"If you were around for the first big wave of cloud adoption, you'll remember how quickly the term cloud was pasted on everything. Anything with an IP address and a data center suddenly became a cloud. Vendors rebranded hosted services, managed infrastructure, and even traditional outsourcing as cloud computing. Many enterprises convinced themselves they had modernized simply because the language on the slides had changed. Years later, they discovered the truth: They hadn't transformed their architecture; they had just renamed their technical debt."
"That era of "cloudwashing" had real consequences. Organizations spent billions on what they believed were cloud-native transformations, only to end up with rigid architectures, high operational overhead, and little of the promised agility. The cost was not just financial; it was strategic. Enterprises that misread the moment lost time they could never recover."
Marketing is labeling many simple automations, thin LLM interfaces, and enhanced chatbots as 'AI agents,' which obscures important architectural and risk distinctions. The cloud adoption era shows how rebranding technology without real transformation produced wasted investment, rigid architectures, and lost strategic time. A genuine AI agent requires autonomy, multistep planning and execution, and adaptation to feedback and changing conditions. Treating non-agentic systems as agents invites governance failures, operational and regulatory risk, and misplaced trust. Assessment of decision authority, technical behavior, and tool access is essential before assigning agent-level controls and oversight.
Read at InfoWorld
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