From Browsing to Buying: Agentic AI's Journey Through Retail

Key Takeaways:

1. Agentic AI can act as virtual employees, not only driving insights but taking autonomous actions
2. These agents enable efficiency, hyperpersonalization and improved supply chains
3. Visual search and augmented reality can bridge the gap between physical and digital retail
4. Implementation should be expert-led and tailored to retailer specifics

In an era where hyperpersonalized customer experiences and optimized operations are essential to be competitive, agentic AI in retail is becoming a must-have technology.

Agentic AI has the potential to address key challenges like omnichannel integration, personalization at scale and operational efficiency across the entire value chain - from product discovery and selection, all the way to purchase and the support beyond it. No surprise, therefore, that the global market for retail AI is expected to grow by more than 400% between 2024 and 2030.

In this blog, we’ll explore how agentic AI in retail works, why it matters, and the scale of the difference it can make - not only now, but in the future, too.

What is Agentic AI and Why Does It Matter for Retail?

Agentic AI uses large language models and wrapped functionality to perform complex tasks and operations, without the need for much (or even any) human intervention along the way. Instead of just driving insights and findings from data, these are AI systems that can take autonomous actions based on real-time information, essentially acting like virtual employees.

From an industry perspective, agentic AI in retail has broken down the access and cost barriers to advanced technology that many businesses have faced in the past. Now, retailers big and small can create hyperpersonalized software applications, augment and expand the capabilities of their workforces, and address use cases that previously seemed economically unviable.

A key advantage of agentic AI is its ability to enable micro-SaaS solutions that tackle problems that traditional software approaches couldn't justify economically. This opens up the "long tail" of retail applications that were previously out of reach for all but the largest enterprises.

Modern Retail Hurdles: What's Holding the Industry Back

The advent of eCommerce has transformed the global retail industry over the last two or three decades. Through that revolution, customer expectations and drivers of competitive advantage have changed, and many retailers have struggled to deal with emerging challenges. These include:

Omnichannel Integration

Creating truly seamless experiences across physical and digital channels remains difficult, especially when customers increasingly expect consistency across stores, websites and mobile apps. Separate systems across online and offline channels often lead to gaps that are difficult to bridge.

Personalization

McKinsey has found that businesses that excel at personalization generate 40% more of their revenue from it than those with weaker capabilities. Initial AI solutions for personalization focused on simple product recommendations based on structured historical data, but the bar has been raised since then. Now, agentic AI is essential to incorporate real-time contextual information and achieve the genuine one-to-one personalization that consumers are looking for.

Operational Efficiency

Smaller retailers in particular have lagged in adopting advanced inventory and supply chain management tools for resource and cost reasons. That has limited their ability to forecast demand with accuracy, reduce the burden of human oversight and intervention, and explore new opportunities for efficiency and revenue (such as dynamic pricing).

Technology Adoption

Taking on innovations like AI has been difficult for physical retailers, many of whom struggle to digitize their operations. Online players who are based around technology naturally have an advantage, which also extends to their organizational structure, talent pool, access to usable customer data, and ability to scale.

Agentic AI in Retail: A New Edge

Agentic AI in retail has the ability to help solve all of these problems, in no small part because it can act as a highly skilled virtual employee. Forward-thinking retailers have already adopted agentic AI in retail across use cases such as:

Autonomous Shopping Agents

Preconfigured AI agents can discover, evaluate and even purchase products on a customer’s behalf based on their preferences, price considerations and instructions. They’re able to collate data across independent platforms like marketplaces and product comparison sites to find the best choice for the consumer at the best price.

Hyperpersonalized Customer Experiences

Agentic AI in retail enables new levels of personalization for individual customers. For example, it can generate product images that are contextual to customer preferences, and support highly granular customer communication and segmentation through deeper data analysis and insights. Furthermore, combining structured and unstructured data into customer service chatbots enables more detailed conversations and resolutions for more complex queries.

Visual Search and Augmented Reality

AI-driven visual search can bridge the gap between online and offline shopping experiences, where customers can explore augmented reality environments and visualize products in their own settings. This allows them to compare different items and choices in the same way as they would in a store, without the need to visit in person and interact with items physically.

Intelligent Inventory and Supply Chain Management

Automated, intelligent AI agents are transforming retail operations behind the scenes. They can power accurate, real-time inventory information through visual recognition systems and webcams, and add greater intelligence to demand forecasting and dynamic pricing to enhance inventory planning and reduce stock issues.

Key Benefits of Agentic AI in Retail

The adoption of agentic AI offers retailers significant advantages:

In Summary: Embracing the Future with Agentic AI in Retail

Perhaps the most exciting thing about agentic AI in retail is that it’s continuing to evolve, and its capabilities will only continue to expand in the months and years ahead. From truly autonomous shopping experiences to hyper-efficient supply chains, the possibilities are expanding rapidly, so the time to invest in agentic AI - if you haven’t done so already - is now.

The best way to unlock all this potential, and navigate the complexities of this technology and its implementation, is to work with an expert retail AI partner like Ciklum. Our unique combination of AI engineering, UX capabilities, and business expertise means we can create applications that are easy to use, your customers will love, and are based on proven frameworks for decision-making, tool choice, and implementation strategy.

Our vendor-agnostic approach means we can build the right implementation for your specific requirements, and put in place everything you need to drive competitive advantage through agentic AI in retail. 

To find out more, contact our experts today for a consultation.