Ready for AI? Three questions to ask first 

Large language models (LLMs) like GPT-4 and other forms of AI have the potential to unlock new business opportunities – but they come with formidable challenges. In short, AI-based tools must be tailored to the context of the organization in which they are used for them to deliver real value.

As customization helps handle the specific requirements unique to each corporate environment, an off-the-shelf tool is insufficient to meet most organizations’ needs. AI models should be fine-tuned with data referring to the problem that the company wants to solve with them, but to do this, high-quality, extensive, and relevant data is required. If that data lies outside the boundaries of the organization, data collaboration platforms can be used to fine-tune these AI models.

Data collaboration platforms act as intermediaries between the organization owning the AI in need of fine-tuning and the organization owning the data that can enable it. Examples include Snowflake, Sherpa.ai,…