Comprehensive course analysis
Who should attend
- Senior executives who want to understand how they can make their organisations AI-ready
- Leaders and senior executives seeking the comprehensive perspective they need to lead in a digital world, with a focus on strategic understanding, organisational wisdom and innovation-based capabilities
- Senior managers seeking to build their own capabilities in strategy, leadership and innovation, while developing personalised, actionable plans
About the course
Demystifying Artificial Intelligence in the digital age
Artificial intelligence (AI) is rapidly emerging as the most important and transformative technology of our time. Recent advances, particularly in machine learning - a computer’s ability to improve its performance without human instruction - have led to a rapid proliferation of new applications that are changing the game for companies in almost all industries.
AI can help accomplish many business activities with greater accuracy and at a fraction of the time it would take humans to do the same.
AI also offers a substitute for human judgement because it can forecast based on patterns in data that are undetectable by humans. These features can change what businesses and the managers in them do but also how they do it in profound ways.
The effects of AI will only be magnified in the coming decade, as industries transform their core processes and business models to take advantage of its capabilities. Rather than miss the momentum, business leaders need to understand and act on the tremendous opportunities AI offers their industry. They need to consider what is possible now, what will be possible, and what other industries are doing that could translate to their business to give them a competitive advantage.
AI for Business is designed to give managers an understanding of the growing deployment of AI in business, so they can appreciate what it can and cannot do for their organisation.
The programme also provides practical templates to guide how you work with data scientists and programmers in your organisation in making the most of these emerging technologies. Uniquely, it also features hands-on sessions where you will be shown how to commission analysis and analyse the results that data scientists produce.
AI for Business is delivered over three immersive days by faculty members at the forefront of applying AI-based techniques in areas such as marketing, finance and organisation design.
How you benefit
- Demystify AI. Develop a deep and jargon-free understanding of AI and machine learning concepts
- Understand how AI is put into practice. Gaining exposure to applications across functional areas
- Learn to collaborate with AI specialists. Learning how to work with data scientists
- Understand when, and when not, to rely on AI. Understanding the limits and dangers of blindly relying on algorithms
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
Theos Evgeniou is a Professor of Decision Sciences and Technology Management at INSEAD, and an Academic Director of INSEAD eLab, a research and analytics center at INSEAD that focuses on data analytics for business. Professor Evgeniou has received four degrees from MIT, two BSc degrees simultane...
Sameer Hasija is an Associate Professor of Technology and Operations Management at INSEAD. He earned his PhD in Operations Management and MS in Management Science Methods from the Simon School of Business at the University of Rochester and his BTech from the Indian Institute of Technology Madras....
Philip M. Parker is a Professor of Marketing at INSEAD and the INSEAD Chaired Professor of Management Science. Before joining INSEAD, he was a Professor of International Strategy and Economics at the University of California, San Diego. He has taught at Harvard University, MIT, Stanford Universit...
Phanish Puranam is a Professor of Strategy, the Roland Berger Chaired Professor of Strategy and Organisation Design at INSEAD. He is the Academic Director of the PhD Programme. Professor Puranam studies the design and management of collaboration structures within corporations (i.e. between divis...
Ville Satopaa is an Assistant Professor of Technology and Operations Management at INSEAD. His current research explores different areas of forecasting: judgmental and statistical forecasting, modeling crowdsourced predictions, combining and evaluating different predictions, and information elici...
Videos and materials
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.