Content Overview


AI for Business uses video case studies, cutting-edge technologies and vibrant debate to illustrate how established companies can use strategy, leadership and innovation to adapt to digital transformation.




What AI can do for your industry

Participants will be given a thorough, non-technical introduction to different kinds of AI. 

Topics covered include:

  • From perception (traditional statistics) to prediction (machine learning)
  • The key idea: How machines (algorithms) learn from experience (data)
  • Don’t let your data take you hostage: Avoiding over-fitting
  • Prediction errors: Which mistake is more painful?
  • Applications across functional areas (marketing, finance, operations and HR/organisational development)
  • The strategic disruption that AI is bringing to various industries


Getting the most out of your in-house AI experts 

This section of the programme gives participants the skills to engage in a rigorous conversation with the data scientists who typically report to them, or who are available as a centralised pool of talent. The goal is to improve your ability to communicate business needs and apply the insights you may receive from these colleagues.  

Each group of participants will be assigned a “Chief Data Scientist”. You’ll work together on a problem during the class, to get a feel for how machine learning insights are produced and deployed to support business decisions.


Next practice: Beyond data mining through AI

This section begins with a thorough discussion of some of the logistical, legal and ethical challenges associated with deploying AI in management. We will also focus on some core weaknesses of machine learning–based decision-making.

Topics covered include:

  • The Global Data Protection Regime
  • AI ethics: The trade-off between social and statistical biases
  • Correlation versus causation
  • Randomisation as the “gold standard”
  • Network analysis and agent-based models

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