Artificial Intelligence Business Strategy and Transformation
Overview
This unit introduces students to the strategic application of Artificial Intelligence (AI) in contemporary business environments. Students will examine how AI intersects with innovation, business models, organisational structures and value creation. The unit explores what is required for successful AI adoption and transformation, including critical enablers, implementation challenges and ethical and governance considerations. Through conceptual frameworks, real-world case studies and scenario-based assessments, students will develop the capability to identify and evaluate AI opportunities, analyse organisational readiness and communicate strategic insights to diverse stakeholders. Designed as a conceptual and analytical unit, this subject provides a strong foundation for future technical and applied studies in AI, data, and digital business.
Requisites
01-November-2026
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Evaluate how AI technologies contribute to strategic innovation and business model transformation
- Analyse ethical, governance and organisational readiness factors influencing successful AI-driven transformation
- Assess and frame AI opportunities within different business contexts, considering feasibility and strategic alignment
- Design a conceptual AI implementation roadmap that aligns with organisational strategy and transformation goals
- Communicate insights and recommendations on AI strategy and transformation to diverse stakeholders using appropriate business and technical language
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
On-campus Class (Computer Lab) |
2.00 | 12 weeks | 24 |
Online Lecture (asynchronous) |
1.00 | 12 weeks | 12 |
Unspecified Activities Independent Learning |
9.5 | 12 weeks | 114 |
| Total | 150 |
Assessment
| Type | Task | Weighting | ULOs |
|---|---|---|---|
| Assignment 1 | Individual | 30-40% | 1,2 |
| Assignment 2 | Group | 30-50% | 1,2,4,5 |
| Assignment 3 | Individual | 20-30% | 1,2,3,4 |
Content
- Introduction to AI in Business
- Key AI technologies (machine learning, NLP, computer vision, etc.) and their strategic relevance
- Strategic Implications of AI
- AI as a driver of competitive advantage and business model innovation
- AI Adoption Frameworks and Maturity Models
- Readiness, stages, and organisational capability assessment
- Case Studies in AI Business Transformation
- Real-world examples from industries such as finance, retail, healthcare, logistics
- Data as a Strategic Asset
- The role of data governance, data strategy, and data-driven culture in AI success
- AI and Business Model Innovation
- Platform business models, servitisation, and ecosystem thinking
- Organisational Change and AI
- Cultural resistance, workforce reskilling, and digital leadership
- AI Ethics and Responsible Innovation
- Bias, transparency, accountability, and regulatory frameworks (including Australia’s AI Ethics Principles)
- Human–AI Collaboration
- Augmented intelligence, decision augmentation, and the future of work
- AI Strategy Formulation
- Linking AI initiatives to business strategy, vision, and KPIs
- AI Governance and Risk Management
- Ethical, legal, reputational, and operational risk management
- AI Implementation Challenges
- Infrastructure, integration, talent gaps, project failure rates
- Change Management in AI Transformation
- Managing transitions, stakeholder engagement, agile methods
- Measuring AI Value and ROI
- Metrics, impact assessment, performance dashboards
- Communicating AI Strategy to Stakeholders
- Tailoring messages for executives, employees, customers, and partners
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.