生成式AI訂製珠寶服務創新商業模式—以Olivia Yao Jewellery為例

本研究以獨立設計珠寶品牌 Olivia Yao Jewellery(OYJ)為案例，探討如何運用生成式人工智慧(AIGC)技術優化其訂製珠寶服務，並建立創新商業模式。隨著全球訂製珠寶市場的快速成長，特別是在亞太地區，消費者需求逐漸從標準化產品轉向個性化、高參與度的訂製服務。尤其千禧世代及Z世代的崛起，更推動了具有故事性、互動性及情感價值的珠寶需求。為因應市場需求並解決現有高級訂製服務成本高、流程冗長的問題。 OYJ自2020年起推出高級訂製服務，成為品牌營收的重點項目。然而，現行訂製流程高度依賴專業珠寶設計師，導致成本高昂且服務供應受限，難以觸及中低價市場，高價的設計人力也難以配置於所有門市並發揮專業性，形成訂製客群與一般消費者的斷層。因此，OYJ希望透過AIGC技術降低人事成本、提升流程效率，並擴展中低價位的日常訂製市場。本研究結合文獻資料收集、田野調查與市場測試。首先，針對領域進行現有AI技術及市場趨勢、產業應用案例並分析競爭優勢作為，開發AIGC技術原型知識基礎。並透過波特五力分析探討珠寶訂製市場的競爭環境，並運用STP模型進行市場區隔與定位。其次，進行品牌內部訪談與消費者調查，了解現有流程的痛點與需求。研究團隊開發最小可行性產品(MVP)，透過門市試點與問卷調查收集市場反饋，並建立財務預估模型，評估新商業模式的潛力。全球訂製珠寶市場正處於快速增長期，預計未來五年內複合年增長率將達到7.4%。亞太市場，特別是台灣，因消費者對個性化與情感價值的重視，已成為訂製服務的重要市場。千禧世代與Z世代的消費行為顯示，他們更注重設計的獨特性及品牌形象，而非傳統的材質價值，這為中低價位的日常訂製市場帶來巨大潛力。然而，訂製服務涉及複雜的溝通與高人力成本，成為市場發展的主要障礙。 OYJ引入AIGC技術，目標是將訂製流程數位化、模組化，降低人力需求並縮短生產周期。具體應用包括：透過AI輔助生成擬真設計圖，減少討論與擬真照片渲染時間的圖像生成技術、使非專業門市人員也能協助基本訂製洽談的AIGC工具最終透過AI自動化生成模組，將訂製服務擴展到一般門市，實現訂製服務的中低價市場滲透。研究團隊透過小規模市場測試，收集消費者的反饋，結果顯示AI輔助訂製流程在效率與滿意度上有顯著提升。消費者對快速生成的設計圖與靈活的訂製選項反應正面，顯示市場對AIGC應用於珠寶訂製具有高度接受度。透過AIGC技術，傳統珠寶品牌可以有效降低訂製服務成本，拓展中低價市場並提升整體競爭力。未來，隨著技術的成熟與市場驗證的深化，OYJ計畫將AIGC訂製服務推廣至所有門市，甚至未來有機會發展成為線上化的訂製平台，建立完整的數位訂製生態系統。

關鍵字

人工智慧；生成式人工智慧；生成式AI ； AIGC ； Stable Diffusion ； AI應用； Olivia Yao Jewellery ； OYJ ；客製化珠寶；訂製珠寶

並列摘要

This study focuses on the independent jewelry design brand Olivia Yao Jewellery (OYJ) as a case study to explore how generative artificial intelligence (AIGC) technology can optimize its custom jewelry services and establish an innovative business model. With the rapid growth of the global custom jewelry market, particularly in the Asia-Pacific region, consumer demand is shifting from standardized products to personalized, high-engagement custom services. The rise of the millennial and Generation Z cohorts has further driven the demand for jewelry that carries stories, interactivity, and emotional value. This shift presents challenges for high-end custom services due to high costs and lengthy processes. Since 2020, OYJ has launched high-end custom services, becoming a key revenue driver for the brand. However, the current custom process heavily relies on skilled jewelry designers, resulting in high costs and limited-service capacity, making it difficult to reach the mid-to-low price market. The high expense of design personnel also makes it impractical to deploy them across all stores, creating a disconnect between custom clientele and regular consumers. Therefore, OYJ aims to leverage AIGC technology to reduce labor costs, improve process efficiency, and expand into the mid-to-low price segment for everyday custom jewelry. This study combines literature review, field research, and market testing. Initially, it investigates current AI technologies, market trends, and industry case studies to develop a foundational understanding for creating an AIGC technology prototype. Using Porter’s Five Forces analysis, it examines the competitive landscape of the custom jewelry market and employs the STP (Segmentation, Targeting, Positioning) model for market segmentation and positioning. Furthermore, internal brand interviews and consumer surveys identify pain points and needs within the current process. The research team develops a Minimum Viable Product (MVP), conducts pilot tests in stores, collects market feedback through surveys, and builds a financial projection model to evaluate the potential of the new business model. The global custom jewelry market is experiencing rapid growth, with a projected compound annual growth rate (CAGR) of 7.4% over the next five years. The Asia-Pacific market, especially Taiwan, has become a key region for custom services due to consumers’ emphasis on personalization and emotional value. The purchasing behaviors of millennials and Generation Z indicate a preference for unique designs and brand identity over traditional material value, highlighting significant potential in the mid-to-low price segment for everyday custom jewelry. However, the complex communication and high labor costs associated with custom services remain major barriers to market development. OYJ aims to digitalize and modularize the custom process using AIGC technology, reducing labor requirements and shortening production cycles. Specific applications include AI-assisted generation of realistic design images, which reduces the time needed for discussions and photo rendering. Additionally, AIGC tools enable non-specialist store staff to assist with basic custom consultations. Ultimately, AI-automated modules will expand custom services to regular stores, penetrating the mid-to-low price market for custom jewelry. The research team conducted small-scale market tests, gathering consumer feedback that demonstrated significant improvements in efficiency and satisfaction with AI-assisted custom processes. Consumers responded positively to quickly generated design images and flexible custom options, indicating strong market acceptance of AIGC technology in jewelry customization. Through AIGC, traditional jewelry brands can effectively lower custom service costs, expand into mid-to-low price markets, and enhance overall competitiveness. As technology matures and market validation deepens, OYJ plans to extend AIGC-enabled custom services to all stores and potentially develop an online virtual customization platform, creating a comprehensive digital custom ecosystem in the future.

並列關鍵字

Artificial Intelligence ； AI ； Generative Artificial Intelligence ； AIGC ； Stable Diffusion AI applications ； Olivia Yao Jewellery ； OYJ ； Customized jewelry ； Personalized jewelry