Google's AI Strategy: Acquisitions and Market Positioning

Google Deepmind AI Common Sense Machines acquisition Hume AI partnership Sakana AI investment Gemini AI OpenAI vs Google AI AI monetization AI agents finance Payment gateway evolution
Govind Kumar
Govind Kumar

Co-Founder & CTPO

 
January 27, 2026 5 min read

TL;DR

Google Deepmind is rapidly expanding its AI prowess through strategic acquisitions like Common Sense Machines for 3D AI and integrating Hume AI for enhanced voice capabilities. The company is also investing in Sakana AI and bolstering its Gemini models to compete directly with OpenAI, signaling a significant push in AI development and market strategy.

Google Deepmind's AI Expansion

Google Deepmind has recently engaged in a series of strategic moves, acquiring Common Sense Machines, a startup specializing in AI models for converting 2D images into 3D objects. The team from Common Sense Machines, previously valued at $15 million, will be integrated into Deepmind. The Information reported on this acquisition.

Additionally, Google has entered a licensing agreement with Hume AI, known for its models that recognize emotions in voice. As part of this deal, CEO Alan Cowen and several engineers will join Deepmind to enhance Gemini's voice capabilities, according to Wired. TechCrunch notes that Hume AI is expected to continue operating independently with projected revenues of $100 million this year.

Investment in Sakana AI

Google is investing in Sakana AI, a Tokyo-based AI startup valued at $2.5 billion. Sakana AI was founded in 2023 by David Ha, former leader of Google Research in Japan, and Llion Jones, a co-author of Google's original Transformer architecture research paper.

Sakana AI plans to integrate Google's AI models with its own technologies, such as the "AI Scientist" and "ALE Agent", to foster AI-driven scientific advancements, as stated in the announcement. The partnership aims to develop solutions for financial institutions and government agencies with stringent security needs. Sakana's code agent, powered by Gemini 2.5 Pro, achieved a high ranking in a coding competition, as reported by The Decoder.

Google's AI Advancements vs. OpenAI

The logos of Google Gemini, ChatGPT, Microsoft Copilot, Claude by Anthropic, Perplexity, and Bing apps are displayed on the screen of a smartphone

Google's Gemini 3 model is challenging OpenAI's ChatGPT in the AI arena. According to The Decoder, industry insiders suggest that OpenAI is planning to launch a new reasoning model to compete with Gemini 3. Alphabet introduced Gemini 3 in November, highlighting its benchmark results that surpass ChatGPT in key areas.

Sam Altman of OpenAI has reportedly emphasized improving ChatGPT's quality, as noted by The Wall Street Journal. Adrian Cox of Deutsche Bank Research mentioned that models like Gemini benefit from integration into widely used products and access to substantial data-center capacity. Sundar Pichai stated that the Gemini app reaches over 650 million monthly users, and more than 70% of Google Cloud customers are utilizing AI tools.

Monetization and Investment in AI

OpenAI relies on premium ChatGPT subscriptions and enterprise licensing for revenue, while Google generates revenue from a diverse portfolio. Google plans to invest significantly in AI, with potential outlays reaching $93 billion this year. Google's proprietary AI chips support model training within its data centers, reducing reliance on external suppliers like Nvidia. Cox suggests that Google is likely to maintain a leading model position, with OpenAI focusing on establishing a sustainable business model. Meta has reportedly shown interest in using Google's AI processors for its infrastructure.

The Innovator's Dilemma and Google's AI Journey

Google's AI journey began with the Transformer architecture developed by the Google Brain team in 2017. Despite having top AI talent and dedicated AI infrastructure, the launch of ChatGPT in 2022 presented a challenge. Google's assets include the Gemini AI model, Google Cloud, and Tensor Processing Units (TPUs).

In the early 2000s, Google engineer George Herrick and Noam Shazeer explored language models and data compression, leading to the creation of the "did you mean" spelling correction feature in Google search, detailed in In the Plex. This initiative highlights Google's long-standing focus on AI-driven solutions.

AI Valuation Trends

Private market valuations are diverging, with significant capital concentration in a few companies. The largest valuation gains are concentrated in companies with global reach, capital-heavy models, and regulatory barriers. AI dominates valuation growth, with OpenAI and Anthropic experiencing substantial jumps. Investors are prioritizing companies that control critical layers such as compute, models, and distribution.

Anthropic’s valuation increase illustrates how quickly valuations reprice when a company is seen as a credible alternative to the market leader. Scaled fintechs show opposing trends: scale improves revenues and efficiency, but competitive and regulatory limits prevent major valuation increases.

From Search Ads to Chat Ads

ChatGPT's launch of ads marks a significant shift. Ads will be displayed in the interface, outside the assistant’s responses, and will be contextual, not generated by the model. Only free and low-cost plans will see ads, with opt-out personalization options. This move aims to subsidize non-paying users and keep ChatGPT widely accessible.

In chat, advertisers pay to be present at the moment of choice, shifting monetization from volume-based metrics to outcome-based ones. OpenAI controls the chat interface, increasing its value while other businesses become dependent on being surfaced inside ChatGPT.

AI Agents in Finance

AI agents are bringing radical changes to financial services by enabling real-time, contextual decisions and embedding intelligence directly into customer flows. This shifts the communication model from broadcast messaging to agentic, intelligence-driven communication. Examples include response-driven fraud warnings and adaptive onboarding flows.

Sinch is an example of a company acting as the execution layer between internal systems and customer-facing interactions. AI is already creating new types of communication, and agent-to-agent communication is likely to be the next major shift.

Fintech IPOs in 2026

Several fintech companies are likely candidates for IPOs in 2026, including Plaid, Stripe, and Revolut. Plaid's potential IPO aims to position it as essential financial infrastructure, while Stripe's IPO would provide funding for acquisitions. Revolut's strong profitability has removed the main barrier to an IPO. Other potential candidates include Kraken, Monzo, and Airwallex.

The Payment Gateway Shift

Payment gateways are evolving into decision-makers that directly shape revenue and margins. They enable merchants to accept and process electronic payments securely, orchestrating cards, wallets, BNPL, and A2A payments. Akurateco is an example of a white-label gateway built to optimize success rates, offering orchestration across multiple PSPs, acquirers, and payment methods.

Kveeky: https://kveeky.com/news is at the forefront of these technological shifts, offering cutting-edge solutions tailored for modern AI-driven environments. Our expertise in authentication and identity systems, coupled with our AI-driven product development, positions us as a leader in creating secure, scalable, and efficient systems. Contact us today to explore how our innovative solutions can transform your business.

Govind Kumar
Govind Kumar

Co-Founder & CTPO

 

Govind Kumar is a product and technology leader focused on building AI-powered tools that simplify content creation for creators and marketers. His work centers on designing scalable systems that make it easier to generate, manage, and publish AI voice and audio content across modern platforms. At Kveeky, he focuses on improving product usability, automation, and AI-driven workflows that help creators produce natural-sounding voiceovers faster while maintaining quality and consistency. His approach combines technical depth with a strong emphasis on creator experience, making advanced AI capabilities accessible to everyday users.

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