Leveraging AI and Consumer Data for Real-Time Festival Management and Privacy (Full Transcript)

Speaker 1: To deliver the best personalized customer experiences, businesses must understand how their consumers think and behave. So how can companies use consumer data and AI to predict demand and scale services in real time while still preserving privacy? Let's find out in this edition of the AI Training Ground. During the summer in Denmark, nearly 75,000 concertgoers double the size of a nearby town during a week-long festival. Every logistical challenge from transportation, traffic management, food and beverage provisions, sanitation, sales, and supply chain needs to be addressed on-site in real time. So how can AI be used to shape a better experience? To start, festival attendees all wear smart wristbands during the event. These are used for cashless payments for almost a million transactions. The data collected provides insights from ticketing information, purchasing patterns, and location data. It's the fuel that keeps the festival at peak performance and gives a real-time view of consumer behavior. But with so much data being collected, there are challenges. The data needs to be accessible to even be harnessed. And if it's all living in silos and can't be combined with other data sets, it can't be used to make accurate predictions on the day of the festival. By combining multiple years with external data sources such as weather, you can predict attendance and supply chain demands for future events. In 2018, nearly 40% of the food items were returned, costing festival planners both time and money. But with predictive AI, this could have been avoided. There's also the issue of preserving privacy. With all the customer data being collected, festivalgoers want to be sure their private data remains just that, private. And that it's not being misused or leaked. By anonymizing this customer data and scrubbing all digital traces of personal information, businesses can use sensitive data to innovate securely and responsibly. Designing and implementing trustworthy AI requires a deep understanding of the human problem you're trying to solve for. With a human-centric approach, you can create better outcomes for your customers and for your business. Learn more about building predictive AI that's secure with IBM's AI Training Ground.