“Platformization” eventually comes to every high-profile IT space as the number of tools and amount of complexity increases. Companies want to build platforms because they generate profits, and companies want to buy platforms because integration is a given and therefore deployment is easier and faster as new functions are added.
As an example, it’s happening rapidly in cybersecurity, with the sharp rise in the number and sophistication of cyberthreats and expanding attack surface driving enterprise demand for fewer point products that they have to integrate and maintain themselves and more tightly integrated offerings that can more easily and simply provide their defense needs.
The same trend can be seen in AI, as the myriad tools in the stack for everything from model development and governance to security and, now, agents continue to flood the market from cloud giants to pure-play AI vendors to smaller startups.
As IBM wrote recently: “AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction. Some AI platforms also provide advanced AI capabilities, such as natural language processing (NLP) and speech recognition.”
Those are the driving ideas behind Google’s new Gemini Enterprise, a platform that Google Cloud chief executive officer Thomas Kurian calls a “front door” into the growing number of AI tools and services that the hyperscaler has rolled out and those that will come in the future.
That includes Google’s Agent Development Kit, an open source framework introduced at the Google Cloud NEXT 2025 conference in April and designed to make it easier and quicker for developers to build agentic AI applications that are production-ready and created with more precise and flexible tools. It’s an open version of the framework Google uses with such products as Agentspace – a multimodal search agent introduced in December 2024 to bring together the advanced reasoning in Gemini, search, and enterprise data to the enterprise – and its Customer Engagement Suite.
There also is Google’s Agent2Agent (A2A) protocol, unveiled in April, to make it easier for agents to collaborate, and the Agent Payment Protocol (AP2) to let agents interact and transact agent-led payments across multiple platforms, both part of a larger push in the industry for protocols to make AI and agents more useful.
Google also includes the AI elements that it provides, from its Vertex AI development platform to infrastructure – including GPUs and its own Tensor Processing Units (TPUs) for machine learning workloads – to its AI Agent Marketplace that lets developers and organizations to create, buy, and sell agents for a range of tasks, from e-commerce to management.
“We’ve put all of that for users into one single user experience,” Kurian told journalists. “Gemini Enterprise is integrating all of these pieces into a super easy-to-use platform for every user in every company – no matter how small or how large – and teams and departments within these companies to use AI at scale.”
Gemini Enterprise gives organizations “a front door to access all this,” he said.
The new platform builds on the vendor’s belief that for the capabilities of AI to be fully realized, the technology needs to be more than chatbots, according to Alphabet and Google chief executive officer Sundar Pichai.
“You need a comprehensive and integrated platform that brings all your company’s data, tools, and people together in one secure place,” Pichai wrote. “Gemini Enterprise is an AI-powered conversational platform designed to bring the full power of Google AI to every employee for every workflow. Built with Google’s most advanced Gemini models, it enables you to chat with your company’s documents, data, and applications. It also gives you the tools to build and deploy AI agents, as well as a suite of pre-built agents, and is grounded in your company’s information and your personal context at work.”
The Core Components
The Gemini models are part of Google’s six core components for Gemini Enterprise, according to Kurian. There also is a no-code workbench that users from any department can use to analyze information, have agents to automate workflows, and to chat, search, and direct processes throughout an organization.
Through the workbench, individuals can “chat with all of your enterprise systems – your ERP system, your CRM system, your enterprise documents and databases. The second is so you can get your information from there, have it summarized, and have it very easy to find all the information in your organization. You can also do the same with the Internet.”
Google also offers what it calls a taskforce for creating custom agents or using pre-built agents from Google or partners via the marketplace for a range of specific jobs, from deep research to drawing out insights from data. In addition, through Gemini Enterprise, organizations can connect to their data that is held outside of Google Workspace and in others applications, such as Microsoft 365 office automation tools, Salesforce CRM, and SAP ERP.
“We give you packaged connectors to connect the large language model in Gemini Enterprise to all of your internal systems – Microsoft Office, SharePoint, ERP systems, CRM systems, coding tools – to make it easy,” Kurian said. “You don’t have to do it. We integrate it for you. We also remember who you are and what you do and use it to personalize the context you have when you work with a large language model.”
The last component is a governance framework to ensure which agents were deployed, monitor their use and security, and audit their functions.
Growing The Cloud Business
All this comes as Google continues to grow its cloud business as the global cloud infrastructure services space rapidly expands. The second quarter, the market almost reached $99 billion, a $20 billion jump over the same time in 2024 and the third consecutive quarter with year-over-year growth of 24 percent to 25 percent, according to Synergy Research Group.
<<Synergy numbers>>
Google Cloud is still solidly in third place with 13 percent of the market – Amazon Web Services accounts for 30 percent and Microsoft Azure at 20 percent – but Pichai noted that the business in the second quarter surpassed a $50 billion annual run rate and that each of the 13 product lines generated more than $1 billion in annual revenue.
He added that “much of this growth is driven by AI, with 65 percent of our cloud customers already using our AI products. Those customers include nine of the top ten AI labs and nearly all AI unicorns.”
I’m sure compliance departments rejoice at the thought of Hannah from HR spinning up an undocumented AI pipeline that ingests stuff from controlling, the ERP, strategy, legal, and R&D, just to prove to her coworker that the new intern in finance is a good catch.