Additionally, the article stresses the need for cost management strategies to prevent AI expenses from spiraling out of control and underscores the importance of training and change management to ensure user adoption. The author advises starting small, building strong foundations, and scaling thoughtfully, emphasizing that successful AI deployment is a long-term commitment requiring continuous optimization based on real-world performance.
Key takeaways:
- Start with clear business objectives by defining concrete business outcomes and specific metrics to guide AI development and justify investments.
- Choose the right foundation model by prioritizing models that deliver consistent, rapid responses for customer-facing applications and considering compliance requirements.
- Implement essential safety controls, including content filtering, output validation, and circuit breakers, to protect your business and customers.
- Focus on security from day one by incorporating end-to-end encryption, role-based access control, and privacy-enhancing computation techniques.