Advanced Diploma in Business Management

Change Management focuses on managing and leading organizational change, blending classical change management theories with AI-driven strategies. Students explore frameworks for effective change (e.g. Kotter’s 8 Steps, Lewin’s Change Model, ADKAR) alongside modern digital transformation practices. Equal emphasis is placed on people-centric skills (stakeholder engagement, communication, overcoming resistance) and AI tools that facilitate change. By integrating AI analytics and automation, students learn to plan and implement changes more efficiently, using data to anticipate challenges and tailor change initiatives. This module prepares learners to champion change in a business world where technology and AI are continuously driving organizational evolution.

• Explain key change management theories and models, and apply them to business scenarios.
• Develop comprehensive change management plans (including communication and training) for business initiatives.
• Leverage AI tools (e.g. analytics, chatbots) to assess organizational readiness, monitor change progress, and address resistance.
• Analyze employee feedback and performance data to refine change strategies and improve adoption rates.
• Demonstrate skills to lead digital transformation projects, balancing human factors with AI-driven insights.

Business Law provides a comprehensive overview of the legal environment in which businesses operate, with a dual focus on fundamental business law concepts and the application of AI in legal contexts. Students will revisit core areas of business law – including contract law, corporate law and governance, employment law, intellectual property, and compliance/regulations – to understand the legal obligations and risks managers must navigate. Alongside theory, the module introduces AI-driven legal tools and discusses how AI is transforming legal practices. Students learn how routine legal tasks like contract review, compliance monitoring, and legal research can be streamlined by AI, and they examine the legal and ethical challenges posed by emerging technologies (such as data privacy laws, AI ethics, and regulatory compliance for AI deployments).

• Describe key principles of business law (contracts, company law, employment, IP, and regulatory compliance) relevant to managing a business.
• Analyze and interpret basic legal documents (contracts, policies) to identify risks and ensure compliance with laws.
• Utilize AI tools to assist in legal research, contract analysis, or compliance checks, improving efficiency and accuracy in legal tasks jeremyeveland.com.
• Evaluate the legal and ethical implications of implementing AI solutions in business (including issues of data protection, algorithmic bias, and liability).
• Ensure business decisions and strategies are informed by legal considerations and facilitated by technology (e.g. using compliance software to adhere to laws across jurisdictions).

Strategic Leadership delves into high-level leadership and strategy formulation, marrying classic leadership theory with AI-enhanced decision-making tools. Students examine what it means to be a strategic leader in modern organizations – covering leadership styles (transformational, transactional, servant leadership, etc.), vision and mission development, strategic planning models, and organizational strategy execution. Traditional strategy frameworks (such as SWOT analysis, PESTEL analysis, Porter’s Five Forces, and Balanced Scorecard) are revisited, but with equal emphasis on data-driven and AI-supported approaches to strategic decision-making. Learners will discover how leaders can leverage AI for insights – for example, using big data analytics to inform strategy, or AI simulations to test decisions – while also honing the human skills (critical thinking, ethical judgment, motivational communication) needed to guide organizations. This module prepares students to lead teams and make informed strategic decisions by combining human vision with AI’s analytical power.

• Demonstrate understanding of strategic leadership concepts and distinguish between different leadership styles and their impact on organizational strategy.
• Conduct strategic analysis for a business scenario (market analysis, competitive analysis, risk analysis) using both traditional frameworks and AI-powered data insights.
• Utilize AI-based tools (e.g. predictive analytics, dashboards) to support strategic decision-making and planning and interpret AI-generated insights to formulate effective strategies.
• Apply decision-making techniques that integrate data (analytics, AI predictions) with human judgment and ethical considerations, especially under uncertain or complex conditions.
• Develop and communicate a strategic plan for a business initiative, including setting a vision, defining objectives (KPIs), and outlining execution steps, while illustrating how technology and AI will be leveraged in the process.
• Reflect on one’s own leadership skills and adopt strategies (including using AI feedback or coaching tools) for continuous improvement in leading people and innovation.

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.

• 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)

Life Influences in Business examines the interplay between societal, personal, and ethical factors (“life influences”) and business success, highlighting how businesses can thrive by aligning with human values, well-being, and broader social responsibilities. This module uniquely integrates topics like ethics, corporate social responsibility (CSR), personal development, and the impact of external social trends on businesses – all augmented by AI applications. Students will discuss how personal values and ethics shape leadership decisions, how businesses influence and are influenced by society and the environment, and why issues like diversity, inclusion, and employee well-being are strategic business concerns. Alongside these themes, the module demonstrates how AI can be a force for good in business: supporting ethical decision-making, monitoring and improving workplace culture and wellness, and driving sustainable business practices. The goal is to produce leaders who not only drive profits but also enhance the quality of work life and uphold responsibility to the community – using advanced tools to achieve these ends.

• Articulate the importance of business ethics and social responsibility, and apply ethical frameworks to resolve dilemmas in business scenarios.
• Evaluate how personal life factors (e.g. values, health, work-life balance) and broader societal influences (demographic changes, cultural norms) affect employee performance, consumer behavior, and business strategies.
• Implement strategies for corporate social responsibility (CSR) and sustainability in a business context, setting initiatives that align business goals with societal and environmental well-being.
• Utilize AI tools to promote ethical practices and well-being in the workplace – for example, using AI to detect bias in recruitment, to monitor employee engagement and wellness, or to reduce a company’s environmental footprint knowmadmood.com.
• Understand the ethical implications of AI in business (such as privacy, algorithmic bias, and job displacement) and manage AI deployments in a way that is transparent, fair, and inclusive.
• Develop a plan for a business initiative that demonstrates balance between profitability and “people/planet” considerations (e.g. a sustainability project, a diversity and inclusion program, or an ethics policy rollout), incorporating AI solutions to enhance its effectiveness.

AI-Driven Business Innovations is a capstone academic module that brings together innovation management theory with cutting-edge AI applications, showing students how AI can be a catalyst for new business models, products, and operational efficiencies. On the theory side, students will learn how businesses innovate and adapt – covering topics like the innovation lifecycle, disruptive innovation (e.g. how new technologies can upend industries), design thinking for product development, and the challenges of managing innovation within organizations. On the practical side, the module surveys state-of-the-art AI technologies and their business applications: from machine learning and data analytics to robotics, generative AI, and beyond. Students examine case studies of companies transforming their operations with AI (in marketing, finance, supply chain, etc.) and get hands-on exposure to AI tools. By blending innovation theory with real AI use cases, this module equips learners to lead digital transformation and innovation initiatives. They will understand not just how to implement AI solutions, but how to align them with business strategy and manage change (drawing on Module 1) to ensure these innovations deliver value. This forward-looking module reinforces the reality that AI is now central to business innovation – with over 80% of businesses embracing AI as a core technology ventionteams.com – and prepares students for the continuously evolving future of work.

• Understand and explain key innovation theories and models (e.g. disruptive innovation, diffusion of innovation, open innovation) and how they relate to technological change in business.
• Analyze emerging AI trends and technologies, evaluating their potential impact on various industries and functional areas of business (marketing, finance, operations, etc.).
• Develop a strategic plan for adopting or implementing an AI-driven innovation in a business scenario – including identifying a suitable AI solution, building a business case (ROI, competitive advantage), and outlining steps for implementation.
• Demonstrate proficiency with several AI tools/platforms through practical exercises or projects, and illustrate how these tools can be integrated into business processes to drive improvements or create new opportunities.
• Address management considerations for AI innovation: including cross-functional collaboration (business teams with data scientists/IT), change management for AI adoption, scalability and integration with existing systems, and ethical and compliance considerations for new technology.
• Cultivate a mindset of continuous learning and adaptability, recognizing that future career success will require staying current with technological innovations and guiding organizations through ongoing digital transformation.

The practicum is a culminating component of the program where students apply what they’ve learned in a comprehensive project, emphasizing AI integration in a real or simulated business context. This capstone project is largely self-driven (with faculty mentorship) and spans 120 hours of the total program hours. It allows students to synthesize knowledge from all six modules, demonstrating both their business acumen and ability to leverage AI tools. Students may work individually or in small teams to tackle a practical business challenge – often in collaboration with an industry partner or using case studies that mirror real-world conditions. They will be expected to identify a problem or opportunity within a business domain and develop an innovative solution that incorporates AI as a key element. The practicum emphasizes experiential learning: instead of a purely theoretical report, students produce tangible deliverables (analysis, prototypes, dashboards, or strategic plans) and often present them to a panel or the partner organization, simulating a professional consulting or management environment.

• Consulting Project: Analyze a company’s business problem and recommend an AI-driven solution. For example, a student team might work with a local business to improve customer retention – they could analyze customer data using an AI tool to identify churn predictors, then propose a strategy (Module 3) and change plan (Module 1) to implement a personalized marketing AI solution.
• AI Implementation Plan: Select a specific AI technology (chatbot, predictive analytics, RPA, etc.) and develop an end-to-end implementation proposal for a firm. This would include a change management plan (Module 1), consideration of legal/regulatory compliance (Module 2) like data privacy, alignment with the company’s strategic goals (Module 3), adaptation for global or cultural factors if deploying internationally (Module 4), and addressing ethical implications (Module 5). The final deliverable might be a detailed report and presentation outlining how the AI solution would be rolled out, with a small demonstration or prototype.
• New Venture or Product Development: Create a business plan for a new product or service that is built around AI innovation. For instance, propose a startup idea that uses AI to solve a business/societal problem (e.g. an AI-driven personal finance advisor app). Students would cover market analysis, business model, go-to-market strategy, and even develop a prototype or simulation of the AI functionality. This taps into creativity and showcases understanding of innovation management (Module 6) and all-around business planning.
• Case Study Research: Investigate a prominent case of AI integration in business (such as how a multinational implemented AI in its supply chain or how a bank uses AI for customer service). Students would research and possibly interview stakeholders, then produce a case study report analyzing what made the project successful or what pitfalls occurred. They must connect this to course learnings – e.g. discussing the change management, leadership decisions, legal compliance, cultural issues, and life influence (ethics/CSR) aspects observed in the case.
• Integrated Simulation or Hackathon: Some projects may be done in a simulation environment or hackathon style. For example, students might participate in a simulated global business expansion scenario where each week they respond to new challenges: they might use an AI market analysis tool to choose a country to enter, then plan a culturally appropriate marketing strategy, then set up an AI chatbot for customer service in that region, etc. This would be structured by faculty but allow students to make decisions and see outcomes, reinforcing learning in a hands-on way.