A new TCS Global Retail Outlook 2026 study finds that while retailers overwhelmingly view AI as a key driver of future competitiveness, most remain stuck at a superficial stage of adoption. Executives are investing in chatbots and virtual assistants, but lag significantly in deploying advanced, agentic AI systems that can drive real-time, autonomous decisions across the value chain.
Retailers Still Stuck in Basic AI Use Cases
According to the TCS study, 51% of retailers say their primary AI initiative today is limited to chatbots and virtual assistants, indicating that AI is still being applied in narrow, customer-facing scenarios rather than embedded deeply into operations. Only 24% are currently using AI for autonomous decision-making, such as dynamic pricing, real-time assortment optimisation, or adaptive supply chain decisions.
The gap is stark when it comes to next-generation, multi-agent or agentic AI systems: 85% of retailers report that they have not yet started implementing such systems, and nearly half have no plans to do so. This suggests that large-scale, enterprise-wide AI intelligence remains more aspiration than reality.
Skills, Budget and Data Use Hold Back Transformation
The report highlights that, after financial pressures, workforce skills gaps are the biggest barrier to progress. Retailers know that AI will define the next era of competitiveness, but most lack sufficient AI-savvy talent and digital literacy across the organisation to operationalise it.
Only 33% of retailers see structured digital literacy programmes as a primary lever for transformation and upskilling, underscoring a misalignment between ambition and capability building. At the same time, retailers are underutilising the rich data they already possess: just 37% use loyalty insights to shape channel or in-store experience strategies, and only 45% apply them consistently to pricing and promotions. This leaves significant value untapped in areas like personalised marketing, margin optimisation and product planning.
Perceptive Retail: From Isolated Experiments to Pervasive Intelligence
TCS frames the future state as “Perceptive Retail” — an operating model where AI, machine learning and multi-agent systems are integrated across the value chain to interpret signals, adapt operations in real time, and orchestrate decisions end‑to‑end. The study argues that today’s fragmented pilots and point solutions must give way to connected, context-aware systems that continuously learn from market shifts, customer behaviour and operational data.
Executives already rank AI‑powered decision-making, faster time‑to‑market, and automated workflows above traditional business intelligence tools in terms of impact potential over the next one to two years. However, closing the gap between intent and execution will require bold investments not only in technology platforms, but also in skills, operating models and governance.
Retail at a Defining Crossroads
The findings portray a sector at a strategic crossroads. On one side, leaders clearly recognise that AI is essential to sensing market changes in real time, responding to competitors, and delivering differentiated customer experiences. On the other, most organisations remain early in their journey toward true enterprise intelligence, with AI confined to siloed use cases and basic automation.
TCS positions itself to help retailers move from experimentation to pervasive, outcome-driven AI, but the broader message is clear: retailers that fail to invest in talent, data utilisation and multi-agent capabilities risk falling behind as the market shifts toward intelligent, experience-led retail. Those that successfully make the leap stand to become perceptive enterprises, capable of learning and adapting in real time.
