Supply Chain & Logistics
Counterfeit product detection in supply chain
Use computer vision and data analysis to identify counterfeit or grey-market products entering the supply chain. Compare product images, packaging, and documentation against authenticated references.
20–40%
improvement in counterfeit detection rates
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Challenging. Significant technical work required. Likely needs an AI engineer or specialist vendor. Not a quick win.
Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.
High risk. Significant external exposure or regulatory implications. Requires robust oversight and clear accountability.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
This is most relevant for luxury goods, pharmaceuticals, electronics, and branded consumer goods where counterfeiting creates significant financial and reputational risk.
The model needs a comprehensive library of authenticated product images and packaging to compare against. Building this reference library is the first step.
Counterfeiters adapt quickly — a detection system that catches today's fakes will need regular updates as the counterfeiting techniques evolve.
Experiment starter: Source 20 known authentic products and 20 known counterfeits (from seizures, marketplace purchases, or test buys). Run them through a visual comparison model to measure detection accuracy. If the model distinguishes authentic from counterfeit at 85%+ accuracy, it's worth developing further.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — Risk and GovernanceThis opportunity scores low on risk exposure — read the risk and governance approach before you start.More in Supply Chain & Logistics
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