High costs and personal data security challenge Taiwan's smart retail and smart healthcare.
In recent years, smart retail has emerged and achieved initial success in Taiwan's retail industry, particularly in the promotion of unmanned stores and electronic payment systems.
Some convenience stores in Taiwan have introduced AI-powered checkout systems, significantly reducing customer waiting times and improving user experience. However, due to the high cost of smart retail equipment, small and medium-sized retailers face a barrier to technology adoption, and the acceptance of unmanned services by some consumers still needs time to improve.
(Section Heading) High technology costs lead to difficulties in promotion
So, how can smart retail be successfully implemented? Learning from good examples and drawing on successful experiences is the best way for Taiwanese business owners to hone their skills and improve themselves. For example, IKEA in Europe launched a new smart shopping experience in 2024, introducing AI-powered shopping assistant systems in some of its stores. Through a mobile application, customers can scan products, obtain detailed information, and receive personalized product recommendations.
In addition, IKEA has integrated mobile payment functionality, allowing customers to complete purchases directly within the app and then pick up their items at designated areas in the store, bypassing the traditional checkout process. This innovation not only improves shopping efficiency but also enhances the customer experience, leading to a 15% increase in sales at these IKEA stores in the first half of 2024.
In Taiwan, a convenience store chain has successfully reduced labor costs by approximately 20% by introducing unmanned checkout systems. Unfortunately, due to the high installation cost of IoT equipment, this model has not yet been fully implemented across Taiwan and can only be piloted in high-traffic urban core areas.
Therefore, the promotion of smart retail is constrained by the high cost of equipment, which constitutes a major obstacle, especially for small and medium-sized retailers with limited capital. Furthermore, the stability of current AI and IoT systems still needs further optimization, and consumer usage habits and acceptance are also important factors in promoting the widespread adoption of smart retail.
(Section Heading) Privacy protection and data sharing become challenges for smart healthcare
In addition to the retail industry's smart transformation, the medical field is also closely integrated with intelligence. Smart healthcare in Taiwan is hoped to become the next "sacred mountain protecting the nation" and a world-class industry. Medical institutions, ICT manufacturers, and academia are actively rushing in, and related developments have made significant progress, especially in early cancer diagnosis and chronic disease management, achieving considerable results.
The Endoscopy Diagnosis and Treatment Center of Taipei Veterans General Hospital has combined AI technology to develop a multimodal auxiliary diagnosis system for gastrointestinal endoscopy, which can increase the accuracy of early colorectal cancer diagnosis to 90%, significantly improving diagnostic and treatment efficiency. However, the standardization of medical data and privacy protection remain two major challenges facing the industry.
Livongo Health, a digital company for chronic disease management, is a classic and continuously evolving international case in the field of smart healthcare that Taiwan can learn from.
Since 2024, Livongo Health's smart management platform has continuously upgraded its AI algorithms, specifically targeting patients with diabetes, chronic diseases, and multiple conditions, to provide more precise and timely health management services. These advances are primarily due to the integration of larger datasets and high-performance AI models, enabling the platform to extract deeper health insights from patients' daily behaviors and real-time physiological data.
In 2024, Livongo Health introduced an "active intervention model." This model not only passively tracks patient data but also proactively sends health risk warnings to patients based on AI analysis results. For example, if a patient's blood sugar data shows abnormal fluctuations, the platform will immediately send automated recommendations and notify the medical team for further intervention. This feature reduced patient hospitalization rates by 35%, further lowering overall medical expenditures, far exceeding the previous 30% savings rate.
In addition, Livongo Health has deepened cooperation with major health insurance companies and healthcare systems in the United States, including Kaiser Permanente and Anthem Health, achieving closed-loop data sharing among patients, insurance companies, and healthcare providers. Through this synergy, the platform has successfully expanded into more chronic disease areas, including cardiovascular disease and kidney disease management, and has achieved a high satisfaction rate of 92% in user satisfaction surveys.
In Taiwan, a health technology company has also launched health management services to assist chronic disease patients in predicting health risks. However, due to the unresolved issue of National Health Insurance data standardization, this service still faces challenges in data integration and application efficiency.
The application of data in the field of smart healthcare requires finding a balance between individual privacy protection and data sharing efficiency. In addition, medical AI systems need to be seamlessly integrated with diverse medical information systems (HIS) to improve practicality.