AWS is still chasing a cohesive enterprise AI story after re:Invent
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AWS is still chasing a cohesive enterprise AI story after re:Invent
"AWS kicked off re:Invent 2025 with a defensive urgency that is unusual for the cloud leader, arriving in Las Vegas under pressure to prove it can still set the agenda for enterprise AI. With Microsoft and Google tightening their grip on CIOs' mindshare through integrated AI stacks and workflow-ready agent platforms, AWS CEO Matt Garman and his lieutenants rolled out new chips, models, and platform enhancements,"
"Garman's biggest swing, at least the one that got it "closer", came in the form of Nova Forge, a new service with which AWS is attempting to confront one of its strategic weaknesses: the absence of a unified narrative that ties data, analytics, AI, and agents into a single, coherent pathway for enterprises to adopt. It's this cohesion that Microsoft has been selling aggressively to CIOs with its recently launched IQ set of offerings."
"Unlike Microsoft's IQ stack, which ties agents to a unified semantic data layer, governance, and ready-made business-context tools, Nova Forge aims to provide enterprises raw frontier-model training power in the form of a toolkit to build custom models with proprietary data, rather than a pre-wired, workflow-ready AI platform. But it still requires too much engineering lift to adopt, analysts say. AWS is finally positioning agentic AI, Bedrock, and the data layer as a unified stack instead of disconnected services,"
AWS presented chips, models, and platform enhancements at re:Invent 2025 to strengthen its enterprise AI foundation. Nova Forge was introduced to give enterprises frontier-model training capabilities and toolkits to build custom models using proprietary data. The Nova Forge approach prioritizes raw model-building power over a pre-wired, workflow-ready platform. Microsoft’s IQ stack ties agents to a unified semantic data layer, governance, and business-context tools that simplify adoption for CIOs. AWS has started to position agentic AI, Bedrock, and the data layer as a unified stack, but substantial engineering lift is still required to achieve broad enterprise cohesion.
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