AI, Devouring the Retail Industry... The End of "Chatbots," The Era of "Intelligent Agents" Arrives

The retail industry is entering a fundamental turning point. Artificial Intelligence(AI) is no longer an elusive experimental tool; it is gradually becoming the core operating system of retail. From inventory adjustments, customer experience, marketing to supply chain management, AI is crossing all areas of retail operations, transforming from an advisory role to a true action-taker.

By 2027, AI is expected to no longer be just a part of technology but integrated as an operational system that underpins the entire business. Databricks Chief Scientist Jonathan Frankel asserts, “AI is simply a new form of computing different from traditional computation.” This highlights that AI is not just a functional element but signifies a platform-level transformation.

The core change is not whether to introduce AI but how to elevate it into a genuine competitive advantage. CIO advisor Tim Crawford explains, “We are moving beyond chatbots and evolving into truly executable systems,” and emphasizes that the introduction of AI requires restructuring at the operating system level and governance innovation.

The central axis of AI introduction is shifting toward building a “modular AI stack” to achieve more customized intelligence. Retail companies are selecting and combining models and tools that fit their own DNA, which is part of avoiding dependence on specific vendor strategies. Steven Orban from Databricks describes this shift as “not a retail show, but a tech show,” emphasizing a paradigm shift centered on technology.

The transition from analytical AI to behavioral “agent AI” is also noteworthy. Nitin Mantani, head of Salesforce Retail, states that AI is evolving beyond mere data extraction toward taking real actions. This means AI systems can not only identify inventory imbalances but also automatically correct them.

This change also fosters a staff-centric digital collaboration structure. Mike Mikuč, CEO of Fabric, explains that they are deploying role-based AI agents for store managers and operators. These agents are not dashboards but serve as “digital colleagues” performing work tasks.

Particularly, the impact of this wave of transformation is first evident within organizations. Knowledge hidden in documents, legacy systems, and team units is reconnected through AI agents, thereby increasing operational speed and consistency across the company. This exemplifies AI’s evolution beyond mere support roles to functioning as the enterprise’s “neural network.”

Interestingly, the power of AI is creating greater opportunities for small and medium-sized retail businesses rather than large corporations. Companies that quickly adopt agent systems can relatively escape the thin-margin, high-volume model, providing high service quality even without fixed expenses, thus gaining a competitive edge. Smaller, agile companies that reduce unnecessary layers are rising as “small but powerful” entities.

Additionally, digital commerce is evolving from “PC-based” to “context-based.” Customers no longer browse passively but explore products based on intent through voice, video, text, and other methods. AI learns this information in real-time and designs personalized shopping paths. Mantani diagnoses that through this approach, “the store itself is transforming into a living, organic entity.”

Offline stores are no exception. AI is not about full automation but about enhancing through sensorization and analytical functions, evolving into “smart stores.” On-site staff are liberated from repetitive tasks and can focus on high-value activities.

The true value of AI is most evident in the supply chain. In an increasingly unpredictable global supply environment, AI performs real-time inventory redistribution, recommends alternative logistics routes, and simulates demand. Its role is no longer just a cost-saving tool but a weapon to protect profits and ensure brand trust.

Meanwhile, robotic logistics and physical AI technologies are gradually penetrating the retail industry. Autonomous driving, robot picking, and other innovations are no longer laboratory concepts but integrated into standard warehouse workflows. AI has begun to control the “real world,” not just the virtual realm.

However, whether all these potential capabilities can be realized ultimately depends on people. Even with high-performance AI models, if organizations lack the ability to integrate and execute them, their effectiveness will be limited. Leadership and operational strategies are more important than coding, requiring organizational redesign.

The final competitive point for AI proliferation is “reasoning infrastructure.” Computing resources used for prediction or recommendation are unimaginably vast, and their efficiency and stability directly impact business speed and profits. This is why the perspective shifts from viewing AI as just a technology to considering it as a fundamental business infrastructure.

Today, retail has moved beyond the introduction phase into the stage of establishing advantages. Experiments are over, and systems are being built. The era of technology adoption and benchmarking has passed. The next 12 months will be a decisive moment—determining not just who “uses” AI but who will define the retail landscape of the AI era.