So far, we have talked about generative AI’s use cases in the marketing, retail and e-commerce sectors. In this segment, we will continue this discussion and talk about the use cases of generative AI in technology, finance and customer operations.
In the next video, Kshitij will talk about the use cases of generative AI in technology.
Some of the ways in which generative AI can be used to help professionals working in technology, as outlined by Kshitij, are as follows:
- Automated code generation.
- Code completion and intelligent suggestions.
- Bug detection and correction.
- Code summarisation.
You can see that generative AI tools can be very useful in helping programmers write readable and bug-free code. Two examples of platforms that use generative AI that you may have seen before are GitHub Codespaces and Replit Ghostwriter.
In the next video, Kshitij will talk about generative AI’use cases in the banking and financial services industries.
In the finance industry, a strong knowledge of financial data and trends is critical. BloombergGPT is a domain-specific large language model that is trained on financial data and reports and allows the user to perform various natural language tasks to access the underlying data. You can read more about BloombergGPT here.
In the next video, Kshitij will talk about the last category in which we will explore generative AI’s application: customer operation
As discussed in the video, MakeMyTrip has partnered with Microsoft to create a chatbot interface on its website that assists users in planning and booking their travel.
You have now surveyed use cases of generative AI in different industries. In the next segment, we will synthesise your learning by categorising the use cases of generative AI. Before moving forward, answer the following question.