Startup eBooks

Top 6 generative AI use cases for startups Ebook_EN

Issue link: https://read.uberflip.com/i/1517599

Contents of this Issue

Navigation

Page 2 of 10

Before you can successfully adopt generative AI, it's important to determine where and how you can apply the technology for the greatest impact. In other words, you need to select the right generative AI use case for your startup. This requires the consideration of several factors. First, you need to find a balance between optimal business value and speed. A proof of concept built by a siloed data scientist is not likely to generate much enthusiasm from your team. What is more likely to attract the needed commitment, and potentially, investor funding is showing how generative AI can address the practical issues your startup currently faces. Furthermore, to not lose momentum, you will want to find something that can be accomplished in the short term, whether that means a few weeks or a few months. This is especially true if this is your first foray into AI. Second, you will want to find a use case that will leverage your existing data to create a unique value for your startup. Generative AI business value grows exponentially when the foundation models (FMs) are customized with your own data through prompt engineering or by fine-tuning them. You will be able to customize your own FM with your data and intellectual property (IP), which will stay completely protected, secure, and private. Lastly, here are two critical factors to consider when selecting the right generative AI use case: • Impactful: Early use cases should solve real business problems (or create new opportunities that matter to your business and your investors) and demonstrate the differentiated benefit of using generative AI to solve them. • Relatable: Initial use cases shouldn't be limited to solving one problem. Spark team members' imagination and inspire them to think about what they can solve within their domains using generative AI. The best way to satisfy these two criteria is to ensure that technical experts and domain experts are working hand in hand on your generative AI project. Technical experts can conduct feasibility assessments, and domain experts will ensure the solution is solving a real business problem and that it will have a real impact. What is generative AI? Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. It is powered by large models that are pretrained on vast amounts of data, commonly referred to as foundation models (FMs). Choosing the right generative AI use case 3

Articles in this issue

view archives of Startup eBooks - Top 6 generative AI use cases for startups Ebook_EN