Solving Business Problems with AI

The video discusses AI applications in DHL and Unilever, focusing on forecasting and recruitment. It highlights the challenges of AI deployment, such as data quality and bias, and the importance of measuring success through KPIs. The speakers emphasize the need for organizational acceptance and the role of AI in transforming business processes. They also address ethical concerns and the necessity of upskilling the workforce to adapt to AI-driven changes.

How did the use of AI in forecasting lead to cost savings for DHL?

What measures were taken to ensure that AI algorithms used in recruitment were not biased?

What was the significance of data lakes in improving access to quality data for AI projects?

What strategies did both companies employ to manage expectations around AI capabilities?