Artificial Intelligence (AI) is one of the most transformative technologies in human history. It already influences how we work, communicate, learn, and make decisions, often in ways that are invisible to the people using it. Before we can deploy AI responsibly in organisations and public life, especially in sensitive domains such as business, education, healthcare, finance, and government, we need a clear understanding of what it actually is, how it emerged, and why it has advanced so quickly in recent years.
Public imagination often associates AI with science fiction images of robots replacing humans or sentient machines making their own choices. In reality, the story of AI is more grounded and more human. It is the story of mathematicians, engineers, psychologists, and policymakers trying to formalise different aspects of intelligence: perception, language, pattern recognition, reasoning, and decision making. It is also the story of how societies choose to apply these capabilities, and what that means for workers, institutions, and citizens.
This module introduces AI in a structured way, starting from the turning point in the 1970s when early promises met real-world limits and the field entered its first “AI winter.” From there, you will follow the story of how AI recovered and matured: from rule-based expert systems, through the rise of Machine Learning and Deep Learning, to the Transformer architectures and Large Language Models that power today’s tools. Along the way, we will connect the history to the core ideas underneath modern systems so you can see how data, computing power, and new algorithms brought us from fragile prototypes to practical, reliable capabilities.
The aim is not to train you as an engineer, but to give you a clear working understanding of where current AI comes from and how it operates at a high level. By the end of this module, you should be able to explain what AI is in practical terms, describe the key milestones that led to today’s models, and recognise how those models now support platforms such as Cyrenza and other enterprise tools. This technical and historical foundation prepares you for the rest of the curriculum, where we focus on applied use in the workplace, responsible deployment, and the leadership skills needed to guide AI in real organisations.