Admission
AI Commercialization Model Innovation in Indonesian Critical Mineral Economy

    Eligibility: International graduates from AACSB accredited business school with the required entry requirements
    Duration: Full-Time – between three and four years fixed term
    Application deadline: 28 April 2026
    Interview date: Will be confirmed for shortlisted candidates
    Start date: August 2026

    For further details, contact

    Introduction

    This study investigates the commercialization pathways of artificial intelligence (AI) technologies within the context of the Indonesian critical mineral economy, by examining the processes and conditions that enable AI innovations can transition from technological development to scalable industrial applications. The increasing global demand for critical minerals such as nickel, cobalt, and rare earth elements has positioned Indonesia as a strategic player in global supply chains, while advances in Artificial Intelligence offer significant opportunities to enhance efficiency, sustainability, and value-added creation across mining and mineral processing activities. However, despite rapid technological progress, many AI innovations in the mining sector struggle to achieve successful commercialization due to organizational limitations, high capital intensity, regulatory complexity, and fragmented industry ecosystems. This challenge is particularly evident in Indonesia, where the expansion of the critical mineral industry is not fully supported by the readiness of firms and institutions to adopt and scale AI-based solutions, and where existing studies tend to separate technological development from market adoption, leaving a gap in understanding end-to-end commercialization processes.

    To address this gap, the research adopts an integrated perspective that combines technology commercialization theory, dynamic capabilities, and innovation ecosystem approaches. The study conceptualizes AI commercialization as a multi-stage and multi-actor process involving technological readiness, organizational capability, market alignment, and ecosystem collaboration. Particular attention is given to how business model innovation enables AI technologies to create value within the Indonesian Critical Mineral economy, which is currently characterized by rapid industrial expansion driven by down-streaming (hilirisasi) policies, increasing global demand, and growing investment in processing capabilities, yet it continues to face challenges related to technological readiness, ecosystem coordination, and value optimization. By examining how these factors interact and evolve throughout the commercialization journey, the research aims to identify the mechanisms operating across macro, meso, and micro levels that contribute to the development of an integrated AI ecosystem facilitating the commercialization of AI technologies in the mining sector. The findings are expected to provide strategic insights for policymakers, mining companies, and technology providers in designing adaptive and effective AI commercialization strategies, thereby supporting the sustainable development of Indonesia’s critical mineral economy.

    • Project details

      The PhD student will conduct theoretical and empirical research on the commercialization dynamics of artificial intelligence technologies and the role of business model innovation in enabling successful market deployment within the Indonesian Critical Mineral Economy. Possible research directions include:

      • Despite rapid growth in artificial intelligence development, many AI innovations in emerging economies such as Indonesia face challenges in transitioning from technological capability to sustainable commercial applications.
      • The commercialization of AI technologies is influenced by multiple interacting factors, including technological readiness, organizational capabilities, regulatory environments, market demand, and the maturity of the digital innovation ecosystem.
      • In the Indonesian Critical Mineral Economy, firms and startups often experiment with new business models to capture value from AI technologies, highlighting the critical role of business model innovation in bridging the gap between technological innovation and market adoption.
      • Existing technology commercialization frameworks frequently examine technological, organizational, and market factors independently, offering limited insights into how these elements interact in emerging digital economies.
      • There is a requirement to identify how different configurations of technological capability, business model innovation, market conditions, and ecosystem support influence the success or failure of AI commercialization within Indonesia’s rapidly evolving digital economy.
      • A comprehensive analytical framework is required to explain how organizations design and adapt business models, orchestrate technological resources, and leverage ecosystem partnerships to enable scalable AI commercialization in the Indonesian Critical Mineral Economy.

      Funding
      Tuition fees and bursary from LPDP, PDDI or potentially ITB/CU (separate application).

      Benefits
      The successful candidate will receive comprehensive research training including technical, personal, and professional skills. All researchers at SBM ITB & Coventry University (from PhD to Professor) are part of the Doctoral and Researcher College, which provides support with high-quality training and career development activities.

      Entry requirements

      • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60 overall module average.

      PLUS

      • The potential to engage in innovative research and to complete the PhD within 3-4 years.
      • A minimum of English language proficiency (IELTS academic overall minimum score of 6.5 with a minimum of 6.0 in each component).

      Additional Requirements

      Applicants should hold a good master’s degree in management science, business administration, AI management, or a related discipline. Relevant background may include:

      • Familiarity with AI-assisted research tools and digital knowledge systems, demonstrating the ability to leverage emerging technologies for research and innovation development.
      • Strong methodological capabilities in quantitative and qualitative research, including tools such as PLS-SEM, fsQCA, NVivo, R, or similar analytical methods used in innovation and management research.
      • Experience in system dynamics modeling and simulation using tools such as Vensim, particularly for analyzing innovation systems, digital ecosystems, or technology commercialization processes.
      • Academic or professional experience in innovation ecosystems, digital entrepreneurship, or technology commercialization, particularly in emerging digital economies.
      • Demonstrated experience in research on digital transformation, AI governance, or digital economy development, including involvement in applied research projects related to AI, digital platforms, or technology-driven industries.
      • Experience in business model innovation and entrepreneurial ecosystem analysis, particularly in the context of startups, MSMEs, or digital innovation ecosystems.
      • Established professional networks across academia, industry, and policy institutions, facilitating access to key stakeholders within the Indonesian digital entrepreneurship and innovation ecosystem.
      • Practical exposure to consulting, policy research, or industry collaboration, particularly in projects related to technology policy, digital economy development, or innovation strategy.

      The ideal candidate will be highly motivated, methodologically skilled, and interested in studying AI commercialization and business model innovation within the Indonesian Critical Mineral Economy, including the role of startups, digital platforms, and innovation ecosystems in enabling scalable AI-driven economic development.

      For more information on the application requirements for ITB, click here, and for Coventry University, click here.

      Please contact for informal inquiries: Prof. Wawan Dhewanto, Ph. D (Institut Teknologi Bandung), Dr. Mujahid Mohiuddin Babu (Coventry University) and Dr. Sahat Hutajulu (Institut Teknologi Bandung)