## Leveraging Artificial Intelligence and Machine Learning to Enhance Customs Operations

## Source details

**Canonical URL:** [Leveraging Artificial Intelligence and Machine Learning to Enhance Customs Operations](https://www.imf.org/en/capacity-development/training/icdtc/schedule/sa/2026/cadsa26-36)

## Other formats

- [Markdown version](/en/capacity-development/training/icdtc/schedule/sa/2026/cadsa26-36/index.md)
- [Structured JSON version](/en/capacity-development/training/icdtc/schedule/sa/2026/cadsa26-36/index.json)
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## Bibliographic details
- Session: SA 26.36
- Location: New Delhi, India
- Dates: September 14-18, 2026 (1 week)
- Delivery method: In-person Training
- Primary language: English
- Status: Deadline passed

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### Event overview and eligibility
- Event title: Leveraging Artificial Intelligence and Machine Learning to Enhance Customs Operations
- Session No.: SA 26.36
- Location: New Delhi, India
- Date: September 14-18, 2026 (1 week)
- Delivery Method: In-person Training
- Primary Language: English
- Qualifications: Open only to senior customs and ICT experts from Bangladesh, Bhutan, Cambodia, Fiji, India, Maldives, Mongolia, Nepal, Sri Lanka, and Vietnam, who are working in their respective country's administration.
- Target Audience: Senior customs and ICT experts involved in digitalization, technology management, modernization, policy and operations in their country's administration.

### Training purpose and strategic focus
- Aim: Support selected Asia-Pacific economies in advancing digital transformation and strengthening data-driven decision making in customs.
- Strategic emphasis:
  - Practical pathways for developing and implementing AI strategies in customs operations.
  - Moving from concept to implementation, including identifying investment priorities and resource requirements across financial, technological, and human dimensions.
  - Supporting tailored AI strategies that account for uneven AI adoption and gaps in infrastructure, skills, and integration across the region.

### Applications, analytical themes, and implementation challenges
- Applications explored:
  - AI in risk management.
  - AI in trade facilitation.
  - AI in compliance.
- Key implementation challenges addressed:
  - Data quality.
  - Interoperability.
  - Governance frameworks.
  - Resource constraints (financial, technological, and human).

### Pedagogy and participant engagement
- Learning methods:
  - Interactive discussions.
  - Country presentations.
  - Group exercises.
- Expected participant outputs:
  - Exchange of experiences across participating administrations.
  - Development of actionable roadmaps and implementation plans.

### Course objectives and outcomes
- On completion, participants will be able to:
  - Understand how to design tailored AI strategies from concept to implementation;
  - Identify pathways for developing and implementing AI strategies in customs operations;
  - Better understand applications of AI in risk management, trade facilitation, and compliance, and how to approach challenges (e.g., data quality); and
  - Develop actionable plans to implement AI strategies.

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## References

- [In-person Training](https://www.imf.org/en/capacity-development/training/icdtc/delivery-methods)
- [Core Elements of Banking Supervision (CBS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2027/cbsat27-10)
- [Advanced Government Finance Statistics (GFS-A)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/gfs-ace26-45)
- [Fiscal Sustainability (FS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/fsce26-38)
- [Safeguards Assessments of Central Banks (SAC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/sacat26-30)
- [Macroeconomic Management in Resource Rich Countries (MRC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/mrcce26-44)

_Source: https://www.imf.org/en/capacity-development/training/icdtc/schedule/sa/2026/cadsa26-36_