Together AI positions open-weight AI models as the enterprise moat for cost, control and IP
Nobody is talking about this: enterprises are ditching closed models. The reason? Control, not capability.
Why it matters
As agentic AI moves into production, enterprises are reassessing the trade-off between frontier model performance and data sovereignty. Open-weight models are emerging as the preferred architectural choice for companies processing sensitive workflows, signaling a structural shift in how organizations will deploy AI at scale.
The key facts
5 to knowEnterprises moving from AI experimentation to core business process deployment
Data control and IP protection emerging as primary decision drivers over model capability
Open-weight models positioned as enterprise preference for agentic AI workflows
Proprietary data exposure to closed frontier models viewed as material risk
Shift reflects broader enterprise risk management in AI deployment strategy
Go to the source
SiliconAnglesiliconangle.com
Publisher excerpt: Enterprises racing to deploy AI at scale are discovering that the biggest constraint isn’t model capability anymore — it’s control. As agentic AI moves from experimentation into core business processes, companies are rethinking whether handing proprietary data to closed frontier models is a risk…