What types of AI agents exist, and which ones actually bring business benefits?
Lately I’ve been trying to understand which types of AI agents actually make sense for a real business, not just in theory. In our logistics company, we experimented with a simple support bot, and while it reduced some repetitive questions, it didn’t really change the bigger picture. Now management is talking about analytical agents and process automation, but I’m not sure what the difference is in practical terms. Are customer support agents the most profitable option, or do things like workflow automation and predictive analytics bring more long-term value? I’d really like to hear from someone who has seen these different types in action and can share what actually paid off.
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When we explored this topic for our retail business, we realized that not all AI agents are created equal — some focus on communication (like customer support agents), others automate internal processes, and some are data-driven agents that analyze behavior and generate predictions; what really brought us value was combining automation with analytics, because cutting manual tasks saved time, but predictive insights improved decision-making. I found a breakdown of different approaches to AI agents development here: https://sam-solutions.com/services/ai-agents-development-services/ — it helped me see how conversational, task-oriented, and intelligent workflow agents differ in scope and integration level. In our case, the biggest ROI came from automating order processing and adding a recommendation component, not just from a chatbot.