AI新創企業危機驅動之策略轉型研究 —以盛星科技為例

Abstract

本研究以盛星科技股份有限公司（Astra Inc.）為個案，探討一家台灣AI新創企業在新冠肺炎疫情衝擊下，如何從高度依賴單一通路夥伴的B2B2B間接銷售模式，轉型為直接面對終端客戶的 B2B SaaS服務商。盛星科技自 2017年起透過日本NTT East作為唯一通路夥伴銷售雲端人臉辨識服務，2020年疫情導致跨國服務鏈全面斷裂，迫使公司啟動一場「被迫型樞紐轉向」（forced pivot），建立自有品牌GoFace，直接服務多元產業客戶。 本研究採用單一個案研究法，以研究者兼創辦人之參與觀察及公司內部次級資料為基礎，透過時間序列分析與主題分析法，深入解析轉型的決策過程、執行路徑與成效。研究發現：第一，疫情對盛星而言是「觸發因子」而非「加速因子」，轉型本質為通路結構的根本重構，而非營收模式的轉換，因其自始即採用 SaaS 訂閱制；第二，公司透過「固定成本最小化、浮動成本最大化」的經營哲學，搭配非核心職能外部化、績效導向薪酬體系與 AI 自動化工具的深度嵌入三重機制，以約十六人的精簡團隊服務超過一千五百家2B客戶，實現「極端精實化」的組織型態；第三，2019年啟動的軟硬體脫勾探索構成了危機中快速轉型的「數位基礎能力」。 在學術意涵上，本研究的主要貢獻在於整合既有的策略樞紐轉向（Ries, 2011）、商業模式畫布（Osterwalder & Pigneur, 2010）、AI 賦能管理（Davenport & Ronanki, 2018）與組織韌性（Duchek, 2020）等理論視角，以單一深度個案分析方式，刻畫一種「危機驅動下、由間接 SaaS 模式轉向直接 SaaS 模式」的轉型路徑，並具體呈現AI自動化工具如何在中小企業情境下支撐「極端精實化」組織型態之運作機制與其先決條件。在實務層面，本研究為台灣中小企業提出降低通路集中度風險、以訂閱制建立財務韌性、以固定成本最小化強化抗風險彈性、以AI自動化突破人力瓶頸等四項策略建議。

This study examines how Astra Inc., a Taiwanese AI startup specializing in facial recognition technology, executed a crisis-driven strategic pivot from a B2B2B indirect sales model—relying solely on NTT East as its channel partner—to a B2B SaaS provider serving end customers directly under its own GoFace brand. The COVID-19 pandemic severed the company's sole cross-border service channel in 2020, forcing the management team to fundamentally restructure its business model within an extremely compressed timeframe. Employing a single case study methodology grounded in participant observation by the founder-researcher and secondary data from internal company documents, this research applies chronological analysis and thematic analysis to trace the decision-making process, execution path, and outcomes of the transformation. Three key findings emerge. First, the pandemic served as a “trigger” rather than an “accelerator,” as the core transformation involved restructuring the channel architecture rather than shifting revenue models—Astra had operated under a SaaS subscription model from the outset. Second, through a management philosophy of “minimizing fixed costs and maximizing variable costs,” combined with three reinforcing mechanisms—outsourcing non-core functions, performance-based compensation, and deep integration of AI automation tools—the company achieved “extreme lean transformation,” serving over 1,500 clients with a lean team of approximately 16 employees. Third, the hardware-software decoupling initiative launched in 2019 constituted the “digital baseline capability” that enabled rapid transformation during the crisis window. The academic significance of this study lies in its integration of multiple theoretical lenses—including strategic pivot (Ries, 2011), business model canvas (Osterwalder & Pigneur, 2010), AI empowerment (Davenport & Ronanki, 2018), and organizational resilience (Duchek, 2020)—to analyze, through an in-depth single case study, a crisis-triggered transformation path from an indirect SaaS model to a direct SaaS model, and to articulate how AI automation tools sustain an “extreme lean” organizational form within an SME context. Practical implications include four strategic recommendations for Taiwanese SMEs: diversifying channel concentration risk, building financial resilience through subscription revenue, minimizing fixed costs for structural flexibility, and leveraging AI automation to overcome workforce scaling constraints.