Augmenting Business Decisions with AI |
Summary
Artificial Intelligence is increasingly embedded across business functions, reshaping how organizations create economic value. This course examines the ways AI can support, augment, and automate decision-making in diverse business contexts, while also highlighting its limitations and ethical considerations.
Objectives
By the end of the course, students will be able to:
- Understand how different AI techniques can support, augment, and automate business decisions.
- Critically evaluate the capabilities and limitations of AI models across business applications.
- Apply knowledge of AI methods to assess business use cases and design effective AI-enabled strategies.
- Recognize risks, biases, and governance issues in AI-driven decision-making.
Contents
- AI in Business Decision-Making: The spectrum of AI maturity: from advisory systems to augmentation to full automation. Value creation through data-driven insights and predictive analytics.
- Core AI Problem Types in Business Contexts: Classification problems and applications across domains. Regression and estimation for forecasting and optimization.
- Generative AI and Cognitive Augmentation: Applications of generative AI in decision-making (e.g., ideation, content creation, personalization). Cognitive and causal limitations of generative models. Ethical and interpretability challenges.
- Reasoning and Advanced Decision Models. Causal inference and reasoning models in strategic and operational decision-making. AI for scenario planning, simulations, and the creation of synthetic personas.
- AI Integration into Organizations. Combining narrow AI, generative AI, and agent-based AI for holistic business solutions. Organisational readiness, governance, and adoption challenges. Future directions: towards hybrid human–AI decision ecosystems.
Requirements
A solid understanding of classic machine learning, deep learning, and generative AI models.
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