Gartner: Google Cloud Next showed a shift from AI tools to agentic systems

On April 23, 2026, Gartner described Google Cloud Next 2026 as a turning point. According to analyst Moutusi Sau, this is no longer about adding individual artificial intelligence features to existing applications. In her view, Google showed a coordinated move toward an architecture in which autonomous and semi-autonomous agents are treated as a distinct operational layer. This means changes in infrastructure, data platforms, development tools and risk governance. For enterprise IT, the important point is that agents create different requirements than traditional analytics. They need data semantics, persistent rules management, cost control and the ability to cooperate across systems. Gartner explicitly warns that traditional application architectures were not designed for this type of operation. Agentic AI is therefore not just another add-on to the cloud. It is pressure to rebuild the company's data and operating foundations. A concrete example is Gemini Enterprise Agent Platform. Gartner says it brings models, development, testing, deployment and governance into one agent environment. Functions such as pre-deployment simulation, operational evaluation and automatic improvement are intended to enable management of large groups of agents even in regulated industries. The benefit is clear: fewer fragmented tools and a faster path to value. The risk is equally clear: greater dependence on one vendor's platform. Sau uses a precise formulation: according to Gartner, Google's openness is tilted toward lock-in. In other words, Google supports multiple models and access to data across clouds, but agent identity, rules and lifecycle remain concentrated in Google Cloud. Gartner therefore recommends piloting aggressively, but not locking into a single platform. By 2027, companies should maintain at least one additional agent operating capability with another large provider. The business impact is significant. An agent platform may become as strategic a layer as an enterprise system or data warehouse. A poor choice can mean expensive migration, weaker negotiating power or regulatory problems. A good choice can connect data, knowledge and human work into a faster operating model.

Gartner: Google Cloud Next showed a shift from AI tools to agentic systems

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