Transforming Malaysia’s Food Safety Landscape Through Smart Regulation and AI Integration
Food safety has become a growing concern in Malaysia, with an increasing number of food poisoning and foodborne illness cases reported each year. Although the country is governed by the Food Act 1983 and the Food Regulations 1985, enforced by the Ministry of Health Malaysia (MOH), the reality is that incidents of food contamination continue to occur frequently.
According to the MOH Annual Food Safety Report, the number of food premises ordered to close rose from 1,300 in 2022 to 1,650 in 2024. This statistic demonstrates that food safety problems are no longer isolated incidents but have evolved into systemic challenges affecting all levels of the food industry — from luxury restaurants to roadside stalls.
In several countries such as South Korea and Singapore, data-driven and artificial intelligence (AI)-based approaches are used to predict and prevent food contamination risks — a model that Malaysia could emulate. Looking ahead, improving food safety in Malaysia should involve strengthening enforcement integrity, reforming outdated laws, and empowering consumer rights.
Food safety encompasses every stage of the food process — from preparation, handling, to storage — that must be strictly observed by food producers and entrepreneurs. Its primary goal is to protect consumers from various foodborne hazards, including physical, chemical, and biological risks, throughout the food supply chain, from farm to table. Local authorities (PBT) must also be mobilized comprehensively, as many cases of contaminated food occur at small-scale premises such as street stalls and home kitchens.
In Malaysia, various food safety standards and regulations have been established, with the Food Safety and Quality Division (FSQD) under the Ministry of Health serving as the main body responsible for food safety control. Through frameworks such as the Food Act 1983 and Food Regulations 1985, the FSQD ensures nationwide compliance with food safety standards.
Among the FSQD’s key responsibilities are the implementation of national compliance projects, administration of food exports, pre-market approvals, food poisoning prevention activities, consumer communication, and public engagement. Hence, it is important to recognize that FSQD plays a critical role in reviewing, assuring quality, and evaluating the enforcement of food safety monitoring measures.
Although the FSQD under the MOH already monitors food quality from farm to table, further improvements are still necessary.
One of the main recommendations is to strengthen the powers of Local Authorities (PBT).
Enforcement officers should be trained to utilize AI technology and computer simulations to enhance their ability to handle real-life scenarios. AI can also be used to identify high-risk locations or premises that are prone to food safety violations.
Additionally, the MOH could develop a Secure Online Complaint System.
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A mobile application could be introduced to allow the public to lodge complaints by uploading photos or videos of food premises. AI technology could assist in detecting hygiene issues from the submitted images. Furthermore, the MOH could implement Digital Food Handler Training, where food safety courses are conducted online using AI that adapts learning content according to each participant’s level of understanding.
The integration of artificial intelligence (AI) into Malaysia’s food safety monitoring system represents a transformative shift in regulatory governance.
As the nation faces increasing reports of foodborne illnesses and contamination, traditional inspection methods—often manual, time-consuming, and reactive—are proving insufficient to address modern challenges in a complex food supply chain. AI-based monitoring provides a proactive and data-driven solution capable of predicting, detecting, and preventing food safety risks before they escalate into public health crises.
In the context of food safety enforcement, AI systems can analyze large datasets obtained from inspection records, consumer complaints, laboratory tests, and even social media platforms to identify patterns or anomalies that suggest potential contamination. For instance, predictive algorithms can forecast high-risk areas or premises based on environmental conditions, supply chain data, and previous non-compliance history. This allows the Food Safety and Quality Division (FSQD) and local authorities (PBT) to prioritize inspections, allocate resources efficiently, and respond more swiftly to emerging threats.
Moreover, AI-powered image recognition and computer vision technologies can be deployed through mobile applications or surveillance systems to detect hygiene violations in real time. Food handlers and enforcement officers can use handheld devices or smart cameras to assess the cleanliness of kitchens, utensils, and food storage facilities. Through deep learning, the AI system can automatically identify irregularities such as improper food handling, cross-contamination risks, or pest presence—alerting authorities instantly and supporting evidence-based enforcement actions.
Food safety is not merely a public health issue, but also a fundamental human right.
In Malaysia, food safety laws must uphold this principle — that every plate of food represents a trust to protect the health of the people.
MSU aligns with this modern development by offering TVET programs that integrate AI technology with hygiene and food safety aspects. Through these programs, students are trained to use AI to monitor the cleanliness of food premises, detect contamination risks, and analyze public health data to prevent foodborne diseases. This approach not only enhances technical competence but also supports the nation’s effort to ensure safe and high-quality food for all Malaysians.
By
Dr. Angelina Anne Fernandez,
Senior Lecturer,
Faculty of Business Management and Professional Studies,
Management and Science University
