Agentic E-commerce, also known as agent commerce or Agentic Commerce, has redefined buying and selling in the digital environment, creating a faster, more efficient and personalised ecosystem, where the key lies in collaboration between humans and AI.
E-commerce has evolved rapidly in recent years since the arrival of the first online stores, through automation and now with the emergence of artificial intelligence. It is no longer a question of consumers searching for products, but rather of AI agents finding them for us, negotiating the best price and purchasing them.
What is Agentic E-commerce?
Agentic E-commerce is an automated e-commerce model based on artificial intelligence systems that act as autonomous agents. These agents learn from consumer behaviour, tastes and preferences to perform specific actions such as searching for products, comparing them, bidding on them and managing payments.
It is therefore an evolution from traditional e-commerce, which depended on rules, static funnels and limited automation, to a new model that includes AI agents capable of making autonomous decisions, anticipating user needs and improving their experience.
The big difference with automation is that agents not only execute, but also reason, prioritise and optimise results.
Benefits of Agentic E-commerce
Surely, after reading these first few lines of the blog, you are already thinking of the many improvements that this new model can bring to your business. In essence, we are talking about moving from operating an online shop to supervising an intelligent buying and selling system.
- Scalability and sustainability: the model quickly adapts to new channels and markets without increasing operating costs.
- Real-time decisions: agents process large amounts of data and make decisions much faster, more accurately and more agilely than previous systems.
- Hyper-personalisation: users receive recommendations tailored to their profile, reducing friction and improving conversion and retention.
- Cost reduction: less dependence on manual systems and greater efficiency in key processes such as customer service or pricing.
- Continuous business optimisation: with AI, we are able to continuously enhance and improve our processes, because the algorithms learn from every interaction and result.
In mature businesses, this new approach focuses mainly on improving KPIs such as customer LTV or NPS.
Use cases for Agentic E-commerce
Imagine that we are in the middle of a key period such as Christmas or Black Friday, where competition is increasing and big brands are bidding for users with very competitive pricing strategies.
Well, this is where our intelligent agents come into play, adjusting prices based on market demand, our product stock, competitor prices and customer history: tastes, needs, budget… All with the aim of offering the best product, at the best price and at the best time to the customer.
Another very common use case is incidents. Until now, we had automation systems to ask users to leave reviews of devices, give us feedback if something had gone wrong with the delivery, or if the product had been delivered damaged.
Now, our agents can resolve user queries about the whereabouts of their order in real time, offer personalised compensation to users whose order has been delayed, manage and negotiate returns if the customer is not satisfied with the product, or escalate complex cases where we want to deal with the user personally. Here, once again, we are looking for agile processes and the best user experience.
The result is therefore clear: more agile processes, less friction and a much more refined user experience.
How to implement Agentic E-commerce in your strategy
To implement an Agentic E-commerce model in our business, we first need to have a well-defined strategy, the right technology and profiles capable of designing, supervising and scaling autonomous systems.
In addition to these three pillars, the most fundamental thing is to define which decisions we want to delegate: pricing, customer service, inventory management, negotiation with suppliers… The key is not to automate everything from the outset, but to have a real, high-impact use case.
Technology
The first step is to internalise that AI agents need context and purpose. Therefore, technology is key to being able to rely on advanced language models (LLMs), capable of reasoning and making decisions based on objectives. In addition, these models are complemented by agent frameworks that allow tasks to be coordinated, roles to be defined and autonomous orchestration. All of this must also be integrated into the ecosystem of platforms present in e-commerce natively: CRM, logistics, payment systems, etc.
Data
Once we have the technology, the next key element is data. Agents make decisions and learn based on available information such as customer history, purchasing patterns, stock, and price trends. Therefore, we need to refine our database, structure it, and make it accessible. Without quality information, autonomy loses its value.
Key profiles
Finally, the human factor remains decisive. Implementing Agentic E-commerce requires technical profiles such as artificial intelligence or machine learning engineers, capable of designing and training reliable agents. On the other hand, we need product managers to define clear objectives, as well as e-commerce and business specialists to oversee decisions from a strategic perspective. In addition, we need to add UX and CX profiles, responsible for ensuring that the experience remains reliable and human.
The future of e-commerce is Agentic
Agentic E-commerce is not a fad, it is a reality that has changed the way online stores are built and managed. Its potential is enormous, but its adoption also brings with it major challenges such as data governance and control, the biases and errors that our models may commit, and trust and transparency with our customers.
In the coming months, we will increasingly interact with online stores that are partially or fully autonomous and AI-based personal shoppers who make decisions for us.
In other words, we will experience increasingly agile and invisible processes for the user, leaving aside complex interfaces and delegating our own decisions. In turn, brands will have to understand this change in order to lead the next generation of digital e-commerce, where the key is to combine autonomy with business objectives and customer expectations.
The first step towards this new reality is simple: you just have to identify a critical process, delegate low-risk decisions and start learning with your agents.
