For the best part of a year, Google has been telling an ambitious story about enterprise AI agent adoption\u2026 now it has the receipts to back it up.<\/p>\n
Speaking to investors during the company\u2019s Q1 2026 earnings call, Alphabet (Google\u2019s parent company) CEO Sundar Pichai revealed that revenue from products built on Google\u2019s GenAI models grew nearly 800% year-over-year.<\/p>\n
Gemini Enterprise paid monthly active users also grew 40% quarter-over-quarter in the same period, with Bosch, Merck, and Mars Inc. named among the major global brands now active on the platform.<\/p>\n
Speaking to investors during the call, Pichai said:<\/p>\n
\u201cWe are winning new customers faster with new customer acquisition doubling compared to the same period last year.<\/p>\n
\u201cWe are seeing strong deal momentum, doubling the number of $100 million to $1 billion deals year-on-year and signing multiple billion-dollar-plus deals.\u201d<\/p>\n
Until now, Google\u2019s enterprise AI build-out has largely been tracked through product launches and partnership agreements.<\/p>\n
CX Today has followed much of that journey \u2013 from the January launch of Gemini Enterprise for Customer Experience<\/a>, to the SAP marketing agents integration in April<\/a>, and the expanding Salesforce partnership<\/a>.<\/p>\n What the latest earnings call added was something more tangible: evidence that enterprise buyers are committing at scale, and that those commitments are growing in size.<\/p>\n The Platform Behind the Numbers<\/p>\n The results arrived alongside a new Gemini Enterprise Agent Platform, unveiled at Google Cloud Next.<\/p>\n Pichai described it as empowering users to \u201cbuild, orchestrate, govern, and optimize agents with the controls that enterprise customers need.\u201d<\/p>\n New capabilities added to the Gemini Enterprise app (projects, canvas, long-running agents, and skills) are designed to push agent deployment well beyond specialist IT teams.<\/p>\n \u201cEvery employee can build agents,\u201d Pichai said.<\/p>\n Alongside the platform, Google introduced what it is calling an agentic data cloud, with Pichai claiming that it gives \u201cagents business context from enterprise data to help them reason intelligently,\u201d drawing on Google\u2019s Cloud Lake House, knowledge catalog, and deep research agents.<\/p>\n For CX and contact center teams, this is the infrastructure layer that determines how useful an enterprise AI agent can actually be.<\/p>\n An agent working from real-time customer history, product inventory, and transaction data is a very different proposition from one working off a static knowledge base \u2013 and Google is increasingly building with that distinction in mind.<\/p>\n A $462 Billion Backlog Tells Its Own Story<\/p>\n The AI agent numbers sit inside a broader Google Cloud performance that is accelerating quickly.<\/p>\n Alphabet CFO Anat Ashkenazi reported cloud revenues of $20 billion in Q1, up 63% year-over-year, with AI solutions named as the \u201clargest contributor to cloud\u2019s growth this quarter, driven by strong demand for industry-leading models, including Gemini 3.\u201d<\/p>\n Cloud backlog nearly doubled sequentially in Q1, reaching $462 billion, driven by what Ashkenazi called \u201cstrong demand for enterprise AI offerings.\u201d<\/p>\n The backlog figure is arguably more telling than the revenue line. Revenue reflects what enterprises have spent; backlog reflects what they have committed to spend.<\/p>\n A near-doubling in a single quarter suggests the enterprise AI evaluation phase is giving way to something more durable.<\/p>\n Reading the 800% Carefully<\/p>\n The near-800% growth rate will attract the most attention, but some context is useful.<\/p>\n Google hasn\u2019t disclosed the base from which that figure is calculated, and GenAI solution revenue is still reported within Cloud\u2019s broader numbers rather than broken out separately.<\/p>\n As the base expands \u2013 and based on the backlog, it is expanding fast \u2013 that growth rate will naturally compress.<\/p>\n What the Q1 results do establish is that Google has shifted its enterprise AI agent story from potential to performance.<\/p>\n