Excessive Costs and Personal Data Security: Challenges for Taiwan's Smart Retail and Smart Healthcare
In recent years, smart retail has emerged and achieved initial results 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 enhancing user experience. However, due to the high cost of smart retail equipment, small and medium-sized retailers face barriers to technology adoption, and it will take time for some consumers to fully accept unmanned services.
(Section Title) High technology costs hinder promotion
But 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 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 functions, allowing customers to complete purchases directly in the application and then pick up items in designated areas of the store, bypassing traditional checkout processes. This innovation not only improves shopping efficiency but also enhances the customer experience, leading to a 15% increase in sales in related IKEA stores in the first half of 2024.
In Taiwan, a convenience store chain successfully reduced labor costs by approximately 20% by introducing an unmanned checkout system. However, unfortunately, due to the high installation costs 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 high equipment costs, especially for small and medium-sized retailers with limited capital, forming a major obstacle. Furthermore, current AI and IoT systems still need further optimization in terms of stability, and consumer usage habits and acceptance are also important factors in promoting the full普及 of smart retail.
(Section Title) 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 smart technology. Smart healthcare in Taiwan is hoped to become the next "guardian mountain" and a world-class industry, with medical institutions, ICT giants, and academia actively vying for it. Significant progress has been made in related developments, particularly in early cancer diagnosis and chronic disease management, achieving considerable results.
The Endoscopy Diagnosis and Treatment Center at Taipei Veterans General Hospital combines AI technology to develop an intestinal endoscopy multimodal assisted diagnosis system, which can increase the accuracy of early colorectal cancer diagnosis to 90%, significantly improving diagnosis and treatment efficiency. However, medical data standardization and privacy protection issues 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 providing more precise and timely health management services for patients with diabetes, chronic diseases, and multiple conditions. These advancements are mainly 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, based on AI analysis results, proactively sends health risk warnings to patients. For example, if a patient's blood sugar data shows abnormal fluctuations, the platform will immediately send automated suggestions and notify the medical team for further intervention. This function has reduced patient hospitalization rates by 35%, further lowering overall medical expenditures, far exceeding the previous 30% savings rate.
Furthermore, Livongo Health has deepened cooperation with major US health insurance companies and medical systems, 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 achieved a high satisfaction rate of 92% in user satisfaction surveys.
In Taiwan, a health technology company has also launched health management services to help chronic disease patients predict health risks. However, due to unresolved issues with the standardization of health insurance data, the 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 hospital information systems (HIS) to improve practicality.