Pichai revealed that the Gemini app has reached 650 million monthly active users, while AI Mode now serves 75 million daily users. He added that the company delivered 100 product updates in Q3, which boosted query growth across Google Search. Cloud revenue saw major acceleration, with AI-related demand driving a 46% quarterly growth in backlog to $155 billion.

Philipp Schindler, Google’s Chief Business Officer, said Google Services revenue reached $87 billion for the quarter, marking a 14% annual increase. Search and YouTube revenues grew 15%, led by strong performance in retail and financial services advertising.

Pichai highlighted that Google is scaling advanced chips, including NVIDIA GPUs and its own TPUs, across data centers. He added that AI Overviews and AI Mode are helping expand commercial queries, creating new opportunities for monetisation. Alphabet’s focus remains on AI-driven innovation to enhance user engagement and business growth.

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Choudhary said investments in AI across banking, insurance, and payments may reach $100 billion by 2027. Around 78% of financial organizations already use AI in some form, up from 55% in 2023. The industry, he noted, is preparing for how fast AI will reshape its future.

He explained that Generative AI and Agentic AI are leading this change. These technologies improve fraud detection, automate compliance, enhance trading accuracy, and elevate customer experience. They could raise global banking productivity by up to $340 billion each year.

Choudhary praised India’s progress in digital innovation through NPCI’s initiatives like UPI Lite, UPI 123Pay, and UPI for Her. He said these solutions expand financial access and support women entrepreneurs and rural users across the country.

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The announcement follows Nvidia’s $100 billion investment, which gives OpenAI access to roughly 10 gigawatts of AI data centers. This deal alone surpasses the GDP of some countries. Altman also launched Stargate, a $500 billion partnership with Oracle and SoftBank to build massive AI super-hubs in the U.S. The first site is under construction in Abilene, Texas, with five more locations planned, totaling nearly 7 gigawatts of capacity.

Experts have raised concerns about energy availability. Running such massive facilities requires enormous electricity, and the grid may not be ready. Brad Gastwirth of Circular Technology called energy the “silent bottleneck” for Silicon Valley’s AI projects. Producing a gigawatt each week is like powering a major city repeatedly, posing climate and infrastructure challenges.

Despite this, Altman remains optimistic. He sees the project as an opportunity to rethink infrastructure at a planetary scale. If successful, OpenAI will not only train larger AI models but also reshape how technology and energy intersect worldwide.

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The report states global incremental AI compute needs may reach 200 gigawatts by 2030, with the US accounting for nearly half. Shifting IT budgets to cloud and reinvesting AI savings would still not cover the full costs. AI compute demand is growing more than twice as fast as Moore’s Law.

Experts warn that governments and leading providers are entering an AI arms race. Overbuilding or underbuilding infrastructure is a major challenge. Innovation, supply constraints, and algorithmic efficiency will be critical to meeting demand over the coming years, Bain said.

While some companies have scaled AI into core workflows, achieving 10-25% EBITDA gains, most remain in experimentation mode. Global supply chains face fragmentation due to tariffs, export controls, and sovereign AI initiatives. Experts note that AI is now a strategic advantage tied to economic, political, and military power.

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