The AI Overload in Retail
Retailers are drowning in AI tools—from chatbots to order trackers—but adding more automation isn't the solution. According to Michael Klein, Head of Retail, Travel & Hospitality Product Marketing at Talkdesk, the real issue is silos.
"Customers expect brands to understand their history without repeating themselves or jumping between channels."
Commerce Orchestration: The Game-Changer
Instead of isolated automation, retailers need commerce orchestration. This approach connects AI agents, systems, and data to create a seamless customer journey. Talkdesk's Customer Experience Automation (CXA) framework coordinates multiple AI agents across service, commerce, and fulfillment, with smooth handoffs to humans when necessary. Crucially, these agents can be built using natural language, making the tech accessible to non-technical teams.
Service as a Growth Driver
AI is shifting customer service from a cost center to a revenue driver. By automating high-volume, low-complexity queries like "Where's my order?", retailers free up human agents for higher-value tasks such as selling, advising, and proactive outreach.
"It's the gift of time. AI handles the routine work so people can focus on meaningful customer interactions."
More natural conversational AI allows customers to engage in ways that feel like speaking with an in-store associate, not a scripted bot.
Building Trust with Guardrails
As AI takes on more responsibility, trust is critical. Klein emphasizes the need for clear guardrails, business rules, and human oversight, alongside careful, real-time use of customer data.
"A bad AI experience can damage loyalty fast. Transparency and control have to be built in."
Early adopters like Rocky Brands are already seeing results, automating around 40% of interactions while maintaining low abandonment rates. Their strategy: a phased "crawl-walk-run" rollout focused on high-impact use cases first.
Practical Steps for Retailers
For retailers stuck in pilot mode, Klein advises: map the customer journey, clean up your data, and prioritize orchestration over adding more tools. Success isn't about how much AI you deploy—it's about how well it all works together.





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