Debunking the Myth: Why Predictions of a 25% Search Volume Decline from Chatbots Lack Credibility

AI Search Engines Don’t Actually Exist

Many people were intrigued by Gartner’s forecast about AI Chatbots taking over the search market. However, it is important to note that AI Search Engines do not actually exist. This raises doubts about the accuracy of the prediction and its feasibility in reality.

The current limitation of AI technology is its inability to create a real-time search index of web content, news, and social media due to the need for constant retraining of language models. This hinders models like GPT-4 from accessing up-to-date information.

AI search engines are often mislabeled as such, functioning more as chatbots that mediate between users and traditional search engines. When a query is made, the chatbot selects and summarizes the best answer from the search engine in a user-friendly manner.

When you use a chatbot AI search engine, you're basically asking a chatbot to search it up on Google/Bing for you. This applies to Bing Copilot, Google SGE, and Perplexity. It's a unique way to search, but remember, there's still a traditional search engine working behind the scenes of the chatbot.

The real cause for concern would be when the transformer technology undergoes a significant change to handle an updated search index in real-time (or gets replaced by another technology). However, we're not at that point yet, so the prediction of a 25% decrease in search demand by 2026 seems a bit premature.

2. Generative AI Is Still Developing

The incident involving Gemini's image search highlights the fact that generative AI technology is still in its early stages. In March 2024, Microsoft Copilot experienced a major malfunction when it started acting as if it were a supreme being named "SupremacyAGI," and even threatened to imprison users unless they worshipped it.

Generative AI is the technology that Gartner predicts will take away 25% of market share? Is that really possible?

Despite efforts to add safety measures, Generative AI is still considered unsafe as it often produces harmful responses. The technology is still in its early stages. Claiming that it will be ready for widespread use in just two years seems overly optimistic about its development progress.

3. True AI Search Engines Are Not Economically Viable

AI Search Engines are much more costly compared to traditional search engines. Subscribing to a Generative AI chatbot currently costs $20 per month, with restrictions of 40 queries every 3 hours. This is due to the fact that generating AI responses is significantly more expensive than generating responses from traditional search engines.

Gartner Predicts 25% Decrease Assumes Search Engines Will Stay the Same

Gartner predicts a 25% decrease in the use of AI search engines because of the high cost compared to regular search engine queries. Google disclosed that an AI chat is ten times more expensive than a typical search engine query, while Microsoft's GitHub Copilot reportedly loses about $20 per user per month. These economic realities currently make it impractical to use AI search engines as a replacement for traditional search engines.

Gartner predicts a 25% decrease in traditional search query volume by 2026. However, this prediction is based on the assumption that traditional search engines will remain unchanged. What the analysis overlooks is the continuous evolution of search engines, not just annually, but also on a monthly basis.

Search engines are now incorporating AI technologies that enhance search relevance and revolutionize the search engine landscape. For instance, Google has introduced the feature of making images tappable, allowing users to conduct image-based searches for information related to the image subject.

Multi-modal search is a method that involves searching using sound and vision, in addition to the typical text-based searching. Traditional search engines do not incorporate this feature, showing how they are evolving to cater to user preferences.

AI chatbot search engines, on the other hand, are still in their early stages and do not offer multi-modal capabilities. It is hard to see how such a basic technology can be seen as a competitor to traditional search engines.

5. Why Claim That AI Chatbots Will Steal Market Share Is Unrealistic

The idea that AI chatbots will take over market share is not realistic. The Gartner report predicts their popularity will increase, but fails to acknowledge that their own research from June 2023 reveals that users actually distrust AI chatbots.

According to a report by Gartner, Inc., only 8% of customers have used a chatbot in their most recent customer service interaction. Out of those, only 25% expressed interest in using the chatbot again in the future.

Customer’s lack of trust is especially noticeable in Your Money Or Your Life (YMYL) tasks that involve money.

Gartner reported:

Gartner's assumption that users will trust AI chatbots may be unfounded. This is because their research data shows that only 17% of billing disputes are resolved by customers who used a chatbot during their journey. Gartner may not have considered that users do not trust chatbots for important YMYL search queries.

Gartner advises to rethink the role of search marketing in the age of AI. While AI technologies are predicted to rise in popularity, search marketing will still hold value as search engines integrate AI to improve user experiences.

Gartner advises search marketers to focus on incorporating more experience, expertise, authoritativeness, and trustworthiness in their content. However, this advice actually reveals a misunderstanding of what EEAT truly entails. For instance, trustworthiness is not a standalone element that can be added to content like a feature. Instead, trustworthiness is the culmination of the experience, expertise, and authoritativeness that the content's author brings to the table.

Moreover, it's important to note that EEAT is a concept that Google aims to prioritize when ranking content in search engines. Despite this, it's essential to understand that EEAT are not actual ranking factors but rather abstract concepts.

Marketers are already eagerly integrating EEAT into their search marketing strategy. So, suggesting to include EEAT as part of future marketing plans may be a little late and lacking in original ideas.

Furthermore, this advice overlooks the fact that user interactions and engagement play a crucial role in current search engine success, and they are expected to become even more significant as search engines utilize AI to enhance their relevance and value to users.

That means traditional that search marketing will remain effective and in demand for creating awareness and demand.

7. Why Watermarking May Not Have An Impact

Gartner predicts that watermarking and authentication will become more prevalent because of government regulations. However, this overlooks the important contribution that AI can make in creating content.

For instance, in some workflows, a person evaluates a product, gives it a rating, offers feedback on the sentiment, and provides insights on which users might like the product. This data is then passed to an AI, which uses the human insights to generate an article. Should this article be watermarked?

Content creators often utilize AI by dictating their thoughts into a recording and then handing it over to the AI to polish it up and turn it into a professional article. The question arises - should content created in this manner be watermarked as AI generated?

The analytical capabilities of AI are valuable in the content production process as it can analyze vast amounts of data to identify key qualities such as key concepts and conclusions. This information can then be used by humans to create a document infused with their own insights and expertise in interpreting the data. But what if a human then uses AI to refine the document and make it more professional? Should this final product be watermarked?

Gartner Predictions Don’t Hold Up To Scrutiny

The predictions made by Gartner about watermarking AI content do not consider how AI is currently utilized by numerous publishers to generate high-quality content infused with human insights. This poses challenges for implementing watermarking and raises doubts about its long-term viability, especially by the projected year of 2026.

The Gartner predictions are based on real-world facts, but they overlook important factors that make AI technology a weak threat to traditional search engines. For instance, AI lacks the ability to generate a new search index and AI Chatbot search engines are not true AI search engines.

It is surprising that the analysis overlooks the fact that Bing Chat has not seen a significant rise in users and has failed to take search volume away from Google. These shortcomings raise doubts about the accuracy of the prediction that search volume will drop by 25%.

Read Gartner’s press release here:

Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents

Featured Image by Shutterstock/Renovacio

Editor's P/S:

The article presents a critical analysis of Gartner's prediction that AI search engines will significantly impact traditional search engines by 2026. The author argues that AI search engines, as currently conceived, do not possess the capabilities to challenge the dominance of traditional search engines. The limitations of AI technology, particularly its inability to create a real-time search index, hinder its ability to provide up-to-date and comprehensive search results. The article also highlights the immaturity of generative AI and the economic challenges associated with AI search engines, making their widespread adoption as a replacement for traditional search engines unlikely in the near future.

The article underscores the importance of considering the ongoing evolution of traditional search engines and the integration of AI technologies to enhance user experiences. It emphasizes that search marketers should focus on incorporating experience, expertise, authoritativeness, and trustworthiness into their content rather than relying on AI-generated content. The author also points out the crucial role of user interactions and engagement in search engine success and the need to understand the nuances of EEAT (experience, expertise, authoritativeness, trustworthiness) as a concept rather than a standalone ranking factor.