In 2026, consumers will remain price sensitive, but intolerant of friction

Retailers that compete on provable outcomes will outperform those who focus on headline promotions and offers, predicts Christopher Bartlett, CEO at Tapestry.  

Shoppers are increasingly unforgiving of out-of-stocks, inconsistent promotions, substitutions and a mismatch between a brand’s promise and the on-shelf reality, he explains.

“The retailers that win will be those that reduce uncertainty – through better availability, clearer execution, and fewer surprises – not those shouting the loudest about price,” Bartlett told Inside Retail.

“As loyalty becomes conditional, earned and tested weekly, consumers will not be asking just: ‘Is this cheap?’ They’ll ask: ‘Will this work – and can I trust it?’.” 

Bartlett highlights four other key trends for retailers during the year ahead: 

Retail technology adoption will be driven less by the depth of features and more by distribution into core workflows. 

Tools that integrate into daily execution will scale; standalone analytics will stall, says Bartlett. “The technologies that will scale fastest won’t be flashy; they’ll be practical, and embedded into how retail teams already work.” 

Three stand out:

AI for inventory visibility and exception management: “AI is moving beyond dashboards and ad-hoc analysis into day-to-day operational roles. We’re seeing rapid adoption of intelligent inventory assistants, as well as weekly department and store-level workflow recommendations that prioritise what needs attention now. In practice, AI begins to replace the traditional analyst role – not by generating more insight, but by synthesising signals into clear, actionable focus areas.” 

Direct data monetisation at the point of sale: More retailers are choosing to monetise their data directly with suppliers, using POS systems as the distribution layer. Rather than aggregating and reselling data through intermediaries, retailers are increasingly enabling permissioned, direct access to verified sales and performance signals, creating new revenue streams while retaining ownership and control.

Data-driven collaboration becomes essential as AI embeds: As AI systems embed deeper into retail operations, the limiting factor becomes operationalisation, not insight. “The next wave of adoption focuses on tools that move teams from insight to action to collaboration – especially between retailers, wholesalers and suppliers.” 

The retailers who succeed with agentic AI will be those who invest first in clean, verified operational signals – not those chasing surface-level personalisation.

Agentic AI will move retail from optimisation to orchestration, but it won’t scale everywhere at once. “The bottleneck is trust. AI agents can recommend, predict and transact – but only when identity, payments, returns and dispute resolution are reliable. Where those guardrails are weak, adoption stalls.

Operationally, this means pricing, fulfilment and service decisions will be coordinated using AI, less time spent on analysing dashboards, and more time acting on prioritised exceptions.

Growth will come from retailers that make execution measurable with data and AI – not those adding more reporting layers.

In-store innovation in 2026 won’t be about novelty. It will be about execution, predicts Bartlett. 

“AI will increasingly reach the shop floor through mobile analytics and operational tools, giving department and store managers instant access to performance signals – and the ability to act across a store or group in real time, directly from their phones,” he explains.

The winning innovations will focus on two shifts, he says: Technology that links the plan to action and verifies outcomes, and using AI to prioritise issues and confirm whether changes worked and store-specific localisation at scale, with range, space and activity tuned to the realities of each store rather than rolled out uniformly.

“When execution becomes visible and provable, debates disappear. Teams stop arguing about what happened and start improving what happens next.”

Supply chains that close feedback loops fastest through direct data sharing will turn inventory velocity into a sustained competitive advantage.

Predictive analytics has long promised better supply chains – but in practice, its impact has been limited by one thing: Trust in the inputs, he advocates.

“This year, the biggest gains won’t come from more sophisticated forecasting models. They’ll come from direct, permissioned data sharing between retailers and suppliers, anchored at the point of sale.”

He says that when verified sales and inventory signals are shared in near real time, three shifts occur:

• Buffers shrink: Safety stock, over-ordering and defensive inventory positions reduce as uncertainty falls.
• Exceptions matter more than averages: Teams focus on what’s changed locally, not on broad forecasts that arrive too late.
• Collaboration replaces negotiation: Retailers and suppliers align around the same facts, enabling faster decisions on ranging, replenishment, activity and funding.

“The downstream effect is material: higher inventory velocity, lower working capital, and new margin opportunities for both retailers and suppliers – created through coordination rather than cost-cutting.”

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