Agentic AI will reshape the commerce industry – here's how to prepare

You’ve been hearing about AI agents non-stop for weeks, but what are they? Will AI agents truly disrupt the commerce industry as we know it? Read on to find out and stay tuned for deeper coverage on AI’s commerce impact throughout the year. ‍

What are AI agents and how do they work?

AI agents in commerce are intelligent, autonomous systems that assist consumers in discovering, evaluating, and purchasing products. You might also hear them referred to as “co-pilots.” These include advanced recommendation engines, automated shopping assistants, and AI-driven decision-making tools that personalize and streamline the buying process.

AI agents are essentially systems capable of performing tasks on your behalf, or on the behalf of another system. To bring this concept to life, for consumers, a personal AI agent could assist with ordering your usual list of groceries for delivery on Sunday, prioritizing certain products that you prefer or even prioritizing low prices, quicker delivery times, etc.  

A great example of an AI agent that lies within a specific retailer platform is Amazon’s Rufus chatbot, which has been trained to field product suggestions based on scrapes of PDP information triggered by questions rather than traditional keywords (read more here). Amazon’s next innovation in this space is the recently announced Alexa+, a personalized shopping assistant powered by generative AI that is available for free for Prime users.

With access to your past purchasing data and behaviors, a personal AI agent knows you well and might even learn to shop more efficiently than you. On the product discovery and evaluation side, retailers have a head start in that they have endless product and behavior data for the agents to learn from. But will AI agents entirely disrupt the industry?

Will AI agents disrupt the commerce industry?

This is a bit of a loaded question, but above all the answer to this depends on if consumers adopt the usage of AI agents in mass.

If most consumers start using AI agents for discovery, evaluation, and purchasing of products, then yes – the industry will be disrupted. This implies that search behavior changes entirely, and in some cases, it would no longer performed by the consumer but rather the AI agent trying to output a recommended set of products based on past behaviors.

If consumers are doing less searching, they are interacting with fewer ads along the way – which means that the AI agent is the entity interacting with these ads. Brands will need to find new ways to engage with consumers along the funnel (and measure that impact) while also developing new advertising tactics aimed at reaching the AI agents conducting product research.  

Here’s a brief overview of how AI agent adoption would force industry changes:

• A reduced reliance on traditional ad placements: As AI-driven discovery replaces manual searches, brands must optimize for AI-driven visibility rather than just paid ads.

• A shift toward contextual and conversational commerce: AI assistants will curate shopping recommendations based on real-time needs rather than static search queries.

• New performance metrics: Success will be measured by AI-driven product rankings and recommendation placements rather than just impressions and clicks.

• More focus on structured data: Brands that invest in AI-friendly product content, metadata, and contextual relevance will outperform those that rely on traditional advertising.

How retailers and agencies need to adapt to AI

For retail media agencies and brands, this all means that the consumer journey is shifting from traditional advertising-influenced decisions to AI-driven suggestions, where algorithms determine what products are surfaced, ranked, and purchased.

Retailers will need to update for and/or build advertising models that meet the expectations of brands while catering to the eyes of AI agents rather than consumers, and this will take time to sort out. Agencies will need to develop a deep understanding of this new landscape, learning to optimize for AI-driven product suggestions vs. paid ad placements. We’ve been in the lab here – stay tuned for more details on what we’ve been building!

On another note, AI has also begun to influence bidding engines at the retailer and agency level, which will allow for highly intelligent models to analyze and optimize campaign performance based on a variety of metrics: organic rank, CPCs, share, etc. We’re working on a blog that covers how AI will shape the future of commerce strategy development and execution, so stay tuned.

As AI takes its place in formulating and executing campaign strategy for brands, this puts a greater emphasis on having clearly defined goals for growth. AI can build and execute campaigns based on a goal, but brands will still need to input what the goals they want AI to achieve. Combining this with a shift in what metrics actually matter when consumers adopt agentic AI for product search, discovery, and purchasing – this completely changes commerce as brands have known it. Naturally, we are also working to bring you more details here. There’s a lot of exciting content coming your way in the coming weeks.

How brands should prepare for AI disruption

If consumers adopt AI agents to assist with product discovery, evaluation, and purchasing, loyalty may shift from specific brands to the AI systems they trust. This makes it critical for brands to establish a presence within AI-driven purchase flows and putting AI-native tactics into play. This looks like:

• Optimizing for AI-driven discovery: Product content needs to be structured in a way that AI agents can easily interpret and prioritize. This looks like ensuring product content is easy to understand, detailed, and contains key search terms. Back-end attributes, category data, and metadata should all be completely and accurately filled in, and photos should be correctly tagged with image descriptions.

• Rethinking brand loyalty: AI agents may favor function and efficiency over brand recognition, meaning brands must find new ways to maintain consumer preference.

• Investing in your data: Data is power, and the more a brand understands its customers, the better it can influence AI-driven recommendations. The unlock to understanding consumer behavior comes from partnering with retailers to analyze this data through clean rooms such as AMC to then inform decision-making.

• Exploring AI-powered ad formats: As retailers introduce new AI-driven advertising models, brands must adapt their media buying strategies accordingly.

• Building direct AI integrations: Some brands may benefit from developing their own AI-driven shopping assistants or integrations with emerging AI-powered platforms.

The potential disruption of AI can feel overwhelming as a brand, but the only constant that commerce knows is change. It’s critical to think of AI as an opportunity instead of a threat, and brands who research and begin building now will be well on their way to succeeding in an AI-driven shopping landscape should the industry get to that point (which will likely take years to reach).  

If you’re looking for a partner who has been on the forefront of AI in commerce who can help your brand navigate the unknown, let’s connect.

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