The Evolution of Price as a Quality Indicator
For centuries, price has served as a cognitive shortcut. If something costs a lot, it is perceived to be of higher quality. Luxury items like an Armani suit, high-end Bang & Olufsen headphones, or an in-depth McKinsey report all convey value through their price tags. This simple numerical indicator has long represented a compressed form of reputation.
Generative AI Disrupts the Traditional Value Proposition
With the advent of generative AI, this long-held belief is being challenged across various sectors. Today, a logo may cost as little as 15 euros or as much as 15,000 euros, yet both could be identical. Business insights can originate from a major consulting firm with a worldwide presence or from a freelance enthusiast in pajamas who knows how to navigate technologies like Deep Research. In some cases, the latter may even produce better quality work due to a more intimate understanding of the sector. Such scenarios indicate that the quality of output can exist independently of production costs.
The Link Between Production Cost and Outcome
Generative AI is redefining the connection between production cost and quality outcomes. As articulated by Antonio Ortiz, a prominent figure in AI commentary, this shift separates effort from results. If anyone can generate high-quality content in minutes—once a task requiring extensive teams, time, and significant budgets—then prices start to become irrelevant noise in the discussion of quality.
The Shift From Cost to Process
This disruption is causing a notable shift in the signals we prioritize. The focus is shifting from ‘how much’ to ‘who’, ‘how’, and ‘why’. Key questions are evolving to include “who signed this?”, “what process was followed?”, and “what human decisions influenced the output?” In effect, the process itself is becoming the product.
Documenting the Creative Process
We are already observing this trend in design studios that meticulously document every iterative step. Consultancies are not just selling deliverables; they are offering access to the reasoning behind their decisions. Increasingly, professionals are positioning themselves as digital artisans, charging for transparency in their work methods, not simply for the final product.
The New Scarcity: Quality Criteria
As AI has made production nearly costless, the digital landscape is now saturated with diverse content. Consequently, the rarity that once determined value has evolved into criteria of quality. Judging what to ask for, learn from, and discard is becoming crucial—the essence of good taste in an age flooded with options.
Deciding What Matters
AI’s capabilities are expanding rapidly, often outpacing our expectations. While it can generate almost anything, discerning what is most relevant and valuable remains a unique challenge. Deciding effectively what to pursue is still a significant task that cannot be shortcut.
Conclusion
For the foreseeable future, navigating this vast ocean of AI-generated content relies on our ability to critically evaluate processes and outputs. In a world where the production cost is nearly negligible, these discerning criteria will be the key to understanding and appreciating true quality.