Develop international business strategy skills and cultural intelligence in this AI-integrated module. Learn market entry, cross-cultural communication, and use of AI tools for global operations, customer insights, and multilingual business.
Overview
Global Business and Cultural Awareness prepares students to operate in the international business arena, emphasizing how cultural differences and global trends impact business, and how AI tools enable more effective global operations. Learners will study theories of international business strategy (such as globalization vs. localization, entry modes into foreign markets, global supply chain management) and frameworks for understanding culture (e.g. Hofstede’s cultural dimensions, high-context vs low-context cultures). The module highlights the challenges of managing across different countries – communication barriers, cultural etiquette, legal and economic differences – and how modern managers can overcome these. Crucially, it integrates AI applications that facilitate global business, from real-time translation services to global data analytics and culturally adaptive AI systems. By combining cultural intelligence with technology, students gain the skills to lead and collaborate in a multicultural environment and to strategize for global market success.
The Details
FOR SKILLSFUTURE CLAIMS
Registered Title: (Global Business and Cultural Awareness
(Classroom & Asynchronous))
TPGateway Code:
total hours
47:00
Mode of Learning
On Campus
Curriculum
Course Duration
SSG Approved Training & Assessments Hours:47:00Trainer Facilitated Hours (On Campus/Virtual):32:00Self-Directed E-learning Hours:04:00Assessment Hours:11:00
Programme Objectives
Explain key concepts in global business strategy (market entry strategies, globalization vs localization, international trade influences) and demonstrate awareness of how different cultures impact business practices and management styles.
Develop cross-cultural communication and management skills, including the ability to adapt leadership and negotiation approaches to diverse cultural contexts.
Utilize AI-driven tools to bridge language and cultural gaps – for example, employing translation AI for multilingual communication and using analytics to understand cultural market preferences
Analyze global market data using AI and business analytics to inform international strategy (such as identifying international customer trends or optimizing a global supply chain).
Address the ethical and operational challenges of global business in the digital age, including data privacy across borders and ensuring AI systems respect local cultural norms and regulations.
Demonstrate cultural awareness by designing a business solution or strategy that accounts for regional differences (e.g. a marketing plan tailored to multiple countries, using AI insights to customize content)
Course Topics
International Business Strategy
Learning Outcome: Globalization drivers, theories of comparative advantage; modes of market entry (exporting, joint ventures, FDI); adaptation vs standardization of products; managing global supply chains and operations.
Cross-Cultural Management
Learning Outcome: Understanding cultural values and business etiquette (using models like Hofstede’s dimensions or Hall’s high/low context); managing multicultural teams; communication styles and negotiation tactics across cultures.
Global Marketing and Consumer Behavior
Learning Outcome: How culture affects consumer preferences; strategies for branding and marketing in different regions; using AI to localize content (e.g. translating and culturally adapting advertisements).
AI for Language Translation and Communication
Learning Outcome:Real-time translation technologies (e.g. Google Translate, Microsoft Translator) that have revolutionized multilingual business communicationklizosolutions.medium.com; AI-driven transcription and language processing in virtual meetings; chatbots that handle multiple languages to provide customer service globally.
AI for Cultural Analytics
Learning Outcome: How AI can recognize and adapt to cultural contexts – e.g. analyzing local social media trends, sentiment analysis in different languages, or algorithms that adjust to local norms (content recommendation systems tuned to regional preferences). AI-driven platforms can even adapt messaging to align with specific cultural sensitivities, reducing misinterpretations.
Global Data Analysis and Decision Support
Learning Outcome: Using global datasets (financial, economic, demographic) and BI tools to make informed decisions in international operations; scenario planning for geopolitical or currency fluctuation risks with AI models.
International Regulations and Ethics
Learning Outcome: Overview of how laws and ethical norms differ globally (data protection laws like GDPR, AI ethics guidelines in EU vs U.S., etc.); ensuring compliance of AI applications in different jurisdictions; addressing issues like algorithmic bias across populations and avoiding ethnocentrism in AI design.
Developing Cultural Intelligence
Learning Outcome: Techniques for continuous learning about cultures, using AI-based cultural training simulations (e.g. virtual reality or adaptive learning platforms) to practice cross-cultural interactions.
