Google Cloud Next ’25 showcased a clear evolution in Google Cloud’s enterprise strategy, moving beyond standalone product announcements, towards building an integrated, modular platform for artificial intelligence (AI)-led transformation.
Over three packed days, the tech providers introduced innovations spanning agent orchestration, infrastructure, networking, and industry-specific solutions.
These aforementioned announcements reflect the growing platform-centric AI focus, where modularity, openness, and integration matter just as much as model performance. It is now all about leveraging this strategy to create and offer distinct “play arenas” for the ecosystem entities, inviting collaboration from enterprises, Independent Software Vendors (ISVs), and service providers.
But more than the breadth of launches, it was the unifying intent behind them that stood out: enabling scalable, secure, and flexible adoption across varied enterprise environments. After carving out a strong position in the enterprise cloud space, Google Cloud is now accelerating adoption through product innovations and a partner-led sales motion that reinforces its ecosystem-first approach.
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Agents seem to be the central focus in Google Cloud’s roadmap
Google Cloud is moving beyond prebuilt AI tools, to establish itself as the foundational infrastructure layer for enterprise AI. One of the headline themes was Google’s push into Systems of Action (SoA) or AI agents, intelligent platforms that convert insights into execution by orchestrating decisions, enabling autonomy, and bridging the gap between intelligence and scalable action. These systems mark a critical shift from traditional Systems of Record and Engagement toward platforms capable of driving dynamic, AI-managed operations at scale.
With AgentSpace bringing together Gemini models, enterprise search, and no-code tools, and the introduction of the Agent2Agent (A2A) protocol, Google Cloud is leaning into the next evolution of AI: agents that can collaborate and act, not just respond. In parallel, Google Cloud is aiming to enhance trust and governance with AI-powered security agents, SynthID watermarks, and copyright protections, pragmatic steps aimed at easing adoption barriers in regulated or risk-sensitive environments.
And while some of this might sound futuristic, it is grounded in a practical need: enterprises do not want 10 different AI tools that do not talk to each other. They want AI systems that work together, and Google Cloud’s open approach here could prove valuable as companies look to integrate AI across different environments.
Infrastructure to power AI at scale
Google is refining the infrastructure layer of its AI stack to better support enterprise deployment needs. The introduction of Ironwood TPUs, optimized for inference, alongside continued support for Graphics Processing Unit (GPUs) such as NVIDIA’s Blackwell, reflects a focus on flexibility over ecosystem lock-in. This also addresses growing enterprise concerns around the cost and efficiency of running AI workloads at scale and not just training them. The same theme extends to hybrid deployment options, expanded access to networking capabilities through Cloud WAN, and support for open-source models such as LLama 4 in Vertex AI.
It is not just about having the fastest tools, it is about aiming to address common enterprise needs to make AI useful in their real-world environments, whether they are cloud-native, hybrid, or working in highly regulated industries.
Meeting enterprises on their own turf
One of the more practical shifts was around deployment. Google Cloud is extending support for air-gapped environments through its Google Distributed Cloud (GDC) platform. That means even organizations in sensitive sectors such as defense or healthcare can now run Gemini models on-premises.
This hybrid approach assists large enterprises that are not moving entirely to cloud soon. By partnering with Dell and NVIDIA for infrastructure, it is signaling that it wants to help enterprises bring AI to where their data lives, not the other way around.
Enterprises can also gain flexibility in model choice, deployment models (cloud, edge, on-prem), and integration workflows; whereas service and technology providers have an expanded role to play in architecting, customizing, and governing multi-agent, multi-model solutions.
Everyday AI: embedding AI into workflows
What is the point of all this tech if it does not show where people spend their time? That seemed to be the thinking behind Google Cloud’s push into day-to-day productivity. Google Cloud is now embedding AI into everyday enterprise workflows through tools such as Workspace Flows (for automating tasks across Gmail, Docs, and Sheets), Gemini Code Assist (for developer support), and Colab Enterprise (for collaborative AI development).
Enhanced voice and video agents also support customer-facing use cases. Everest Group’s early estimates indicate that up to a 50% improvement in AI-managed exception handling, 30–40% better infrastructure scalability, and 25–35% productivity gains from SoA PoCs, is making Google Cloud’s case for AI’s presence in everyday workflows.
Key takeaways
- Strategic moves such as open-sourcing Agent2Agent, integrating LLaMA 4 and Mistral into Vertex AI, and expanding Model Garden indicate a shift toward open-sourced, community-driven AI rather than proprietary, closed ecosystems
- This strategy is starting to look distinct from some of its peers. Microsoft has leaned heavily into app-level AI through Copilot, while AWS is focused on developer tools and infrastructure. Google Cloud is trying to do both, and to do it with a modular, interoperable approach at the same time
- Challenges remain for enterprises, including integration complexity, governance concerns, and AI skill gaps, but Google Cloud’s roadmap signals that it is actively addressing them
For service providers, these developments open new monetization opportunities in systems integration, data orchestration, and AI-driven transformation services. They will play a vital role in customizing, integrating, and scaling these capabilities for enterprise clients. Providers that invest in Google Cloud-specific accelerators, security frameworks, and vertical blueprints will be well-placed to demonstrate value and differentiate themselves. Additionally, the proliferation of multi-agent architectures and connector-rich ecosystems creates fertile ground for monetization through systems integration, low-code orchestration, and managed AI services.
For technology and ISV partners, Google Cloud’s increasingly open model marketplace (Model Garden), tools such as Vertex AI Extensions, and support for third-party agents represent an expanded surface area for innovation. Technology providers now have clearer pathways to distribute, monetize, and integrate their offerings natively into Google Cloud workflows.
At the same time, these developments establish new expectations for integration readiness: AI solutions must be Application Programming Interface (API)-ready, composable, and interoperable with Gemini agents and other platform services. Providers that can embed natively within Google Cloud’s growing AI fabric stand to benefit from increased exposure, co-sell potential, and alignment with enterprises seeking scalable, vendor-neutral AI solutions.
By fostering a symbiotic relationship with open source, Google Cloud is not just contributing to innovation, it is trying to ensure that its cloud becomes the default execution layer for AI systems developed across the broader ecosystem.
If you found this blog insightful, don’t miss our upcoming webinar, Reshaping the Software Industry: The Rise of Systems of Action. You can also explore our related blog Google Cloud’s US$32B Wiz Move: A Power Shift In Cloud Security Ecosystem | Blog – Everest Group, for a deeper dive into another critical aspect of the evolving cloud landscape.
If you have any questions or want to discuss your Google Cloud and Systems of Action adoption strategy further, please contact Abhishek Singh ([email protected]), Kaustubh K ([email protected]), Zachariah Chirayil ([email protected]), Aastha Chakrawarty ([email protected]), or Vyom Nagaich ([email protected]).
