"We called it a 'botnet' when numerous bots would carry out coordinated actions across one or more networks. Imagine a message in one chatroom triggering a response in another chatroom or even on a different server, long before Application Programming Interfaces (APIs) or workflow automation tools such as Hootsuite, Zapier, or N8N existed. You set a rule about a command, an event trigger, an auto-response if a certain type of message came through, and the system would act."
"From text to action Where generative AI writes, agentic AI executes. It can draft, post, reply, buy, schedule, and optimise without waiting for approval. McKinsey's 2025 survey found that half of enterprises are already piloting autonomous workflows. But governance is lagging behind adoption. KPMG's global study on trust in AI found that nearly three-quarters of people are unsure what content online is genuine. The illusion of engagement is a threat to real communication."
Early chatbots formed networks that triggered coordinated automated actions across rooms and servers using event rules and auto-responses. Agentic AI scales that premise in the cloud, monitoring events, making judgments, and taking actions with minimal human oversight. Generative AI composes content; agentic AI executes it, including posting, replying, purchasing, scheduling, and optimising autonomously. Enterprise pilots of autonomous workflows are already common, while governance and public trust lag. Widespread agent use can amplify, comment on, and optimise content, creating the illusion of engagement, devaluing authenticity, and potentially replacing human interactions with automated systems.
Read at ComputerWeekly.com
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