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Google’s AI Comeback Story

At the start of 2025, skepticism dominated investor sentiment around Google’s position in artificial intelligence. The rapid rise of OpenAI and the mass adoption of ChatGPT had created a narrative that Google, despite its research legacy, was falling behind in execution. Twelve months later, that narrative has shifted sharply. Alphabet shares ended the year with their strongest annual performance since 2009, signaling renewed confidence in Google’s AI strategy and its ability to compete at the highest level.

At the center of this turnaround is DeepMind, the London-founded AI lab acquired by Google in 2014 for roughly £400 million. Once known primarily for research breakthroughs like AlphaGo, DeepMind has now become the operational core of Google’s AI development and deployment engine.

DeepMind as the Engine of Google AI

In an interview with CNBC’s podcast The Tech Download, DeepMind founder and CEO Demis Hassabis described the lab as the “engine room” powering Google’s AI ambitions. According to Hassabis, nearly all foundational AI technologies now originate within DeepMind before being rapidly distributed across Google’s ecosystem, including Search, Workspace, Android, and cloud services.

Over the past two years, Google has restructured its internal AI operations to prioritize speed and scalability. This included unifying DeepMind with Google Brain in 2023, a strategic move that eliminated silos and created a single organization responsible for both cutting-edge research and real-world deployment. The result has been a streamlined pipeline that allows new models to move from lab to product in months rather than years.

Daily Strategy Calls at the Top

One of the clearest signals of DeepMind’s importance is the close working relationship between Hassabis and Google CEO Sundar Pichai. Hassabis revealed that the two executives speak almost every day, often discussing high-level strategy, product direction, and adjustments to AI roadmaps.

These frequent conversations allow Google to make rapid decisions in response to competitive pressure. Roadmaps are no longer static, multi-year plans but living documents that can be revised in real time as new breakthroughs emerge or rivals accelerate their own releases. This operating model reflects a broader cultural shift inside Google toward a more startup-like mindset, emphasizing speed, iteration, and accountability.

From Research Leadership to Product Execution

Google’s challenge was never a lack of innovation. The transformer architecture that underpins modern large language models was developed by Google researchers, a fact that underscores the company’s deep technical roots. The problem, as Hassabis acknowledged, was execution. Competitors like OpenAI were faster at commercializing and scaling new ideas, capturing mindshare and users before Google could fully respond.

That gap has narrowed significantly. The launch of Gemini 2.5 in March 2025 marked a turning point, demonstrating improvements in reasoning, speed, and multimodal capabilities. Later in the year, Gemini 3 further strengthened Google’s position, earning praise from enterprise customers, developers, and industry leaders for its performance and reliability.

Crucially, Gemini models are now designed to integrate seamlessly across Google’s product suite. Updates to Search, advertising tools, productivity software, and developer platforms can all draw from the same core AI models, reducing duplication and accelerating innovation.

Competing in a Crowded and Aggressive Market

Google’s renewed momentum comes amid what Hassabis described as the most intense competitive environment the technology sector has ever experienced. Beyond OpenAI, the company faces pressure from Amazon-backed Anthropic, AI-native search platforms like Perplexity, and in-house efforts from major cloud providers investing tens of billions of dollars into AI infrastructure.

Veterans with decades of experience in the industry have told Hassabis that the current AI race surpasses previous cycles in both speed and scale. The stakes are high, not only in terms of market share but also in shaping how AI is embedded into everyday digital life.

Balancing Speed, Scale, and Long-Term Vision

Despite the short-term urgency, DeepMind and Google remain focused on a long-term goal: achieving artificial general intelligence that is as capable as humans while being developed responsibly and safely. Hassabis emphasized that daily discussions with Pichai balance immediate competitive needs with this broader ambition, ensuring that rapid progress does not come at the expense of strategic coherence or safety.

This dual focus has positioned Google to adapt regardless of how the AI market evolves. The company’s vast underlying businesses in search, advertising, cloud computing, and consumer devices provide both financial resilience and distribution power that few rivals can match.

Is the AI Boom a Bubble?

As global tech companies commit hundreds of billions of dollars to data centers, chips, and AI talent, questions about a potential bubble have intensified. Venture capital has flowed into AI startups at unprecedented valuations, sometimes with limited products or revenue to justify the hype.

Hassabis offered a nuanced view, suggesting that parts of the market may indeed be overheated while others reflect genuine long-term value. He compared the current moment to the dot-com era, when excessive speculation eventually gave way to a smaller group of durable, transformative companies.

According to Hassabis, funding rounds valuing early-stage AI firms in the tens of billions without meaningful products are unlikely to be sustainable. However, he remains confident that AI itself will endure as one of the most transformative technologies ever created, reshaping industries and creating new economic foundations.

Positioned to Win Either Way

Whether the AI boom continues its rapid ascent or experiences a market correction, Google believes it is well positioned. Its diversified revenue streams, global scale, and deep integration of AI into core products provide a buffer against volatility. More importantly, the tighter alignment between DeepMind and Google’s leadership has created an organization capable of moving quickly without losing sight of its long-term mission.

As competition intensifies in 2026 and beyond, Google’s daily, hands-on approach to AI strategy may prove to be its most important advantage in a race where speed, scale, and execution matter more than ever.

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