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Former Google CEO Eric Schmidt says AI boom is not a bubble but ...

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  Published in Stocks and Investing on Tuesday, October 28th 2025 at 2:33 GMT by moneycontrol.com
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Eric Schmidt Says the AI Boom Is Real – Not a Bubble

In a recent interview with MoneyControl, former Google chief executive Eric Schmidt set the record straight on what many analysts are calling the “AI bubble.” The veteran tech leader argues that artificial intelligence is here to stay and that its current surge is more a transformation than a speculative frenzy. Schmidt, who stepped down from Google’s CEO position in 2018, now heads Alphabet’s Board of Directors and continues to be a key voice in shaping the industry’s trajectory.

1. A Long‑Term View of AI Growth

Schmidt opens by contextualizing the AI boom within a broader technological evolution. He points out that every major tech wave—whether it was the rise of the personal computer, the Internet, or mobile computing—was initially met with skepticism and fears of over‑valuation. “We’ve seen that pattern repeatedly,” he says. “When people first heard about the potential of AI, they were right to ask whether it was a bubble. But what we’re witnessing now is a foundational shift in how we build, innovate, and deliver value.”

The former CEO stresses that AI isn’t just another layer of software; it’s a set of capabilities—natural language processing, computer vision, reinforcement learning—that can be embedded in any domain. From healthcare to finance, AI is becoming an integral part of the operational fabric. “You can’t separate it from the core,” Schmidt notes, referencing how AI is already embedded in the recommendation engines of e‑commerce sites and the fraud‑detection algorithms used by banks.

2. Why the AI Boom Shouldn’t Be Dismissed as a Bubble

Schmidt draws a clear line between hype and reality. While the market for generative AI models (e.g., ChatGPT, Gemini, and other large language models) has spiked dramatically, he argues that the underlying technology stack—cloud infrastructure, GPU advances, and open‑source frameworks—is far from saturated. According to him, the current “exponential” growth in AI is due to the convergence of three forces:

1. Hardware Availability – The rapid deployment of powerful GPUs and TPUs has drastically reduced the cost of training large models. Schmidt notes that Google’s own TPU v4 has already set a new benchmark for speed and energy efficiency.

2. Algorithmic Improvements – The breakthrough in transformer architectures and self‑supervised learning has unlocked unprecedented levels of language understanding and generation. This progress is far from a one‑off event; new model families are being released at an accelerating pace.

3. Widespread Adoption – More companies, from startups to Fortune‑500 giants, are embedding AI into their product lines. This is not just a fad; it’s a shift in competitive advantage. “The companies that fail to adopt AI risk becoming irrelevant,” Schmidt warns.

He references a study from McKinsey that projected AI could deliver $13 trillion in global economic value by 2030, underlining the tangible upside rather than speculative bubbles.

3. The Human Element: Talent and Ethics

A recurring theme in Schmidt’s discussion is the human dimension of AI. He emphasizes that the technology itself is not a silver bullet; it requires talent—data scientists, engineers, ethicists—to turn models into products. Schmidt stresses that the current talent crunch is real, with many organizations struggling to hire seasoned AI practitioners. He calls for more comprehensive AI education at universities and professional development programs.

On ethics, Schmidt acknowledges that AI’s rapid deployment raises concerns around bias, privacy, and accountability. He cites Google’s own experience with the “Perspective” tool, which uses AI to detect toxic language, as a case study of balancing innovation with responsibility. He suggests that regulatory frameworks should evolve in tandem with technology, rather than stifle it. “We need proactive governance, not reactive bans,” he asserts.

4. AI’s Impact on Jobs and the Economy

One of the most common worries about AI is job displacement. Schmidt, however, frames the conversation in terms of job transformation rather than loss. He notes that AI can automate routine tasks, thereby freeing up human workers for higher‑value activities. In industries like manufacturing, AI-powered robots and predictive maintenance are already reducing downtime and safety incidents.

Moreover, he points to the surge in demand for new roles such as AI ethicists, model auditors, and data curators. “If we invest in reskilling, the net effect on employment can be positive,” he argues. Schmidt highlights Google’s own internal initiatives—like the “AI Residency Program”—as examples of how companies can nurture next‑generation talent.

5. Financial Market Reactions and Investor Sentiment

Schmidt addresses the volatility that has followed the AI hype cycle. He acknowledges that the market has overreacted at times, pushing valuations for AI startups to unsustainable levels. Yet he remains optimistic about the underlying fundamentals. He cites specific examples such as OpenAI’s licensing deals with Microsoft and the surge in investment for generative AI startups in 2023.

In an interview excerpt from TechCrunch (linked within the MoneyControl article), Schmidt mentioned that while short‑term swings are inevitable, the long‑term trend is upward. “We’re not just building tools; we’re building platforms that create an entire ecosystem of services,” he explains.

6. Looking Ahead: The Next Decades of AI

To cap off the interview, Schmidt outlines what he believes will shape AI’s future:

• Generalization and Multimodal Models – Models that can handle text, images, audio, and video simultaneously, unlocking new use cases in education and entertainment.
• AI‑Powered Personalization at Scale – Beyond product recommendations, AI will tailor user experiences in real time across sectors.
• AI Governance and Transparency – As AI systems become more complex, the need for explainability and accountability will grow. Schmidt calls for industry‑wide standards.
• Sustainability – He stresses the importance of developing energy‑efficient models to minimize the environmental impact of large‑scale AI training.

Schmidt’s concluding thought is a call for collaboration across industries, academia, and governments. “If we treat AI as a public good rather than a private monopoly, the benefits can be distributed more equitably,” he says.

7. Bottom Line

Eric Schmidt’s perspective provides a measured, data‑driven lens on the AI boom. While acknowledging the risks—valuation volatility, talent shortages, and ethical dilemmas—he firmly believes that AI’s transformative power outweighs the uncertainties. According to the former Google CEO, the industry is no longer in a speculative bubble but in a critical growth phase that will redefine how we work, communicate, and solve complex problems.

For those following the AI narrative, Schmidt’s insights suggest that the best way forward is to invest in talent, infrastructure, and governance, rather than shying away from the opportunities that AI presents.