"The giants of enterprise technology -- Microsoft, ServiceNow, Salesforce, and others -- have spent the past year and a half unveiling various kinds of artificial intelligence agents, programs that can automate many tasks within their respective software suites. Also: AI killed the cloud-first strategy: Why hybrid computing is the only way forward now The vendors hope that these agents will manifest what they consider the true promise of generative AI: to make enterprise work more streamlined and productive."
"Here's the key challenge: How do we develop large language models -- such as OpenAI's GPT and Google's Gemini -- to operate over long time spans in which they have broad goals; interact with their environment, including tools; retrieve and store data constantly; and -- the biggest challenge -- set new goals and strategies from scratch. We're not there yet. We're not even close. Today's bots are limited to chat interactions and often fail outside that narrow operating context."
Major enterprise technology vendors have introduced AI agents intended to automate tasks across software suites and make work more productive. These agent products mostly perform narrow automations such as generating documents and operate primarily as chat-based tools. Critical capabilities are missing, including reinforcement learning, complex long-term memory, and autonomous goal-setting. True agents must operate over long time spans, interact with environments and tools, continuously retrieve and store data, and set new goals and strategies independently. Current market uptake is low and expectations for immediate transformational benefits are likely to be disappointed; full-featured agents will take years to arrive.
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