Globalizing Intelligence: Orchestrating Artificial Intelligence for Global Advantage

Editors

• Julian Birkinshaw, Ivey Business School
• Valérie Duplat, Vrije Universiteit Amsterdam
• Saeed Khanagha, Vrije Universiteit Amsterdam
• Oli Mihalache, Athabasca University
• Shaker Zahra, University of Minnesota

Description

Artificial intelligence is fundamentally reshaping how multinational enterprises and international new ventures compete globally. This special issue seeks research exploring how AI technologies—particularly generative AI—enable new competitive strategies, from building proprietary AI capabilities to deploying AI tools for market analysis and decision-making. The call welcomes papers examining AI's impact on firm competitiveness, internationalization strategies, organizational transformation, and resilience in volatile environments.

The issue addresses three core dimensions through which AI influences global strategy. First, it considers how firms develop AI-centric capabilities that serve as sources of competitive advantage across borders. Second, it explores how organizations strategically deploy AI to interpret global markets and make faster, more informed decisions. Third, it examines how firms must redesign governance structures and navigate complex international regulatory frameworks to effectively harness AI across multiple countries and institutional contexts.

Potential topics

• How do proprietary generative-AI capabilities influence entry mode choice in different host-country contexts?
• What factors affect location for AI-centric MNEs and INV founders seeking global scale?
• How do AI-centric firms calibrate the balance between global standardization of models and local adaptation to institutional and cultural distance?
• How do AI-centric INVs build and scale proprietary capabilities to compete globally, and how do these digital-born assets challenge traditional views on firm-specific advantages and gradual internationalization?
• How do AI-centric MNEs and INVs manage international scaling of generative-AI capabilities, and what role do global knowledge-transfer mechanisms play in enabling rapid diffusion across subsidiaries?
• How do AI-centric MNEs manage cross-border complementarities between firm-specific data and host-country capabilities to build sustainable competitive advantage?
• To what extent do open-core versus fully proprietary model strategies shape the boundary decisions (make, buy, ally) of AI-centric firms in different regulatory environments?
• How do AI-centric firms mitigate liability of foreignness in AI ethics and bias by embedding local data and diverse cultural inputs into their global model-training pipelines?
• How can AI-enabled research methods be leveraged by firms to better understand foreign market reception and inform internationalization strategies?
• How do MNEs use generative-AI tools to refine entry-mode strategies (i.e., exporting, licensing, or FDI) by dynamically assessing host-market demand and regulatory complexity?
• Under what conditions can AI-driven scenario planning replace or complement traditional market-selection frameworks (e.g., CAGE) for entering new countries?
• How do firms leverage generative-AI-enabled localization (e.g., product design, marketing copy) to navigate cultural distance and strengthen local responsiveness in global integration strategies?
• What capabilities must regional subsidiaries develop to interpret and act on AI-generated market insights, and how does this reshape subsidiary autonomy versus headquarters control?
• How does generative AI affect the integration-responsiveness trade-off in global operations under geopolitical or natural-disaster shocks?
• In what ways do AI-mediated customer-interaction platforms alter traditional service subsidiary roles and the governance of cross-border service delivery?
• How do firms combine human judgment and AI recommendations in cross-border new product development alliances to balance exploration and exploitation?
• How do AI-enabled INVs sense and respond to global market signals differently than incumbents, and how do AI tools help them to overcome limited experience in culturally or institutionally distant markets?
• In what ways do AI-driven analytics of cultural signals and media content reshape how MNEs and INVs interpret foreign consumer preferences and adapt entry strategies?
• How can methodological advances in AI-based content analysis contribute to more fine-grained monitoring of cultural distance and liability of foreignness in real time?
• How do MNEs structure global AI governance bodies to balance headquarters-led oversight with subsidiary-level discretion across divergent institutional environments?
• What alliance governance mechanisms (joint ventures, co-development agreements) best facilitate GDPR-compliant data-sharing for generative-AI co-creation between European and Asian partners?
• How do emerging global AI regulations reshape MNEs' decisions on center-of-gravity for model deployment (cloud vs. on-prem) across host countries?
• How do entrepreneurial ecosystems in emerging markets influence the design of cross-border data trusts and co-governance structures for INV-led AI initiatives?
• How do platform partnerships with regional software ecosystems (e.g., Midjourney in European design suites, Eleven Labs in Asian media platforms) alter inter-firm governance and value-capture?
• In what ways do pre-competitive data trusts and industry consortia mitigate institutional voids and enable co-governance of domain-specific generative models in emerging markets?
• How must performance metrics and incentive systems evolve to reward cross-border AI collaboration while managing moral-hazard and knowledge-leakage risks?
• What role do board-level AI oversight committees play in enforcing a cohesive global AI ethics framework amid diverse local legal and cultural norms?
• How can AI-based methods be leveraged to examine how firms navigate cross-border governance and regulatory environments?

Associate editors