A system can identify a similarity without establishing why that similarity matters. That distinction sits at the centre of the question: can AI authenticate luxury goods?
AI can support authentication. It can help organise evidence, compare visible features, identify patterns and retrieve reference information. Used appropriately, it can also support consistency in how information is brought together for assessment. These are useful contributions, but none determines what the evidence means on its own.
My position is that technology should support professional judgement, not replace it. The useful discussion is not AI versus the authenticator. It is how the work of comparison connects to a conclusion the evidence can sustain.
The comparison needs the right context
Before interpreting a match or a difference, the reference material has to be appropriate. Brand and model are part of that context, alongside material, construction and production period.
Historical reference information matters because characteristics may change over time. A comparison with material from another production period can make a difference visible without explaining it. The question is whether that difference is relevant to the item being assessed, not simply whether the system has detected it.
A larger reference collection is therefore not enough by itself. What matters is whether it contains reliable, applicable information for this particular assessment. Retrieval is useful when it brings the right reference into view; professional interpretation still has to establish whether that reference belongs in the comparison.
The same discipline applies to the evidence supplied to a system. Photographs may show some areas clearly while leaving others out of view. A result based on those photographs cannot settle a question that requires evidence they do not contain. Where images are insufficient, physical examination may still be necessary.
What happens after the output?
This is where the professional responsibility becomes clearest. Is there enough evidence to answer the question? Why does a particular feature carry weight? Can apparently conflicting observations be reconciled with the item's production context, or does a material question remain unresolved?
Authentication interprets evidence as a whole. A correct serial number does not establish authenticity, and an isolated difference does not establish that an item is counterfeit. Having software identify either one does not change that principle.
Nor should apparently consistent features simply cancel out an unexplained inconsistency. The task is to understand the relationship between the observations, rather than count how many fall on each side. An AI output can help direct attention, but the reasoning must explain what the available evidence supports.
If a relevant reference is missing, or a feature cannot be assessed adequately, that uncertainty should remain visible. I would rather explain the limitation clearly than give a confident answer the evidence cannot sustain. This is the same principle explored in When an Authentication Assessment Cannot Reach a Firm Conclusion: an unresolved assessment is neither confirmation of authenticity nor a counterfeit verdict.
A professional report should preserve the evidence, observations and reasoning behind the conclusion. When AI contributes to an assessment, its output should be considered within that explanation, not stand in for it. A reader still needs to understand why the conclusion follows and what remains uncertain.
My approach to luxury authentication and inspection keeps evidence and professional interpretation connected. Technology has a valuable role where it helps organise the material, make relevant comparisons or identify questions that need closer attention. It cannot independently guarantee authenticity.
The more useful question, then, is not whether AI can produce an answer. It is whether technology and professional expertise together can make the basis for a conclusion clearer, including when the evidence is not yet enough.