AI Deliverables Should Be Judged by Outcomes, Not Effort

The value of AI-generated deliverables should be judged by their outcomes and business impact, rather than the time or effort invested in their creation. When two projects yield the same accurate and useful results, leading to identical business outcomes, the client's satisfaction should remain consistent regardless of the creation time. However, the discovery that one deliverable took 20 hours while another took only 20 minutes can raise questions about AI involvement, pricing, and perceived skill levels.

This disparity in reaction often stems from a long-held societal connection between value and effort. Decades of experience have led many to associate long hours, struggle, and apparent difficulty with expertise and justification for higher prices. Conversely, fast work can appear suspicious, and the efficiency gained through AI can lead to discomfort when a customer realizes AI was used in the creation of a product they purchased.

A LinkedIn poll asking whether the method of creation matters if the outcome is excellent reinforced this observation. The primary objections to AI often appear unrelated to the quality of the final product. This suggests that the discomfort is less about the AI's capability and more about ingrained perceptions of value tied to human labor and time.

The principle is illustrated by a story of an experienced engineer who fixed a ship engine with a single hammer tap, charging $10,000. His breakdown revealed that the tap itself cost $2, while the knowledge of where to tap was valued at $9,998. This anecdote, whether factual or allegorical, highlights the core lesson: expertise and the application of knowledge, rather than the physical effort, are the true drivers of value, a concept that AI deliverables should also be measured against.