Retail’s 2026 AI Strategy Demands Human-Centered, Collaborative Tools and Trust-Building Transparency

Retail is no stranger to artificial intelligence and its powerful capabilities. Many in the industry already use AI in some capacity, with new research indicating 87 percent of retailers have adopted AI in at least one area of their business. The next phase of growth will likely focus on personalization, as 86 percent of all retailers want to enhance their customers’ experiences with generative AI.

Interest in AI shows no signs of slowing down in 2026; however, the opposite may be true of the way it’s developed and implemented. And that’s a good thing. The initial rush to adopt AI is evolving into a complex reality that requires careful, thoughtful strategy design and implementation. Simply having AI isn't enough.

To meet rising customer expectations and differentiate themselves in the new year, retailers must take their time with more specifically tailored, human-centered approaches. With this shift, AI’s role in retail — historically focused on efficiency enhancements — has real potential to bridge the gap between technological hype and genuine customer value.

Prioritize Accuracy and Customized Experiences to Bridge the AI Trust Gap

Scaling AI in retail is an intricate task, often fraught with technical, ethical and organizational challenges, such as the "AI trust paradox." Customers want the benefits of personalization but tend to be suspicious of the data collection required to deliver it. Their understandable concerns include data privacy issues, a lack of transparency in how AI models work, and a general disconnect between the experiences promised and those delivered. The solution isn’t just deploying more AI, but building customized, integratable tools that are ethically governed and designed for human collaboration.

The cornerstone of this initiative, creating a unified data environment, involves consolidating all customer data (purchase history, browsing behavior, support tickets and loyalty interactions) into a single, comprehensive profile. This data foundation informs AI and enables it to generate hyperpersonalized, accurate responses that cultivate consumer trust and prevent the kind of incidents that undermine it.

AI hallucinations (i.e., outputs that appear to be correct but are not) can erode public confidence in companies of all sizes and reputations. When Google launched its first large language model (LLM), the system mistakenly claimed during a promotional video and live demo that the James Webb Space Telescope captured the first photo of an exoplanet. What appeared to be a minor error cost Alphabet, Google’s parent company, an estimated $100 billion in market value as shares dropped 8 percent to 9 percent following the demo. No organization is immune to the deterioration of trust that can occur when technology fails to perform as expected.

Retailers That Treat AI as a Collaborative Partner Enhance Customer Trust and Experiences

Brand collaborations are common in retail, often used as a tactic to build equity and reach new audiences. The industry’s approach to AI should follow the same philosophy, with technology designed to enhance human performance and elevate experiences that foster lasting loyalty. Using generative AI co-pilots, for example, can provide sales and customer service teams with helpful real-time customer context so they can offer more effective support. Conversely, when support is provided in the form of chatbots or recommendation engines, transparency is key. Customers should always know when AI is assisting them to build trust and demonstrate ethical leadership.

A few retailers are already putting these principles into practice. Walmart’s app includes a generative AI shopping assistant that can create a cross-category shopping list based on proprietary data and customer preferences. Skincare brand Olay uses AI to replicate the expertise of a professional consultant, allowing consumers to upload a selfie, which is analyzed for signs of aging. Using the results and a short questionnaire, the tool provides a personalized diagnostic report and recommends an Olay-specific skincare regimen.

Retailers have a lot to consider when formulating their plans and strategies for 2026. For the foreseeable future, though, brands should prioritize efforts to bridge customers’ persistent AI trust gap. The technology’s ability to deliver personalized, high-quality experiences depends on customers seeing that it serves their best interests. Brands that boost credibility by clearly demonstrating respect for privacy and transparency will unlock AI’s full potential to benefit both businesses and consumers.

Emily Clark is the head of retail at Further, a leading data, cloud, and AI company focused on helping companies turn raw data into the right decisions.