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.