‘AI’ Business Model – With many components flowing into the AI domain (cost, data, E&C, people, value, strategy, duplication of everything, etc.), I’ve started to think about splitting out ‘AI’ from the operating model and putting it into a separate legal entity. This way, I could manage a) risk and compliance, b) cost, c) resource allocation, d) governance, e) IP, f) revenue generation, etc. Of course, this isn’t new in general, but I’m especially interested in how this approach could help with the ongoing challenge of ensuring compliance with data privacy and regulations related to LLMs and data access/usage over time. My question: Is anyone else thinking about this, or has anyone already done it? I know there are examples in the literature, but I wanted to float this here for general comments and discussion.

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Director, Enterprise Architecture in Services (non-Government)6 days ago

I suppose the obvious answer as to whether or not this is a good idea is the good old "it depends". My company has not allowed any AI tools for general purpose use and requires a documented use case for even using something as benign as O365 Copilot. But they also invested some $ in standing up an AI CoE - which is still in its infancy, with the goal of trying to deduplicate effort in leveraging AI in various domains. I have noticed that the use cases I have seen so far focus in the non revenue-generating areas of the business. They are all looking for ways to get more done with less. The revenue-generating functions thrive on relationships in maritime, so the play for AI in the BD and sales functions are minimal at this time.

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‘AI’ Business Model – With many components flowing into the AI domain (cost, data, E&C, people, value, strategy, duplication of everything, etc.), I’ve started to think about splitting out ‘AI’ from the operating model and putting it into a separate legal entity. This way, I could manage a) risk and compliance, b) cost, c) resource allocation, d) governance, e) IP, f) revenue generation, etc. Of course, this isn’t new in general, but I’m especially interested in how this approach could help with the ongoing challenge of ensuring compliance with data privacy and regulations related to LLMs and data access/usage over time. My question: Is anyone else thinking about this, or has anyone already done it? I know there are examples in the literature, but I wanted to float this here for general comments and discussion. | Gartner Peer Community