In the first phase of generative AI adoption, most large companies rented intelligence through an API. They connected to models from OpenAI, Google LLC, or Anthropic, ran them on third-party infrastructure, and paid per token or prompt. The setup was quick to deploy but carried growing limitations.
Copyright lawsuits against OpenAI and Stability AI forced companies to question how model training data had been sourced. Compliance teams raised concerns about whether confidential information sent through APIs could be stored or reused. Marketing departments discovered that public models struggled to maintain brand tone or visual consistency across languages and channels. Costs also escalated as experimentation turned into large-scale production.
These pressures have pushed enterprises to take more control. Instead of renting generic models, many now aim to build or co-develop private ones trained on their own data. Adobe Inc. formalised that shift this month with the launch of Adobe AI Foundry, a service that lets companies build custom generative-AI models based on the Firefly family.
