that a lack of disclosure in some enterprise use cases resulted in AI systems failing to identify themselves accurately to third parties. That failure, in turn, can lead to breaches of trust.

Retailers are already conscious of these interactions. And their concerns have manifested in new concerns over how third-party AI agents interact with their catalog data. One of the most prominent examples of this anxiety could be seen in Shopify’s altered approach to ChatGPT in 2026, when it opted to keep merchant data under its own control and available through ChatGPT in the form of apps instead of opening up directly for ChatGPT to funnel everything through a unified checkout experience.

All of the above examples show that retailers are alert and adapting. Importantly, they also underscore that as technology solutions change, so too does the nature of the problems that need to be addressed.

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