An AI agent is only as good as the data behind it.
With the advent of large language models supporting famous generative AI systems like ChatGPT or Claude AI, a great many businesses are turning to AI agents and chatbots to support their daily operations in logistics, customer service or correspondence, among other needs.
What’s the difference between an AI agent and a chatbot?
While both require quality data to support their activities, a chatbot is a simple system that can be “taught” to respond to specific queries with scripts and can fetch information and provide it back on cue. An AI agent is a little more complex and concomitantly more capable.
An AI agent is a relatively autonomous system, powered by machine learning and natural language processing technologies. It can receive and process inputs and return appropriate outputs, and it can also learn about its users’ preferences, extrapolate rules from data presented to it and apply those rules to novel data it encounters. It can use tools, break down tasks, and choose next steps.
How can businesses make sure their data is AI agent-ready?
Data is the lifeblood that flows through all forms of automation, and that includes AI. The DCA Data Services team has come up with a 5-point checklist to help businesses ensure they’re ready to get started with an AI agent of their own.
