Introduction

This Artificial Intelligence module comes from the need to talk more about a tool that’s become part of everyday conversations, not just in professional settings, but in many other areas too. There's a lot of mythology surrounding AI, and it's important to separate the myths from the reality of what it does, what it requires, and where it’s being used.

AI applications are wide-ranging, as we've seen throughout Level II of the RBI modules. We mention and discuss AI in the Customer Management module, especially its role in distribution channels, customer segmentation, and management. We also cover it in Operations and IT, highlighting how both areas are key to understanding and implementing AI, not just within their own functions but across the bank.

AI also comes up in the Collections and Recoveries module, as well as in Retail Credit Risk, where it’s used to support decision-making and credit analysis. We’ve emphasized how data plays a vital role in credit, customer management, and in making AI truly effective, especially when it comes to detecting patterns in fraud, customer behaviour, and overall relationship management.

In short, Artificial Intelligence has become a powerful tool in the day-to-day operations of banks. It’s important to truly understand what AI is today, what it needs to work well, and what the future might look like. That’s exactly what we’ll explore in this module.

In this module, you'll explore what Artificial Intelligence (AI) really is, and just importantly, what it's not.

With all the noise, buzz, hype, and pressure to "do something with AI," organizations are launching projects often without fully comprehending the technology and how it fits within their business strategy. They act out of FOMO (Fear of Missing Out), and then make poor decisions, wasting significant time and resources.

When used properly, AI can be a powerful tool. It can assist organisations in being more efficient, lowering costs, supporting better decisions, and create competitive advantages. But these benefits do not just happen; they follow when the organization understands how to use AI both technically and strategically.

Currently, most AI initiatives undertaken by banks or other companies are confined to certain areas which include fraud detection, customer service, or marketing. Many of these AI initiatives are led by technology (IT) or innovation teams, with minimal involvement from senior leadership. This is a problem because AI works in part when it sits within the bigger picture, aligned to overall long-term company goals and strategies, as well as being integrated across departments.

In this first section, we'll first look at the history and evolution of AI. We will explain what it can and cannot do, and give you the background to understand its potential and limitations. By the end of this module, you will be ready to approach AI not as a fad to chase, but as a tool that can be strategically and intelligently employed, particularly within the universe of banking and financial services.