3 Ways to Implement Agentic AI in Customer Service — And Why It Matters Now

Customer service is evolving at lightning speed. As customers demand faster, smarter, and more personalized support, traditional call centers and help desks struggle to keep up. Enter Agentic AI — autonomous, proactive, and context-aware systems that don’t just respond to requests but think, decide, and take action on your behalf.
If you’re wondering how to bring Agentic AI into your customer service, here are three game-changing ideas — each tackling a real challenge and driving measurable results.

AI Agents vs. Traditional BI: Who Wins in Retail Forecasting?

Retail forecasting has always been a tough challenge. Businesses want to predict demand, manage inventory, and optimize pricing to stay competitive. Traditionally, companies have relied on Business Intelligence (BI) tools — dashboards, historical data analysis, and static reports — to guide decisions. But now, AI agents are becoming more common in retail. They can process data continuously, adapt to changes, and even automate decisions.
Which approach works better for retail forecasting? This article compares AI agents with traditional BI to see which one delivers more value, especially in a fast-moving retail environment.