Seven Lessons for Enterprise AI
1. Start with Evals
- Use systematic evaluation to measure model performance against your specific use cases.
- Evaluate accuracy, safety, and compliance to ensure reliable applications .
2. Embed AI into Your Products
- Integrate AI directly into your product experience to improve outcomes and customer engagement.
- Example: Indeed increased applications and success rates by embedding AI in job recommendations .
3. Start Now and Invest Early
- Begin small, but invest continuously to capitalize on compounding benefits.
- Companies like Klarna show how early investment leads to major progress over time .
4. Customize and Fine-tune Your Models
- Improve accuracy and relevance by tailoring models with your data and industry-specific context.
- Example: BBVA built custom GPTs for different teams to embed expertise .
5. Unblock Your Developers
- Use AI platforms to streamline development and empower engineers with scalable, consistent tools.
- MercadoLibre’s platform Verdi helped thousands of developers build faster and more securely .
6. Get Your AI in the Hands of Experts
- Enable specialists to customize AI solutions for their domains, enhancing quality and relevance.
- Example: BBVA allowed employees to create custom GPTs with industry expertise .
7. Set Bold Automation Goals
- Aim to automate challenging or slow processes to dramatically increase efficiency.
- OpenAI exemplifies this by continuously automating their workflows and encouraging bold targets .