The Role of Artificial Intelligence in Google Search
Are you frustrated with your SEO efforts not delivering the results you expect? It may be time to reconsider your strategy. Traditional SEO tactics are becoming less effective as Google’s AI continues to evolve rapidly. Understanding how Google’s AI systems work is crucial for adapting your SEO approach and improving your chances of ranking higher in search results.
Google has been using AI to identify, weigh, and order URLs since around 2015, starting with its first AI system called RankBrain. This system helped the search engine understand how words relate to concepts. For example, if you search for “What’s the color of the sky?” RankBrain could understand that “sky” is a concept with a perceived color and provide relevant results even if the exact words aren’t used.
In 2018, Google introduced neural matching, a system/sub-system that helps understand how queries relate to pages. This system enables Google to understand ambiguous queries and provide more accurate results. For instance, if you search for “tie my laces,” neural matching can determine that “laces” refers to shoe laces and show you results on how to tie them.
BERT, which stands for Bidirectional Encoder Representations from Transformers, was a breakthrough development in 2019. BERT builds upon the capabilities of RankBrain and neural matching, enabling Google to understand how multiple words in a sentence relate to multiple words on a page and the concepts behind them. BERT is particularly important for entity recognition, helping Google understand brand names, people, and their expertise in specific topics.
In 2021, Google introduced the Multitask Unified Model (MUM), which claims to be 1,000 times more powerful than BERT. MUM can generate language and understand both text and images, allowing for more advanced search capabilities. For example, MUM can provide insights on hiking Mt. Fuji by understanding the concept of comparing mountains, relevant information like elevation and trail details, and even context-specific information such as the rainy season on Mt. Fuji.
These advancements in Google’s AI systems have significant implications for SEO. It’s essential to understand that what you can do with generative AI, Google can do with the AI in their ranking system. Google’s AI can vet sources and evaluate the quality and relevance of webpages to better match user intent. Additionally, AI-driven search is focused on providing a more holistic user experience, moving from simple answers to comprehensive journeys. This means Google can track user engagement with content and analyze how it relates to brands and internal experts.
To harness the power of AI for SEO, it’s important to shift your focus from traditional ranking signals to understanding how humans search for information and why. Creating content that aligns with Google’s AI-driven approach and addresses user intent is crucial for improving your search rankings.
In conclusion, Google’s AI systems, such as RankBrain, neural matching, BERT, and MUM, are reshaping search by enabling more accurate and context-aware results. Adapting your SEO strategy to align with these advancements is key to improving your chances of ranking higher in search results. By understanding how Google’s AI works and creating content that matches user intent, you can stay ahead in the ever-evolving world of SEO.
