The piece then outlines the challenges in operationalizing generative AI, including data quality, security, user experience, and scalability. It suggests using pre-trained foundation models and supplementing them with unique business data for optimal results. The article concludes by highlighting the use of generative AI by companies like JLL and AAA, and emphasizes the importance of getting the data right for successful implementation of generative AI. It also mentions the role of generative AI in creating a unique competitive advantage for businesses.
Key takeaways:
- Generative AI is transforming various industries and is considered a hot topic in boardroom discussions. It can be used to create a sustainable competitive advantage by combining proprietary data with foundation models.
- Data readiness for generative AI depends on the ability to move and integrate data from various sources in a secure, cost-effective manner, and the implementation of data governance.
- Challenges in operationalizing generative AI include data quality and preparation, security and governance, user experience, and scalability. Choosing the right foundation model can significantly impact performance and capabilities.
- High-quality, usable, trusted data built on automated, self-healing pipelines is crucial for making full use of powerful foundation models and driving innovation through generative AI.