IJCA Vol 4 i1 2025 webmag - Flipbook - Page 37
2025 | Volume 4, Issue 1
The AI system, based on machine learning models,
analyzed quality control data—including product
size, pesticide residue levels, and visual defects—to
certify compliance with stringent EU standards.
Implemented by the Egyptian Ministry of Trade and
Industry in collaboration with local agribusinesses, the
system processed inspection data in real-time. As a
result, compliance with EU regulations increased by
10%, and certi昀椀cation processing times were reduced
by 15%, enabling faster export approvals.
However, the rollout faced several challenges.
Inconsistent regional data from rural farms
led to delays, exposing weaknesses in the
national data infrastructure. Additionally,
exporters expressed concern over the lack
of explainability in AI decision-making,
emphasizing the need for greater transparency
to maintain trust with international buyers.
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outputs to ensure decisions are context-aware and
reliable [18].
Develop explainable AI models
Transparent systems like SHAP (SHapley Additive
exPlanations) clarify AI-driven decisions, promoting
fairness and accountability—especially in evolving
regulatory environments—while also requiring
technical capacity for effective implementation [19].
Invest in regional data infrastructure
Improving digital infrastructure in MENA and CIS
countries is essential for effective AI deployment.
Initiatives like the UAE’s Smart Dubai provide a model
for strengthening regional data ecosystems [20].
Enhance collaboration
Ongoing collaboration between AI developers,
regulators, and conformity assessment bodies can
support the development of region-speci昀椀c solutions.
This case illustrates AI’s potential to streamline
certi昀椀cation and improve e昀케ciency in the MENA
region’s agricultural exports, while also highlighting
the importance of data quality and transparency in
building stakeholder con昀椀dence.
Establish ethical guidelines
Recommendations for a Balanced Approach
Conclusion
To help overcome the challenges associated with AI
integration in conformity assessment, the following
strategies are recommended:
AI has the capacity to reshape the 昀椀eld of conformity
assessment—improving fairness, streamlining
processes, and increasing consistency, particularly
in regions like MENA and CIS. The case studies
on UAE manufacturing and Egyptian agricultural
exports illustrate AI’s practical bene昀椀ts when applied
thoughtfully.
Incorporate human oversight
AI should support—not replace—human expertise.
Auditors and assessors should validate AI-generated
Applying ethical frameworks—such as UNESCO’s
AI Ethics Recommendation—can promote fairness,
transparency, and accountability in AI-driven
assessments [21].
