Will Perplexity’s new AI-driven ad model disrupt Google’s dominance?

As the digital advertising landscape undergoes a seismic shift, a new challenger has emerged to shake up the status quo. Will Perplexity’s new AI-driven ad model disrupt Google’s dominance, offering brands a fresh alternative that promises greater efficiency, precision, and ROI?

Experts in the field are taking notice.

Manish Solanki, COO and Co-Founder, TheSmallBigIdea

“This proactive approach anticipates user needs and presents ads at the most opportune moments. For brands, this eliminates much of the guesswork, aligning ads with user intent in real time. This dynamic, personalized approach is likely to drive higher engagement. Additionally, the efficiency of AI optimizing campaigns without over-reliance on past data could make it a more cost-effective option, ultimately attracting brands that are keen on real-time, personalized advertising,” adds Solanki. 

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Exclusive: Will Perplexity’s new Ad model shake up digital advertising?

Parul Bhargava, Co-Founder & CEO, vCommission

With a vision for the future, Perplexity plans to introduce ‘sponsored questions’ – allowing brands to bid on specific queries relevant to their offerings. “From what I hear, Perplexity plans to introduce ‘sponsored questions’, where brands can bid on specific queries relevant to their products or services. In this way, they will be able to place sponsored content/ads directly in the answers seamlessly, contrary to Google ads where sponsored ads are listed separately,” says Parul Bhargava, Co-Founder & CEO, vCommission.

Shan Jain, Independent Director, Brand Strategist and Marketing Transformation Advisor

Shan Jain, Independent Director, Brand Strategist and Marketing Transformation Advisor, succinctly encapsulates the scenario: “Perplexity Vs Google: The Goliath and David Showdown. In the ad world, Google is the Goliath – massive, powerful, and everywhere. Perplexity, the David of this battle, may not have the scale, but with AI-driven precision and a privacy-conscious sling, it’s aiming right at Google’s data-reliant forehead.”

According to her, Perplexity’s AI model challenges Google by offering contextual, non-invasive advertising versus Google’s data-driven, keyword-focused ads. Brands might prefer Perplexity's real-time adaptability and its ability to create a more tailored experience without the need for massive data collection. It also addresses rising concerns about privacy – an issue where Google has faced scrutiny.

“Just as an example, let’s say a user is reading an article about the benefits of eco-friendly living. Google would serve an ad based on user’s previous searches and browsing history (for example, “best organic cleaning products” or “electric cars”), and therefore the ad served would be for a specific brand of eco-friendly cleaning products. The ad is highly targeted based on past behaviour but feels somewhat intrusive as it shows products the user had already searched for or viewed,” she explains.

“Perplexity’s Ad for a user reading the same article about eco-friendly living would interpret the context and generate an ad for an innovative sustainable home energy solution that matches the theme of eco-friendliness, but wasn’t directly searched for by the user. The ad feels contextually relevant without giving the impression of being tracked based on previous actions. For example, “Power Your Home with the Sun—Discover ABC Solar Panels. Easy installation, sustainable savings.” In summary, when ads start listening better than they’re watching, they’ll stop being noise and become music to the consumer’s ears,” says Jain.

Benefits and drawbacks

What are the potential benefits and drawbacks for users of this new ad format? Could it lead to a more personalised and informative online experience?

Shan Jain explains it with examples: “On the benefits side, users may experience a more personalized and relevant ad experience without the sense of being tracked. Imagine a user is reading an article about fitness and healthy living. Perplexity ads displayed could be for relevant fitness products or healthy meal delivery services – without needing to track their browsing history or previous searches,” Jain says. 

However, she adds, the drawbacks could include a potential overload of AI-generated content that may feel monotonous or lack the creative spark of human intervention. Since AI might focus on efficiency over creativity, ads could feel robotic or monotonous over time. Example: “Buy X for Y benefits” or “Save on Z with our latest offer.” 

“Additionally, users might have concerns about AI’s accuracy in understanding intent, especially if ads are placed based on misunderstood content. For example, if a user is reading an article on "how to reduce stress at work," the AI might serve an ad for an expensive office chair, thinking it's relevant. But the user might be more interested in mindfulness apps or wellness programs, not physical products. The irony is, while AI learns to read our minds, it might just forget to understand our hearts,” she says.

According to Manish Solanki, the primary benefit for users is enhanced personalization. “With AI predicting user needs, ads become less intrusive and more relevant, almost like a digital assistant anticipating what they want. This can significantly improve the online experience by reducing irrelevant or disruptive ads. However, the drawback lies in privacy concerns. When ads become too personalized, users may feel like their data is being overly scrutinized, which could lead to discomfort. Balancing the line between helpful personalization and data privacy will be critical to ensuring user trust.”

Parul Bhargava points out that Perplexity’s ad format offers personalized, relevant ads embedded into AI responses, making them less intrusive and potentially more informative than traditional ads. However, she adds, it could introduce bias, as paid content may influence responses, and blending ads with organic content might affect user trust.  

Ethical concerns

With AI-generated content playing a central role, it is imperative to consider ethical concerns regarding the accuracy, bias, and potential misuse of this technology in advertising.

“Oh many! Among all the good things we’re talking about Perplexity’s AI-driven ad model versus Google, this one is particularly to be looked out for. There could be loop holes around the accuracy, biasness, potential misuse, etc.,” says Parul Bhargava.

• Accuracy: AI-generated content might not always be accurate
• Bias: AI models may intentionally/unintentionally favour certain brands or perspectives based on the data used to train them
• Potential misuse: The ability to subtly blend ads into AI responses raises concerns about transparency.

Manish Solanki reckons that ethics is a key consideration in AI-driven advertising. According to him, AI models are only as good as the data they learn from, and if that data is biased, it can lead to skewed ad targeting and misrepresentation. This can have serious consequences, including reinforcing stereotypes or spreading misinformation, if not monitored carefully.

“Privacy is another significant concern; brands must ensure that they handle user data responsibly and transparently. To truly thrive, AI-driven advertising must prioritize ethical safeguards, ensuring that accuracy and bias are carefully managed while protecting user data,” says Solanki.

Shan Jain states that there definitely would be ethical concerns of bias and the possibility of manipulation, as is there with any AI model, presenting information in ways that exploit users’ vulnerabilities or reinforce stereotypes.

She further points out that an AI trained on historical data might disproportionately target certain groups with financial products based on past behaviour patterns, unintentionally reinforcing socioeconomic divides. “Furthermore, the question of transparency arises. How much do users know about why a certain ad is being shown to them? If you can’t tell whether it’s an algorithm or a person selling you dreams, maybe the real question is: who’s controlling the narrative?”

Can we expect more Perplexity-like models?

In the days ahead one can witness the transformative effects of AI in the advertising industry, with a slew of innovative applications and models playing a significant role. So the question is: Can we expect more Perplexity-like models in future?

Shan Jain feels that AI in advertising is just beginning to tap into its potential. Beyond Perplexity, she adds, we’re likely to see more predictive models, capable of pre-empting customer needs before users even voice them. According to her, AI could also drive immersive experiences – think AI-powered VR and AR ads, where users can engage with products in a simulated environment before making purchasing decisions.

“However, the success of these models will depend on balancing automation with creativity. With AI, the future of advertising won’t be about who screams the loudest but about who whispers the right message at the right moment,” she concludes.

Manish Solanki reckons that AI’s potential in advertising is just beginning to unfold. According to him, beyond targeting and optimization, we’ll likely see AI play a larger role in creative processes, designing personalized ad campaigns, and crafting immersive experiences in real time. This, he adds, will lead us to more Interactive ads that evolve based on how users engage with them; this is where AI can take advertising.

“We can also expect more players like Perplexity to explore similar models, as brands increasingly look for ways to enhance efficiency and create deeper, more meaningful connections with consumers,” he adds.

According to Parul Bhargava, advertising industry has a lot to adapt with AI, beyond just content: Automation of repetitive tasks, improved audience targeting, real-time ad optimization, ad fraud detection, etc.

Also Read: Exclusive: Will Perplexity’s new Ad model shake up digital advertising?