Retail is entering a new phase of digital maturity, one where artificial intelligence isn’t just a tool to optimize processes, but the engine behind new business models. From retail media networks to concept creation within R&D, AI is redefining how brands create value, engage consumers, and scale innovation. In 2025, we saw retailers moving from experimentation to operationalization. We see this trend accelerating in 2026, turning AI from a promising capability into a competitive advantage.
New Retail Models for a Data-Driven Future
For years, retailers have relied on AI to improve forecasting, personalization and inventory management. However, the next wave is about reinvention. For example, retail media is rapidly becoming one of the fastest-growing profit engines, with U.S. ad spend projected to exceed $100 billion by 2027. AI makes these networks smarter and more profitable, both for the retailer and the advertiser, matching relevant ads with intent signals across digital and in-store touchpoints.
Meanwhile, subscription and service-based models are reshaping customer relationships. Predictive analytics helps brands anticipate when a shopper needs a refill, upgrade or exclusive offer, turning transactions into recurring engagement. Some brands are also experimenting with digital consumer twins — i.e., anonymized models that simulate shopper behavior to test new products or promotions before launch. These innovations reflect a broader trend: using AI not just to optimize the value chain, but to extend it.
From Isolated Use Cases to End-to-End Optimization
Historically, AI in retail was deployed in silos, one model for pricing, another for logistics, and yet another for marketing or demand forecasting. The future is integrated. Leading retailers are connecting demand forecasting with supply chain agility, dynamic assortment planning, and sustainability goals in order to optimize value across the entire chain of core retail processes.
Achieving this level of integration requires a modern data architecture: unified, secure and built for scale. Many retailers are struggling to prioritize investment in this foundational capability, wrestling with legacy systems and on-premises solutions, as well as having to compete with a crowded investment agenda featuring the demands of store refurbishment, supply chain improvements and investing in price competitiveness.
AI Governance and the Rise of the Chief AI Officer
Given the expense of building a solid data platform and the vast potential it offers forward-thinking retailers, data and AI governance has become a board-level priority. Ethical frameworks, model explainability, and data lineage are now business imperatives. According to a report by Gartner, fragmented AI regulation will drive $5 billion in compliance investment by 2027. To facilitate and oversee this crucial component of AI adoption, many technology leaders are appointing chief AI officers to manage regulatory and business requirements, as well as potential AI risks outside of security.
Reskilling the Retail Workforce
AI transformation is as much about people as technology. Most retailers anticipate large-scale reskilling in the next 18 months. New roles, from prompt engineers to AI ethics specialists, are emerging faster than talent pipelines can supply them. In response, leading companies are embedding AI enablement programs into their overall digital strategy, ensuring all employees have access to new tools and learn how to collaborate effectively with intelligent systems.
This human-centric approach is vital. Without trust and participation from associates, merchandisers and marketers driving the business change agenda, even the most advanced AI tools will struggle to deliver value.
What’s Next: Responsible and Creative AI
The next retail frontier will balance creativity and responsibility. Generative AI already enables dynamic content creation, automated campaign testing and digital product design. However, as consumers grow more aware of responsible AI, transparency and fairness will be key differentiators. Retailers that embed ethics and explainability into every stage of their AI lifecycle will earn long-term loyalty.
Looking toward 2026 and beyond, the retailers that thrive will think beyond automation, using AI to invent new forms of customer value, guided by strong governance and empowered teams. The ones that succeed won’t just use AI to predict the future, they’ll use it to create it.
Martin Ryan is vice president of retail, Europe, EPAM Systems, Inc., a digital transformation services and product engineering company.
