By 2030, AI will power every corner of retail, from personalisation and pricing to supply chain and operations. While its growing influence presents a threat to brand identity and unique experiences, it also offers a great opportunity to strengthen them, says Julian Skelly, Managing Partner at Publicis Sapient.

That opportunity will not be realised through speed and efficiency alone. The retailers that thrive won’t just deploy AI to cut costs or automate decisions; they’ll encode their brand values directly into their AI systems, turning technology into a competitive advantage rather than a leveller.

Cost-cutting may be part of retailers’ DNA, but it’s a dangerous trap when it becomes the only goal of your AI efforts. If every algorithm optimises for efficiency alone, retailers will start to look and sound alike. When every system has the same goals of price, speed, and efficiency, they stop reflecting your brand, making you no different from your competitors.

The real opportunity? AI that expresses your brand’s unique identity in every customer interaction.

The confidence gap

When we launched Publicis Sapient’s 2025 Guide to Next Retail Research earlier this year, we discovered that most retailers are confident in their AI readiness and believe their AI systems already reflect their brand identity. In reality, few actually know whether that’s true, and even fewer can measure it.

Across 157 retail decision-makers, roughly one-third described their AI systems as being scaled enterprise-wide, but most initiatives remain limited to pilots or departmental tests. This disparity reveals what we call pilot purgatory—when retailers believe they’ve incorporated AI, but most initiatives are really still stuck in test mode.

Much of this confidence likely comes from success with traditional AI, predictive models and optimisations that have matured over years. But the next wave of generative and agentic AI demands a different level of readiness: one rooted in governance, brand identity and trust. The good news? Recognising this gap is the first step to capturing the opportunity.

Brand is a key part of your operating system in AI

In the age of AI, your brand isn’t just a campaign anymore. Instead, it’s a system of encoded distinctions, the choices and rules that shape every customer interaction. That means designing AI agents and systems that decide prices, recommendations, and messages to reflect the same priorities as your brand: fairness, quality, service, or sustainability.

Brand-distinct AI shows up in the rules that determine how your products are ranked in search, how your prices fluctuate, and how your AI agents interact with customers and their own AI agents. If these actions aren’t deliberately encoded, AI defaults to simplistic optimisation, and retailers lose their identity.

Think of your brand as part of the training that guides how your AI makes decisions day-to-day. Are you a retailer of trust and fairness? Then your pricing algorithms should reflect that. Are you a retailer of service? Then your copilots should embody excellence, not just efficiency. Are you a retailer of sustainability? Then your supply chain algorithms should elevate those signals in the choices it makes.

Brand-encoded AI in practice

This thinking is reflected in the feedback we have received from retailer leaders. Brand-encoded AI shows up in tangible ways:

Employees: service amplified, not automated away. Rather than replacing staff, AI copilots should understand your brand’s unique approach to service and even articulate it to human employees, empowering associates to deliver experiences that feel authentically yours.

Pricing: fairness over exploitation. Dynamic pricing must reflect brand values, yield curves should lower produce prices as they near expiration to reduce waste, and loyalty should be rewarded through fair discounts, rather than pushing elasticity to the breaking point.

Marketing: creativity over sameness. Good AI amplifies creative distinctiveness, producing campaigns that showcase your brand’s core personality and values while resonating with specific demographics, rather than generating hyper-personalised, yet repetitive content that blurs together.

Every aspect of your brand that was once enforced by people needs to be coded into your AI.

Building the foundation faster

All of these brand-encoded use cases depend on clean, structured, real-time data. Data plumbing (the behind-the-scenes connections that power AI) remains Retail’s Achilles’ heel. Without it, even the best algorithms fail to deliver desired outcomes.

Here’s where 2026 presents a genuine breakthrough: AI-enabled software development. By embedding generative and agentic AI into the development lifecycle itself, retailers can automate code generation, streamline testing, and shorten deployment cycles. This allows teams to build, customise, and scale the data foundations and digital solutions required for brand-encoded AI faster and at lower cost.

This shift turns technology from a capital expense into a continuous capability, freeing resources for customer-facing innovation. Retailers who harness AI to modernise their tech stacks will establish leaner, more resilient operating models. As a result, this makes brand-encoded AI not just aspirational, but achievable.

Agentic commerce: the next battleground

This foundation matters even more as agentic commerce emerges. Almost all retail leaders (96% of those surveyed) say they’re prepared for a future where AI agents transact directly with customers. The reality? We’re seeing previews, not practice. ChatGPT commerce shows what’s technologically feasible, but brand-controlled agentic systems are still developing.

When agent-to-agent commerce arrives, brand-encoded systems will matter more than ever. These agents won’t just represent your products, they’ll represent your reputation across the entire value chain. If your AI can’t express your brand’s values, it risks fading into the background as just another interchangeable assistant.

Choose soul, not sameness

As AI fully saturates retail, cost-cutting and efficiency will become standard, but hopefully not the end goal. What will separate leaders from laggards won’t be the speed of general AI deployment, but the depth of differentiation through AI.

This moment will reveal which brands know who they are and which don’t. The future won’t reward technological sameness; it will reward brands that put soul into their systems. That’s the opportunity 2026 offers: not just deploying AI, but making it unmistakably yours.