AI Is the Key to Meeting Consumer Demand for Personalisation

There has always been a significant gap between the promise of personalised marketing and the reality of executing it, especially as generational buying behaviors demand increasingly nuanced, channel-specific approaches. Personalisation sounds simple in theory but delivering it consistently and at scale has historically been complex, expensive, and slow.

AI is finally closing that gap.

Consider a familiar scenario: you’re a 30-something living in New York City, typically browsing sports scores and local news. One day, you’re scrolling through a big-box retailer’s website and see an ad for a retirement community accepting new residents in Arizona. Not only do you ignore it, but it actively undermines your confidence in the brand. If a company can’t get basic context like age, location, or intent right, how can it possibly deliver meaningful value?

That’s the real challenge of personalisation. It’s not just about driving revenue. It’s about credibility, relevance, and trust. It’s about whether consumers feel understood as individuals every time they engage with your brand.

Today’s consumers expect personalisation across all digital experiences. Whether it’s targeted ads, TikTok Shop recommendations, or ChatGPT’s purchasing integrations, people want experiences that feel bespoke and responsive to their preferences. They’ve accepted that brands will collect data about their digital behavior, and in return, they expect something useful. This is where personalisation delivers ROI, when brands lean into agentic commerce technology that can act on those signals in real time.

AI Can Help Companies Drive Personalisation at Scale

For years, marketing teams have struggled to move personalisation from strategy decks into execution. Tailoring messaging, advertising, and digital experiences across channels has been time-consuming and costly, with marketers reporting that as much as 40% of their budgets towards personalisation efforts.

Agentic AI is changing that equation.

Today’s agentic tools allow brands to automate, adapt, and optimise experiences continuously without requiring massive headcount or ballooning budgets. Both global enterprises and emerging brands can now deliver relevant, individualised experiences across more platforms, at lower cost, and with far greater speed. The advantage no longer belongs exclusively to those with the deepest pockets. It belongs to those who deploy these capabilities thoughtfully.

Big retailers like Target and Walmart have been early adopters of AI-powered personalisation, leveraging significant resources to build sophisticated consumer experiences. But we’re now entering a more accessible phase of agentic commerce. B2B platforms like Fermat and ShopMy make it simpler for brands to embed agentic workflows directly into consumer-facing apps and websites, unlocking personalisation that benefits both the customer and the brand. When an experience feels genuinely relevant, conversion becomes a natural outcome, not a forced one.

As marketers, our responsibility is to understand consumers’ needs, anticipate their intent, and deliver value at the right moment. Whether that means surfacing flight deals before travel planning begins or recommending a new song just as a playlist starts to feel stale, relevance is the currency of modern engagement. Agentic AI allows brands to tailor content and experiences dynamically, rather than relying on static segments or guesswork.

Agentic AI Is the Future of True Personalisation 

Across industries, brands are already using AI assistants and agents to connect with consumers on a more individual level. Companies like Walmart and Mercedes-Benz 

have launched customer-facing AI tools that help shoppers find products, answer questions, and make decisions faster and with greater confidence.

As these agents become more advanced, brands can leverage them to address specific personalisation challenges—whether that’s product discovery, customer support, or post-purchase engagement—while keeping pace with rising consumer expectations.

AI agents that suggest tailored product recommendations or provide real-time technical support function like personal assistants, adapting to each consumer’s needs in the moment. They can pivot, refine, or redirect recommendations instantly, without disrupting the buying journey or slowing momentum. That responsiveness is what makes personalised ecommerce feel seamless rather than scripted.

Take Walmart’s AI agent,Sparky. The tool delivers tailored recommendations based on nuanced inputs—suggesting a different toaster oven for a family of five than for a college student reheating pizza bagels. And it doesn’t stop at recommendations. Walmart has already outlinedexpanded capabilities for Sparky, from testing ads within the agent to developing future features like personalised reordering and event planning.

Not long ago, delivering this level of individualised attention would have required an army of personal shoppers or support staff. Today, agentic AI makes it possible for teams of all sizes to offer similar experiences, both efficiently and at scale.

Personalisation Only Works When AI Is Implemented Strategically

Of course, technology alone isn’t the answer. Data is only valuable when it’s used with intention, and agentic AI is no exception. Even the most sophisticated systems can’t determine which consumers to prioritise or which experiences to personalise without clear direction from the humans guiding them.

Marketers must still define objectives, interpret metadata, and decide where AI can have the greatest impact. As purchasing behavior continues to evolve—whether that’s through traditional ecommerce platforms, social commerce, or conversational interfaces—brands need strategies that are flexible enough to meet consumers where they actually are.

Agentic AI provides the capability. Strategic leadership provides the clarity.

The future of commerce is agentic but success in that future depends on action today. Brands that operationalise AI agents now will be better positioned to grow revenue, capture market share, and build lasting customer loyalty. Those that delay risk falling behind in a landscape where relevance is no longer optional.

The opportunity is clear but only for brands willing to treat agentic AI as a core capability, not a side experiment.