The article also emphasizes the need for high-quality data, the decision between building or buying AI models, and the importance of security and privacy. It concludes by urging businesses to avoid the pitfalls of endless, costly pilot projects and instead pivot from potential to strategic action to fully harness the power of generative AI.
Key takeaways:
- Generative AI has the potential to drive business growth and innovation, but it's crucial to identify areas where it can deliver the highest ROI, such as enhancing customer and employee experiences, advanced data analysis, and business differentiation.
- High-quality data is essential for generative AI models to flourish, offering a domain view with sufficient examples for learning and allowing a robust understanding of relationships and nuances for precise knowledge extraction.
- When deciding whether to build or buy generative AI models, considerations should include technical needs, resource availability, and desired level of control. Building offers customization and control, while buying ensures faster deployment time and lower upfront costs.
- Security and privacy are critical considerations when using generative AI. Large language models may retain confidential data, so running the model privately on your infrastructure with your knowledge base stored as a vector embedding can help mitigate potential risks.