Google Cloud

Alphabet’s Q3 earnings report exceeded expectations, sending shares up 4%. Revenue hit $102.35 billion, a first for the company. Increased capital expenditure, now projected at $91-93 billion, reflects investment in AI infrastructure and Google Cloud’s growth. Google Cloud backlog reached $155 billion. Analysts see Alphabet addressing AI concerns and revised price targets upwards, with Goldman Sachs setting a $330 target and JPMorgan $340, highlighting confidence in Alphabet’s execution and AI’s positive impact on Google Search revenue.

Alphabet’s Q3 earnings exceeded expectations, driving shares up 5% after-hours. Revenue reached $102.35 billion, with EPS at $3.10. Google Cloud’s revenue grew 35% to $15.15 billion, fueled by AI demand. Alphabet is increasing 2025 capital expenditure to $91-93 billion. YouTube ad revenue hit $10.26 billion, and overall ad revenue was $74.18 billion. Net income surged to $34.97 billion, despite a $3.45 billion EU antitrust fine. Cloud customer base growth is high, and AI product use is increasing.

Google Cloud launched Gemini Enterprise, an AI platform designed to streamline AI agent development and deployment, aiming to transform enterprise workflows. It features Gemini models, a no-code workbench, pre-built agents, and seamless data integration with systems like Salesforce and Microsoft Teams. Virgin Voyages and Macquarie Bank are early adopters, demonstrating productivity gains and widespread AI training. Gemini Enterprise emphasizes governance, security, and an open ecosystem. Pricing starts at $21 per seat for smaller businesses and $30 for larger organizations.

Google has laid off over 100 design team employees, primarily within Google Cloud’s user experience research and platform services groups. This reduction aligns with Google’s strategic shift to prioritize AI investments amid increasing competition from companies like Microsoft. The layoffs, impacting U.S.-based roles, follow previous cost-cutting measures and a streamlining of Google’s organizational structure. It suggests a leaner, potentially AI-driven design approach as Google focuses on efficiency and data-driven design. This move reflects a broader industry trend of workforce reductions and resource realignment towards AI and emerging technologies.

Google Cloud’s CEO Thomas Kurian says the division is already profiting significantly from AI investments. At a recent conference, Kurian outlined monetization strategies including consumption-based pricing for AI infrastructure (GPUs, TPUs, models via “tokens”) and subscription models for services like cybersecurity and Google Workspace. Upselling to higher-priced AI tiers also contributes to revenue growth. Google Cloud’s customer commitment backlog is at $106 billion, and it secured a $10 billion cloud contract with Meta. Cloud revenue grew 32% year-over-year in the latest quarter.

At Google Singapore, Google Cloud’s Mark Johnston highlighted the ongoing struggle for cybersecurity defenders. He revealed that 69% of APAC breaches are detected by external parties, underscoring detection weaknesses. Google Cloud is leveraging AI to improve defenses, but acknowledges AI also empowers attackers. Initiatives like Project Zero’s “Big Sleep” use AI for vulnerability discovery. While promising, AI automation introduces risks and requires human oversight. Budget constraints and the need for partners offering scalable solutions pose challenges for CISOs. Post-quantum cryptography deployment is underway.

At Security Summit 2025, Google Cloud outlined its AI-powered vision for proactive security. Key announcements include AI Protection enhancements within Security Command Center for AI agent discovery and threat protection (like prompt injection). The vision extends to an “agentic SOC” with AI agents assisting in threat management and alert investigation. Google Security Operations receives AI-driven capabilities (Gemini AI), unified dashboards, and upgrades to the Trusted Cloud, focusing on compliance, smarter access control, and expanded data/network security for AI. The goal: secure innovation through AI-embedded security.