Google could overtake Nvidia to become the world’s most valuable company by market capitalisation by the end of 2026, according to an analyst assessment at Seeking Alpha that points to a growing challenge facing the technology industry: the rising cost and constraints of AI computing infrastructure. The view comes as Alphabet, Google’s parent company, ramps up spending on data centres and custom AI hardware while reporting strong growth across search and cloud businesses. The analyst argues that Google’s broad AI platform and in-house chips position it to benefit as companies seek alternatives to expensive, power-hungry AI processors, a pressure point increasingly described as one of the industry’s biggest headaches.
ChatGPT did not weaken Google’s AI position: Analyst
First reason pointed by the analyst behind Google’s recent market-cap gains were also driven by a shift in investor perception around artificial intelligence leadership. He argues that the widely held belief that OpenAI’s AI chatbot– ChatGPT would significantly damage Google Search proved incorrect, despite early enthusiasm around the chatbot. According to the analysis, Google’s continued growth in search revenue and the rollout of its own AI products undermined the idea that OpenAI had overtaken Google as the industry’s AI leader. The reassessment, he said, helped narrow the valuation gap between Google and Nvidia.
Google’s platform and the AI infrastructure
The analysis notes that Alphabet’s planned capital expenditure of up to $180 billion for 2026 has drawn attention, but says the focus should instead be on Google’s underlying business performance. Google Search revenue grew 17% year-on-year in the latest quarter, while Google Cloud revenue rose 48%, with a reported backlog of $240 billion.The analyst argues that Google’s strength lies in its ability to monetise AI across a wide range of products, including Google Search, advertising, cloud, and vidoe-streaming platform YouTube. Unlike rivals that rely heavily on third-party chips, Google designs its own Tensor Processing Units (TPUs), giving it more control over costs, performance, and energy use, the analyst claims.
Pressure on world’s biggest chipmaker, Nvidia
The assessment also points to increasing competition for Jensen Huang-led Nvidia, whose high-margin GPUs dominate AI training but face challenges in the inference market, where efficiency and power consumption matter more. As pointed out in the report, custom chips from companies such as Broadcom, Amazon, and Google are gaining traction as cheaper and more energy-efficient alternatives.As AI workloads shift toward inference at scale, the analyst believes demand for application-specific processors will grow, reducing reliance on Nvidia’s GPUs. This shift, combined with Google’s expanding cloud business and proprietary hardware, is seen as a key factor that could allow Google to close the remaining market-cap gap and surpass Nvidia, potentially as early as 2026.The prediction comes amid heightened investor scrutiny of AI spending, power availability, and long-term returns across the technology sector.
