Most AI agents in customer support are just chatbots with fancy wrappers.
Most AI agents in customer support are just chatbots with fancy wrappers.
And I hate to break it to you, but they are the exact wrong place to start.
Everyone wants to jump straight to automated responses. But you cannot improve what you cannot clearly see.
Here's what I mean - we worked with an EV client drowning in support tickets. Humans were trying to sort requests manually across 12 main categories and over 60 subcategories.
The result? Inaccurate data, untrusted metrics, and total operational chaos. They didn't need a chatbot - they needed an AI agent to clean their data.
So we deployed an AI agent strictly for categorization. No complex reasoning. No generating responses. Just structuring the incoming requests.
The reality is:
ā Categorization is a safe, low-overhead starting point
ā It doesn't require massive models - open-source works perfectly
ā It reveals exactly which high-volume tickets you should actually automate
Only when you have pristine data do you start automating responses. Because that is when you clearly know where the biggest value for automation lies.
Stop chasing the generative AI hype. Start structuring your data.
If you are building AI into your operations, what is your first step? Are you categorizing your data first, or jumping straight to chatbots?
#AI #Automation #AIAgents #CustomerSupport #TechLeadership