TCS Global retail outlook 2026: Why retailers are falling behind on AI

Artificial intelligence has become central to how retailers envision the future of competitiveness, agility, and customer experience. Yet, despite strong executive conviction, the journey from experimentation to enterprise-wide intelligence remains slow. A new study by Tata Consultancy Services, a global leader in IT services, consulting, and business solutions, highlights a striking gap between AI ambition and execution across the global retail sector.

The TCS Global Retail Outlook 2026 study finds that while AI is ranked among the most critical enablers for retailers, most organisations have made limited progress in deploying AI at scale. The research suggests that retail’s AI adoption remains largely surface-level, with advanced capabilities such as agentic and autonomous AI still out of reach for the majority.

AI in Retail: High Priority, Low Maturity

The study reveals that most retailers continue to rely on basic AI use cases rather than embedding intelligence across the value chain. While AI is widely acknowledged as transformative, its current application is largely confined to isolated customer engagement tools.

More than half of retailers identify chatbots and virtual assistants as their primary AI initiative today. This indicates that AI adoption remains narrowly focused, rather than integrated into core decision-making, supply chain orchestration, pricing, or merchandising strategies.

Only a small proportion of retailers report using AI for autonomous decision-making, underscoring how far the industry still has to go before intelligence becomes self-directed, adaptive, and real time.

Agentic AI: A Readiness Gap Emerges

One of the most striking findings from the study is the lack of preparedness for agentic AI. The vast majority of retailers report that they have neither implemented nor planned for multi-agent AI systems, signaling a significant readiness gap at a time when the industry is moving toward autonomous, self-learning operations.

This lack of readiness is critical because agentic AI represents the shift from insight generation to action execution. Without it, retailers remain dependent on manual interventions, slowing their ability to respond to market shifts, competitive movements, and customer expectations.

Decision Intelligence Rises as a 2026 Imperative

Despite current limitations, retailers clearly recognize where AI must go next. Following cost optimization, AI-powered capabilities are ranked among the most essential enablers for 2026. The ability to sense market changes in real time and respond dynamically to competitor actions ranks among the top strategic priorities.

Adaptive, AI-driven decision-making capabilities are ranked near the top of retailers’ future capability lists, reflecting a growing understanding that conventional analytics and static dashboards are no longer sufficient in an experience-led, fast-moving retail environment.

Workforce Skills: The Silent Constraint

Beyond technology, the study highlights workforce readiness as one of the most significant barriers to progress. Skills gaps emerge as a challenge second only to financial pressures, pointing to a structural issue that technology investments alone cannot solve.

Only a minority of retailers see digital literacy programs as a meaningful lever for organisational transformation and talent upskilling. This suggests that while AI investment is rising, parallel investments in people, operating models, and culture are lagging behind.

Untapped Intelligence in Loyalty Data

The research also exposes a major blind spot in how retailers use customer data. Despite widespread loyalty programs, fewer than half of retailers are able to leverage loyalty insights effectively for pricing, promotions, channel strategy, or store experience design.

This underutilization represents a missed opportunity to convert customer data into enterprise intelligence. In a market where personalisation and relevance are key differentiators, failing to activate loyalty data limits both marketing ROI and strategic decision-making.

Supply Chain Resilience Still a Work in Progress

AI-powered demand sensing is increasingly recognised as critical for supply chain resilience, yet adoption remains uneven. Less than half of retailers report deploying AI-driven demand sensing, despite ongoing volatility in supply chains and consumer demand patterns.

This gap reinforces the broader theme of the study: while awareness of AI’s value is high, operationalising it across complex retail ecosystems remains a challenge.

From Experiments to Enterprise Intelligence

According to Krishnan Ramanujan, the opportunity ahead lies in moving beyond isolated AI initiatives.

“Retailers today are united in their belief that AI will define the next era of competitiveness, yet most have only scratched the surface of its potential. Our Global Retail Outlook reveals that the true opportunity lies in shifting from isolated experiments to pervasive intelligence embedded across the value chain.”

He adds that retailers who succeed in this transition will become more perceptive enterprises, capable of learning, adapting, and responding in real time.

The Rise of Perceptive Retail

The findings align with TCS’s vision for the future of retail, described as Perceptive Retail. This approach integrates AI, machine learning, and multi-agent systems to help retailers interpret signals, adapt operations dynamically, and orchestrate decisions across the enterprise.

The study forms part of TCS’s broader effort to make AI real at the enterprise level, moving beyond pilots toward scalable, outcome-driven implementations.

Cheenttan Voraa notes that the industry stands at a defining crossroads.

“Leaders recognise AI as an essential technology to stay ahead in the next era of competitiveness, yet most organisations remain early in their journey toward true enterprise intelligence. Advancing from siloed use cases to connected, perceptive systems will require bold investments, not only in technology but in AI-savvy talent, along with improved processes and operating models.”

Conclusion: Retail’s AI Moment Demands a Paradigm Shift

The TCS Global Retail Outlook 2026 makes one thing clear: retail is no longer debating whether AI matters, but how quickly it can be operationalised at scale. As the industry moves toward intelligent, experience-led models, the gap between experimentation and execution is becoming increasingly visible.

Retailers that fail to progress beyond basic AI use cases risk falling behind more perceptive competitors, those capable of sensing change, learning continuously, and acting autonomously. Bridging this gap will require not just technology investment, but a fundamental rethink of skills, processes, and enterprise intelligence.

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