LLM chatbots and search engines will coexist, says Google’s Raghavan

However, Google senior vice president Prabhakar Raghavan believes LLMs and search engines will co-exist. “I don’t think any one approach, whether it’s chatbots or LLM-based search engines, is going to completely replace the other,” he told Mint during his recent visit to Bengaluru.

Raghavan, who heads Google Search, Ads, Assistant, Maps, Commerce and Payments, said the number of queries users make on a daily basis is increasing faster than the growth of internet users. He believes the future of search is “not just about providing direct answers or lists of links, but about creating a more dynamic and synthesized experience.”

Raghavan, a computer scientist at heart, explained that while traditional searches offer static results like maps and reviews, LLMs can dynamically categorize options, such as “seafood restaurants” or “romantic places,” improving user engagement. However, he cautioned that “fluid, engaging answers” ​​can compromise factual accuracy, so a balance is needed.

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As for the impact of the shift to LLMs on Google’s ad revenue, which relies heavily on ads, Raghavan believes AI-powered ad personalization will keep advertising strong. AI can better match ads to user queries, which could make ads a more personalized experience. Subscription models could also co-exist with ads, in line with Google’s mission to achieve universal access, according to Raghavan.

In this context, Raghavan highlighted India’s significant contribution to AI and technology, driven by a large talent pool and investments in education. He noted India’s “substantial impact” through innovation, but stressed the importance of understanding local needs, such as the challenge of recognising Hinglish (a combination of Hindi and English) due to limited training data. Having a workforce in India, he explained, allows Google to address these unique requirements and gain valuable market insights, enhancing its global leadership.

I don’t think SEO is anti-search. My view is that if it helps the user get what they want, it’s a good thing. —Prabhakar Raghavan

He also acknowledged the gradual integration of LLM-based chatbots In the area of ​​commerce and payments, Google has stressed the need to proceed with caution. Because of the high stakes of transactions, any inaccuracies, such as incorrect product dimensions, could harm customers. As such, it explained, Google is moving slowly to ensure security and reliability in these areas, although broader integration is expected soon.

Raghavan also made a case for the future of search engine optimization (SEO), calling it an essential business practice. A study by researchers at Germany’s Leipzig University and others, for example, raised concerns about search engines’ handling of highly optimized affiliate content, suggesting that the line between legitimate content and spam is becoming more blurred, especially with generative AI.

While AI could improve the quality of content, Google will focus strictly on “search engine content” that confuses users. “I don’t think SEO is in any way antithetical to search. My view is: if it helps the user get what they want, that’s a good thing,” he said. But he qualified that so-called “search engine content” (he avoids the term “clickbait”) confuses users.

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Despite concerns that generative AI could worsen content quality, Raghavan maintained that Google’s focus is not on whether content is AI-generated, but on whether it is misleading. Raghavan noted that content quality has always been a challenge, but dismissed fears that AI will exacerbate this problem. According to him, while language models can mimic intelligent conversations like those of humans, they are far from achieving tasks such as proving complex mathematical theorems. However, they already perform tasks that are beyond human capability, such as folding 200 million proteins for drug discovery.

Therefore, using human intelligence as a benchmark for AI will not help, Raghavan believes. He added that while AI can help solve complex problems, such as proving mathematical theorems or deciphering Ramanujan’s notebooks, it is unlikely to replace human roles. Moreover, “While AGI (Artificial General Intelligence) is a matter of debate, the definition remains unclear. Instead of focusing on AGI, the focus should be on enhancing the current capabilities of AI to provide more context-sensitive and meaningful assistance,” he said.

Restrictions against Google

Asked about regulatory scrutiny over Google’s market dominance in digital advertising, Raghavan acknowledged that balancing the needs of users, publishers and advertisers is a challenge. “Google is addressing these tensions carefully, ensuring a balanced approach that respects all stakeholders. The solution remains a work in progress, but is central to Google’s ad tech strategy,” he said.

Over the past four years, Google’s dominance has attracted the attention of antitrust enforcement agencies such as the U.S. Department of Justice (DOJ). On August 6, the DOJ ruled that “Google is a monopolist and has acted as such to maintain its monopoly…” in the online search market. Kent Walker, president of Global Affairs, responded on X that Google plans to appeal. On Monday, September 9, Google will face a second major antitrust trial that focuses on its dominance in the advertising market. However, according to Wedbush Securities, while there is a potential for “short-term headline risk” or reputational damage from the trial, the financial impact appears minimal.

From traditional AI to GenAI

Meanwhile, Raghavan believes that traditional AI and generative AI (GenAI) are “evolving towards a more unified, multi-modal experience for users. Today, users don’t care whether it’s text, image, video or voice – it all blends together seamlessly.” To support his point, he cited the example of Google Lens where a user can point at some curtains and say, “I want that in green,” blending image and voice to find a product.

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“Younger users, in particular, view their devices as extensions of their senses and expect seamless interaction. This merging of AI subdisciplines — machine learning, deep learning, computer vision, image recognition, natural language processing (NLP), and GenAI, to name a few — into a cohesive, multimodal experience represents an exciting shift in AI development,” Raghavan explained. He added, “The goal is not to showcase AI for its own sake, but to improve user satisfaction, regardless of whether it is achieved through LLM, traditional indexing, or other methods.”

Strategy and leadership

Asked how a research-focused executive works with a business-oriented leader like Alphabet CEO Sundar Pichai, Raghavan said, “Successful leadership teams thrive on that diversity and debate, avoiding unhealthy environments where directives come from a single voice. Over time, a balance is found naturally through collaboration and debate.”

She added that as a leader, it’s important to know where and when to get involved, and when to step back and trust your team. “Once you’ve decided to delegate, you need to trust that they will deliver, but set a timeline to check that everything is going as planned, whether that’s in two weeks or two months. If things aren’t going as you had planned, the key is to ask the right questions to identify the problem, rather than just demanding to know why it’s not working,” she explained.

The priority is to improve the user experience; the economic gains will follow naturally. —Prabhakar Raghavan

Raghavan believes that to be successful in research, science or in a job, one must always ask the right questions. “In science, wrong questions lead to trivial work or unsolvable problems. Similarly, in a business job, not asking the right questions results in irrelevant or fruitless work,” he explained.

The overall vision of Google, with its range of tools such as core models, LLM, SLM, search engines, ad model, assistants, commerce and payments, “is to make user journeys more efficient,” Raghavan added. For example, planning a vacation involves coordinating flights, accommodation and activities.

“Current language models can help, but they often miss nuances, such as suggesting visits to the Louvre on a closed day. As these models improve, even a 20% increase in user efficiency represents a significant economic opportunity. The priority is to improve the user experience; the economic gains will follow naturally,” he concluded.

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