Summary of Podcast - How to articulate the value of Data & AI?

00:00:00 - 00:30:00

The video discusses how to present an accurate AI solution to customers, how to keep in mind important considerations when introducing AI into a business, and the different types of value that can be generated by data and AI solutions.

• 00:00:00 In order to articulate the value of an AI solution to customers, Deepak recommends that they think of it in terms of three dimensions- as a turbocharged automation solution, as a solution that will impact their jobs, and as a solution that needs to be tested on the customer's data set. He also recommends that the customer be assured that they are not the guinea pig, and that all concerns around data privacy and privacy of the data set have been addressed at the prototype stage.
• 00:05:00 Articulating the value of data and AI can be difficult, as customers often have unrealistic expectations about the accuracy and efficiency of the solution. Three assumptions customers should keep in mind when discussing AI solutions with clients are that the problem statement is well defined, the business challenge is defined, and the criticality of the solution is understood.
• 00:10:00 The author discusses how to present an accurate AI solution to customers, and how to keep in mind important considerations when introducing AI into a business. He also points out that many people have unrealistic expectations about perfect AI solutions, and that it is important to make AI more realistic for customers.
• 00:15:00 The video discusses the importance of data and AI, and how a proper understanding of the value of data and AI can help overcome some of the challenges of making an AI solution work. It notes that it can take up to three months for a proof of concept to be completed, and that pricing should be based on the value of the savings the AI solution provides. If the AI solution is viewed only as an automation solution, then the price should be based on the cost savings it offers. However, if the AI solution is viewed as a solution that saves people time and effort, then the price should be based on that value.
• 00:20:00 The video discusses the different types of value that can be generated by data and AI solutions, and the differences in pricing between them. The video also discusses the head of the analytics lab's approach to writing AI products.
• 00:25:00 The speaker discusses how clients are betting on AI in terms of business value, and how the technology has to be in support of the business. They emphasize that the technology has to be controlled by the human being and that this is an important factor in sales.
• 00:30:00 The speaker discusses the importance of embedding deep domain expertise into algorithms in order to ensure accuracy and performance. They also discuss how to articulate the value of data and AI to customers, emphasizing the need for a domain expert to be in charge. Finally, they mention that investments in AI monitoring technologies help to reassure domain experts about the future of AI.