The author suggests starting with small projects and having an appropriate data strategy before embarking on an AI project. The role of the insights and analytics lead is crucial in identifying specific use cases that allow short-term benefits while defining the long-term strategy and objectives of AI adoption. With the right strategic approach, GenAI can drive innovation and boost productivity, giving companies a competitive advantage in the AI economy. However, it requires thoughtful planning and execution.
Key takeaways:
- Generative AI has the potential to speed up work across all sectors, but it also presents challenges in creating personalized AI that meets the needs of companies, produces correct and scalable results, and guarantees data security and privacy.
- Companies need to control the processes of generative AI from start to finish, intertwining it with their business strategy to avoid critical mistakes.
- The success of any generative AI business development is dependent on a well-established data ecosystem, including governance, technology, culture, and processes.
- Companies should start with small projects when adopting generative AI, ensuring they have an appropriate data strategy and focusing on improving specific processes at a business level.