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Traditional automation is rule-based. You define the trigger, the condition, and the action. If X happens, do Y. It breaks the moment something outside the defined rules appears. An AI agent is different because it reasons. It takes an objective, figures out the steps needed to achieve it, selects tools, handles exceptions, and adapts when the path changes.

The question is no longer whether agents can handle real work. It is which workflows are ready to be handed over. Across industries, several high-value processes are already being run by agents at scale.

The opportunity is real. So are the risks. Businesses that rush into agent deployment without addressing these challenges create new problems while trying to solve old ones.