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Good practice Imported

Dubai Customs' Smart Risk Engine — AI-Powered Cargo Screening Against Smuggling

United Arab Emirates · Dubai · See the United Arab Emirates profile · See the Dubai profile

Evidence: Descriptive / self-reported Top 62% 53/100 · Ask Evidence Copilot about this practice

Dubai Customs' in-house Smart Risk Engine uses AI to flag high-risk cargo; officials credit it, with the Siyaj and Shahin programmes, for 406kg of narcotics and 2.3 million illicit pills seized in 502 operations in early 2026, including 278,850 pregabalin tablets.

406 kg
Narcotics seized (Jan-May 2026)
2.3 million pills
Illicit pills seized (Jan-May 2026)
502 operations
Anti-smuggling operations (Jan-May 2026)
278,850 tablets
Pregabalin tablets seized in single AI-flagged case

Details

Maturity
Established
Promoter
Dubai Customs (Ports, Customs and Free Zone Corporation)
Period
Ongoing; results reported January–May 2026
Keywords
customs, law enforcement, trade facilitation, artificial intelligence

Context

Dubai Customs, part of the Ports, Customs and Free Zone Corporation, built an in-house Smart Risk Engine that applies AI and big-data analysis to millions of shipment records to flag high-risk cargo before physical inspection.

Objectives

The engine aims to intercept smuggled narcotics and other contraband earlier by feeding risk scores into the Siyaj border-monitoring and Shahin cargo-inspection programmes.

Activities

Siyaj combines AI with detection equipment, patrol vehicles and canine units, while Shahin applies smart technologies to cargo inspection, together forming the operational response to the engine's flags.

Results

Officials say the system helped seize 406kg of narcotics and 2.3 million illicit pills across 502 anti-smuggling operations in the first five months of 2026, including a separately reported AI-flagged case that led to 278,850 pregabalin tablets seized and four arrests.

Conclusions

Available reporting names officials and headline seizure totals but does not disaggregate how many interceptions came specifically from AI risk-scoring as opposed to K9 units or routine inspection, nor does it describe an external audit or an appeals process for flagged shipments.

Implementation
Indicative cost
High (€500k–€5M)
Time to results
Medium (1–3 years)
Staffing & skills
Dubai Customs / Ports, Customs and Free Zone Corporation leadership (Abdullah Bin Damithan, Abdulla Busenad, Mohammed Al Ghaffari), in-house AI/data-analytics team, canine units and patrol personnel under the Siyaj programme

Conditions for success

  • integration of the Smart Risk Engine with existing border-monitoring (Siyaj) and inspection (Shahin) programmes
  • access to millions of shipment records for risk scoring

Common failure modes

  • no external audit, published technical documentation, or appeals process for flagged shipments is described
  • reported seizure figures are not disaggregated between AI-driven flags and other methods (K9 units, routine inspection)

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

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