The key factors companies should consider when implementing large AI models, according to the discussion between Zhao Hejuan and Ishit Vachhrajani, are as follows:

1. Problem-solving focus: Companies should concentrate on addressing specific business challenges rather than being preoccupied with the technology itself. The selection of influential and relatable content is crucial.

2. Data strategy refinement: Companies need to pay attention to their data strategies, making sure they have the right data culture to unlock more value(3). Investing in infrastructure and data environments to gain an advantage when using data is also important.

3. Deployment intent of GenAI: The goal should be to truly unleash the productive value of GenAI. Once the proof of concept (POC) is successful, companies can continue to expand.

4. Leadership attention to GenAI: Corporate leaders should pay close attention to GenAI and take the time to accumulate their knowledge. It's important to train employees and get them on board with the AI journey(4).

5. Model selection: Companies need to select AI model products that suit their specific scenarios, choosing different tools for different tasks. It's important to balance accuracy, performance, and cost to achieve the best results.

6. Security and compliance: As enterprises adopt a "cloud-first" approach, data security and privacy protection become crucial challenges in the AI era. It's important to ensure that AI and machine learning are integral to the company's DNA, improving customer experience and driving innovation across all business areas(6).