From Helpdesk Cost Center to AI Profit Engine
Customer service has long been treated as a necessary expense: a reactive function measured by ticket volume and handle time. Agentic AI is rewriting that model by turning every support touchpoint into a potential sales conversation. Text, the company behind LiveChat, ChatBot, and HelpDesk, is emblematic of this shift. Its new agentic AI customer service capabilities are explicitly designed to function as an AI profit engine, not just a deflection tool. Instead of simply resolving issues, Text’s Shopify-native conversational AI agents monitor visitor behavior from the moment someone lands on a site, infer intent, then engage with tailored offers, lead qualification, and in-chat checkout. Crucially, these agents are orchestrated within structured workflows and overseen by an AI Supervisor, enabling companies to blend automation with human intervention. The result is a service model that measures success in revenue, leads, and conversions influenced, rather than seconds shaved off response times.
Text’s Agentic AI Playbook: Selling Agents, Workflows, and Supervision
Text’s strategy hinges on agentic AI selling agents that behave more like digital sales associates than scripted bots. Trained on a brand’s product catalog, voice, and business rules, these agents can identify intent, proactively initiate conversations, recommend relevant products, and complete end-to-end transactions within a single chat window. When nuance or reassurance is needed, a human agent can seamlessly join the session, preserving continuity for the customer. To ensure these autonomous agents remain aligned with business goals, Text has introduced custom AI workflows that encode decision logic and an AI Supervisor program that manages agent behavior at scale. Early deployments suggest this customer service automation is not merely theoretical. Customers chatting with AI agents have seen conversion rates to order improve by 266%, with a test group of nearly 600 ecommerce vendors reporting a 39% increase in Chat Sales Attribution and a 7% rise in Sales Operations, alongside a 74% autonomous resolution rate for traditional support queries.
Coach by DICK’S: Agentic AI as Always-On Sports Advisor
While ecommerce brands use agentic AI to sell more effectively, DICK’S Sporting Goods is applying similar principles to deepen customer relationships. Its new Coach by DICK’S is an agentic AI-powered conversational experience embedded in the company’s mobile app, designed to guide athletes throughout their sports journeys. Built using Adobe Brand Concierge technology and DICK’S proprietary sports expertise, Coach acts as a digital advisor that adapts to each athlete’s sport, goals, and preferences in real time. Rather than focusing solely on transactions, the system blends training guidance, product education, and tailored recommendations, effectively extending the in-store expertise of associates into a digital channel. Over time, Coach is expected to evolve as it learns from ongoing interactions, helping athletes navigate product and service decisions with greater confidence. This positions conversational AI agents not just as sales tools, but as trust-building companions that keep customers engaged well beyond a single purchase.
From Reactive Support to Proactive, Revenue-Generating Journeys
Taken together, Text and DICK’S illustrate a broader enterprise evolution: moving from reactive service to proactive, revenue-generating experiences powered by agentic AI. Instead of waiting for a support ticket, AI agents now anticipate needs by reading behavioral signals, context, and stated goals. In ecommerce, that may mean surfacing the right product at the right moment and closing the sale without forcing a channel switch. In retail-inspired experiences like Coach by DICK’S, it means delivering timely training tips and equipment suggestions that build long-term loyalty and lifetime value. Automation does the heavy lifting—handling routine questions, surfacing content, and orchestrating workflows—while humans step in for complex, high-value interactions. The strategic stakes are significant: customer service is no longer a back-office expense but a front-line growth lever. As enterprises refine these agentic AI systems, the line between support, marketing, and sales will increasingly blur into a single, continuous customer journey.