Roadmap for AI commerce: today, tomorrow, and the next decade

What’s more challenging is that the hype often overshadows what’s actually possible (and profitable) for your brand today.

Therefore, the key is to move with intention and focus on real-world applications that build momentum, create a unique advantage, and prepare you for the future of commerce, one step at a time. 

So what should commerce leaders focus on now vs. in the future? Based on the successes (and failures) we’ve seen at DEPT®, here are some immediate, in-the-next-year, and future AI-powered shopping initiatives for brands.

The “today” of AI is about leveraging tools that already exist, and are quickly becoming table stakes for any competitive e-commerce player. These are the foundational capabilities that build efficiency and customer-centricity.

Chatbots: today’s chatbots are advanced, conversational, and brand-aware. They can improve customer service and answer unique product questions right away, leading to informed users and higher conversion. For example, DEPT® helped essence create “Kenna,” a beauty adviser who could recommend products and give advice.  

Next-best offers: the principle is straightforward: AI is better than standard “recommended product” functionality. When implementing an AI-powered NBO model for a large beauty brand, we saw a 500% increase in revenue from NBO-driven communications compared to mass promotions.  

In-platform features: every major commerce platform is racing to provide the best AI tooling for its client base. Salesforce has AgentForce, Shopify has Magic, and BigCommerce is rebuilding for an agentic world. These tools will enable faster adoption and customisation without lengthy build or buy processes. The best choice is to utilise the features available in your current commerce platform.

The zero-click reality: AI-driven search engines are increasingly answering queries directly, making your organic traffic more precarious than ever. Brands must now focus on strategies that make their products discoverable and desirable within these new ecosystems. This means optimising product data for voice search, rich snippets, and other on-SERP features. Our deep dive into zero-click searches is essential reading for any CMO concerned about future-proofing their traffic.

Content creation to solve growing commerce problems: not every AI-generated asset has been a hit. But plenty have, including Otrium, which created “Ovatars,” AI-powered, digital models that help showcase unsold fashion items. This solution addresses the lack of models for every item while also revitalising past-season inventory. It’s a uniquely Otrium solution to a fashion-specific problem.

The “tomorrow” requires a bit of soul-searching. 

Hyper-personalisation, if not guided by a strong brand identity, can lead to an identity crisis. Are you trying to be everything to everyone? Who are you willing to lose to be truly loved by your core audience? 

You must look inward and understand your brand’s unique DNA. Then, build a proprietary AI “moat” that competitors (even large language models like ChatGPT) cannot easily replicate. What knowledge, data, or expertise does our brand possess that no one else does? Here are two examples to illustrate what we mean: 

For a high-end kitchenware brand: imagine an AI “pantry concierge.” A customer lists the ingredients they have on hand—chicken breast, a stray carrot, half an onion, and some rice. The AI, trained exclusively on the brand’s thousands of recipes and the specific thermal properties of its cookware, doesn’t just find a generic recipe. It generates a custom recipe optimised for their 30-CM non-stick skillet, telling them the exact heat setting and time needed to get the perfect result with that specific pan. That’s a secret sauce that builds loyalty beyond the initial purchase.

For a home and garden retailer: think of a proprietary “yard planner” tool. A customer inputs their post code, soil type, and sunlight exposure. The AI cross-references this with the brand’s deep knowledge of regional horticulture and its own product inventory to generate a visual layout and a dynamic 12-month plan. It recommends the best plants, calculates the precise amount of fertiliser needed, and automatically adjusts the watering schedule based on the local weather forecast. It solves a complex, ongoing problem in a way a competitor can’t easily copy.

The horizon is where things get truly transformative. We are moving into the era of “agentic commerce,” where AI agents, empowered by our preferences and data, will make purchases on our behalf.

The autonomous shopper: early examples, like OpenAI’s Operator, have already emerged. Companies like Google and Amazon are experimenting with features that allow AI to track prices, monitor availability, and even make purchases autonomously based on user-defined criteria. For brands, this means that your new customer is not a person, but an algorithm. The question for CMOs becomes: How do I make my brand the preferred choice of an AI agent?

A wearable revolution: as hardware evolves, so too will commerce. Wearables, from smartwatches to smart clothing, will create new data streams and new opportunities for brands. Imagine a future where your workout shirt can detect muscle fatigue and, with your permission, schedule a yoga class or even order a protein shake for you. While moderately far away, innovations like these will slowly (then quickly) take over. 

A new marketing paradigm: in an agentic world, traditional marketing funnels will become obsolete. Brands will need to focus on building trust, not just with consumers, but with their digital agents. This will require a new level of transparency, data ethics, and brand authenticity.

The journey from “today” to “tomorrow” is not a simple checklist. However, it’s not out of reach. Much of the current AI tooling is proven and user-friendly. Getting your team comfortable with it will help you evolve as the tech accelerates, allowing you to keep pace and continue to stay ahead of AI-powered shopping.