Getting started with AI doesn’t have to mean rebuilding your entire tech stack. For many retailers, the most valuable insights are already happening on the sales floor. Every radio call, help request, and exchange between associates holds data about how the store operates.
By learning from these conversations, retailers can uncover patterns, improve communication, and explore how AI can support the frontline. This guide shares practical steps to start your journey with agentic AI on the frontline.
Step 1: Listen to the frontline
The first step in adopting agentic AI is understanding how your team communicates and where challenges lie. Radio conversations, help requests, and inventory checks reveal where time is spent and where associates need quicker access to information.
Inefficient communication adds up. A recent study found that frontline friction costs businesses an estimated US$80.6 billion annually, with each worker losing hundreds of hours searching for information or waiting for direction.
By capturing and reviewing voice traffic, retailers can identify common themes such as repeated questions and response delays. These insights highlight where AI agents could provide the most value and lay the foundation for deployment through platforms like SYNQ’s voice AI suite. Data is the oil of the AI economy, and this is a massive, untapped data source to inform store operations.
Step 2: Build and deploy store specific agents
Once the opportunities are clear, the next step is to begin training small language models (SLMs) tailored to your stores and the uniqueness of certain terms or acronyms. These models learn from real conversations, policies, and procedures so they can understand how your store runs and respond to associates naturally.
Using tools like Azure AI Foundry, retailers can train SLMs that are specific to their store’s operations and communication patterns. Through SYNQ’s voice AI suite, these models can then be deployed across existing two-way radios. Associates can simply ask questions out loud and receive accurate, real-time answers without leaving the sales floor.
Word to the wise: start simple. Many organizations have deployed overly-complex AI tools that don’t get beyond a test phase. We encourage retailers to consider simple, targeted agents to start. These can always be added to as adoption grows. Examples include inventory queries or a cashier agent for new grocery cashiers to quickly get produce UPCs.
Step 3: Review, refine, and expand
After deploying your store specific agents, observe how they perform in real environments. Track which questions are being asked most often and note where the agent hesitates or asks for clarification. These moments show where the model needs additional information or context.
The voice AI suite makes it easy to review these interactions and update the model manually. New questions and responses can be added so the system continues to learn from real conversations. Over time, this creates a feedback loop that makes the agents smarter, more reliable, and more aligned with store operations.
Bringing AI to the frontline
Agentic AI at the frontline starts with listening, learning, and building on what’s already happening in your stores. By turning everyday communication into data, deploying voice-based agents, and refining them over time, retailers can unlock a new level of visibility and efficiency.
SYNQ’s voice AI suite helps make that possible by integrating seamlessly into existing systems and turning conversations into insights that power better decisions on the sales floor.