Agentic AI in Retail: Use Cases, Benefits & Challenges

AI keeps gaining ground in retail. 61% of retailers have separate AI leadership teams. The technology is most often used for customer support (55%), operations (49%), and marketing content (48%). At the same time, experts are already discussing a third wave that will revolutionize how complex operations are managed. We are talking about agentic AI in retail. AI that is capable of working without prior detailed instructions and without human intervention. 

According to PWC, 88% of executives report that their companies intend to boost agentic AI-related spending next year.

So what is it, what opportunities does it open up, and what are the prospects for its implementation?

Retail agentic AI is a new form of artificial intelligence that combines the achievements of previous generations: large language models or generative AI, machine learning, and others. The technology is capable of working autonomously, analyzing data, setting goals, and implementing them without human oversight.

In other words, AI agents can learn, make targeted decisions, identify and solve problems, and improve with each operation.

This means that AI transforms from an innovative tool into a digital partner capable of working in changing, complex conditions. This new level of automation enables retailers and opens up significant prospects for development.

Spoiler alert: the technology is still under development, but its implementation is just a matter of time. Some retailers are already experimenting with introducing the first tools based on the new AI, and its capabilities are becoming abundantly clear.

Several types of AI are used in store operations:

• Traditional. This uses historical data to forecast demand and classify assortments. For example, it can suggest how many goods to order to avoid shortages and oversupply in the warehouse.
• Generative. That would be a large language model capable of generating ideas or new content based on learned scenarios. For example, it can create product descriptions or work with marketing texts.
• Agentiс artificial intelligence capable of conducting autonomous store operations, as it initiates actions and achieves goals without prior commands. In other words, it is a system capable of taking initiative.

So, the new system can act independently and achieve a specific goal, using feedback and context to make decisions. But can this even be useful in retail? At a minimum, it can improve retail operations by controlling traffic and coordinating the supply chain without waiting for human management decisions.

A single simple example: autonomous systems control traffic in brick-and-mortar stores and manage the number of staff who should be on the sales floor. Moreover, historical data and dynamic information about the flow of customers in real time can be used as decision-making factors.

Let's consider the potential benefits of this new technology and how it could affect retailers and direct buyers.

This is one of the trends in modern retail.  Agentic AI is capable of scaling from buyer segments to specific customers. The system can continuously analyze customer interactions, provide more accurate recommendations, and conduct full-fledged communication. Among the theoretical possibilities are tracking the behavior of each specific buyer in the store and sending individual offers. Regarding online commerce, the system can automatically change the display of goods for each visitor.

New artificial intelligence can highlight competitive advantage and identify the reasons for decreased operational efficiency. At the same time, it corrects them with minimal human intervention or even completely autonomously. This applies to all operational efficiency aspects: inventory management, dynamic pricing, and staff scheduling. The result is reduced costs and improved resource allocation.

The behavior of today's customer is unstable: customer experience is based on fleeting trends. This is a challenge for retailers, as they must adapt quickly to changing conditions. Agentic AI can solve this problem. By promptly identifying the sources and causes of the following change, the system can optimize inventory levels, attract the correct number of staff, redirect buyers to alternative products, and more. The lightning-fast response of artificial intelligence is also critical during “hot periods” such as holiday sales.

If the right products are on the shelves, recommendations are timely and relevant, and customer support is instant and high-quality, this increases customer engagement and makes it highly likely that they will return.

By analyzing the system's potential capabilities, we can predict the most likely applications for this powerful tool:

Modern chatbots rely on pre-written scripts and built-in communication algorithms. Generative AI has improved this experience and made communication more flexible. However, an agent with artificial intelligence can deepen this experience: it will communicate by analyzing the behavior of each specific customer, make personalized offers, and be able to solve complex issues.

The system can be tasked with dynamically changing goods prices to maintain the best margin. Artificial intelligence can decide based on inventory, demand, customer behavior, and competitor activity.

Recommendations, timely communication, notifications based on activity or real-time movements are all possible if the system is provided with the relevant customer data.

Modern AI tackles these problems quite well, but agent-based AI can deepen interaction. It can, for example, identify problems early, reallocate resources, redirect supplies, or even adjust storefronts.

This is a high-risk operation, and artificial intelligence will increase the chances of success. It can adjust launch strategies in real time, managing marketing and inventory.

Despite the potential benefits, implementing a new system can be pretty challenging. We are not just talking about the necessary ample initial resources (both technological and human). There are several ethical and organizational issues. Most importantly, artificial intelligence must be provided with high-quality data. Under legislative frameworks like CCPA and GDPR, consent must be obtained to receive information, protect it, and act as transparently as possible. This issue requires high-quality organization from the first day of the system's implementation.

We must not forget about the potential risks. Any system is capable of making mistakes. Is it too early to give complete control to artificial intelligence? In fact, everything needs to be balanced. You can entrust the system with areas that require analysis of large amounts of data and complex decision-making, while constantly monitoring the results. Areas that require empathy, such as product promotion, can be developed with the help of human potential.

As we have already established, agentic AI requires structured data, intelligent planning mechanisms, and human control. Experts emphasize that the true power of agentic AI lies in its ability to link recommendations to clear explanations, not just results. Such transparency builds trust and accelerates adoption. Without it, agentic systems risk becoming a black box that users are reluctant to accept. That's why at LEAFIO AI, we've already created an ecosystem on which agentic AI will depend.

The LEAFIO AI Retail Platform shares data across a unified ecosystem of functional modules managing inventory, merchandising, and assortment efficiency. Combined with deep retail expertise, it provides the perfect foundation for harnessing the power of agentic AI.

Retail experts agree: AI agents succeed when humans remain in control. Agent AI does not replace planning professionals; it accelerates their decision-making cycles, provides more intelligent recommendations, and eliminates tedious manual work. At LEAFIO, we focus on three key principles:

1. Provide clear, actionable insights (no “black boxes”).
2. Automate what is proven and safe.
3. Leave the final say—and responsibility—with humans.

But how do these principles translate into practice? Let's look at our new AI Assistant, which is integrated into shelf performance reports. This tool demonstrates how we transform routine analysis into quick dialogue.

Imagine a category manager analyzing weekly network performance. Instead of spending hours filtering tables and comparing dozens of columns in an LFL report, they can ask the assistant:

“Which stores showed the highest profit growth?” The AI will instantly identify the leaders whose assortment and pricing practices are worth scaling.

“And which stores are the most problematic, where sales and profits are falling and inventories are rising?” The system will immediately highlight the points that require immediate intervention: review of assortment, promotional activities, or supply.

This is the automation of safe processes: instead of a mechanical search for data, the manager receives a ready-made summary analysis in a few seconds.

Another example is layout optimization. Working with a report of recommendations on facings, a specialist can ask a direct question: “Which products show the biggest difference between the current and recommended display?” 

The AI Assistant will identify products that either take up too much valuable shelf space or are underrepresented, which can lead to out-of-stock situations.

At the same time, we adhere to the principle of “people make decisions.” Our AI Assistant is analytical, not an autonomous manager. That is why we emphasize not using it to make critical decisions without manual verification.

This approach allows brands using predictive tools to generate millions in additional revenue through smarter promotional and assortment decisions. LEAFIO customers are already reaping the benefits—and have the opportunity to move forward with the evolution of agent AI capabilities.

Genuine autonomy is not a feature you attach, but the result of building systems that think, act, and adapt in sync with your business goals. At LEAFIO AI, we have built that foundation. Whether you want to optimize inventory, streamline promotions, or secure the future, our platform helps you work smarter today and prepares you for autonomous planning tomorrow.