Data gravity refers to the tendency of enterprises to aggregate their apps and workloads around their data ecosystem, and hence affords data vendors a lever to cross-sell and up-selling related workloads such as data catalog, analytics, AI, etc.
Similarly, LLM gravity, and its big brother AI gravity, are the recent AI adoption “vectors” that is shaping how vendors compete in the generative AI market, and how enterprise customers are adopting AI.
AI gravity is related but different from data gravity, in that many AI use cases are “net-new” and can grow independently of existing data ecosystem lock-ins. For example, OpenAI has >15K+ enterprise accounts which didn’t exist last year. This affords AI and data companies both competitive opportunities and threats.
This post will try to answer the following questions:
How AI gravity and LLM gravity are playing out in enterprise AI adoption
How enterprise customers feel about AI gravity, and what they are doing about it.
How AI (LLM) gravity compares to data gravity, and how they might interact