In the world of technology, terms like artificial intelligence (AI), machine learning (ML), and algorithms are often used interchangeably, but they refer to distinct concepts. Understanding the differences between them is helpful, especially for those in digital marketing and SEO, as these technologies are reshaping how search engines operate and how brands are found or not found online. Here’s a breakdown of each concept and an overview of their impacts on SEO.

What is Artificial Intelligence?

Artificial Intelligence (AI) is a broad field of computer science focused on creating systems capable of performing tasks that typically require human intelligence. These tasks include problem-solving, understanding natural language, recognizing patterns, and making decisions. AI is the overarching umbrella under which both machine learning and algorithms fall.

Types of AI:

1. Weak AI (Narrow AI): designed for specific tasks (e.g., Siri, chatbots).

2. Strong AI (General AI): hypothetical AI that possesses general cognitive abilities akin to humans.

3. Superintelligent AI: a level of AI that surpasses human intelligence (still theoretical).

Impact on SEO:

AI is revolutionizing SEO by enabling search engines to understand content more deeply, personalize search results, and improve the overall user experience. AI-driven algorithms, like Google’s RankBrain, analyze user behavior and adjust search results accordingly, making SEO more focused on user intent and content relevance. 

What this means is that when we ask ChatGPT a question, the answer we get is more like what a smart human who is a subject matter expert would say.  However, there are documented examples of where ChatGPT and other AIs will literary make up facts. So as users, we have to beware and double check key info before making decisions based on answers from Chatbots.

What is Machine Learning?

Machine Learning (ML) is a subset of AI that involves training algorithms to learn from data and improve over time without being explicitly programmed. ML algorithms identify patterns within data, make predictions, and can even refine their processes as more data becomes available.

Types of Machine Learning:

1. Supervised Learning: The algorithm learns from labeled data.

2. Unsupervised Learning: The algorithm identifies patterns in unlabeled data.

3. Reinforcement Learning: The algorithm learns by receiving rewards or penalties for actions taken in a dynamic environment.

Impact on SEO:

Machine learning is at the core of modern SEO tools and strategies. Search engines use ML to continuously improve how they rank pages, understand search queries, and combat spam. For instance, Google’s BERT algorithm uses ML to better understand the nuances of natural language, improving its ability to deliver relevant search results.

What are Algorithms?

Algorithms are step-by-step procedures or formulas for solving problems. In computing, they are sets of rules that a computer follows to perform specific tasks. Algorithms can be simple, like sorting numbers in an array, or complex, like Google’s search algorithm, which processes billions of web pages to determine the most relevant results for a query.

Types of Algorithms:

1. Search Algorithms: Used by search engines to find relevant web pages.

2. Sorting Algorithms: Organize data in a particular order (e.g., quicksort, mergesort).

3. Recommendation Algorithms: Suggest content to users based on their behavior (e.g., Netflix recommendations).

Impact on SEO:

Algorithms are the backbone of how search engines rank content. Google’s algorithm, for example, uses over 200 factors to determine how pages should be ranked. As these algorithms evolve with AI and machine learning, SEO strategies must adapt to stay effective. Understanding algorithm updates and how they impact rankings is crucial for maintaining or improving search visibility.

The Intersection of AI, ML, and Algorithms in SEO

In the context of SEO, AI, ML, and algorithms work together to create a more sophisticated and user-centric search experience. Here’s how they intersect:

• AI provides the overarching framework, allowing for the development of smarter and more intuitive search engines.

• ML enables search engines to learn from user data, refining algorithms and improving the accuracy of search results.

• Algorithms execute the processes that determine how content is ranked, using insights gained from AI and ML.

Together, these technologies are pushing SEO towards a future where Google understands user intent more and more, and therefore, can deliver the most relevant info to a user’s question, but still not in the conversational way that ChatGPT can.

From the digital marketer’s point of view this means, creating high-quality content and staying up-to-date with algorithm changes are more important than ever.  The other major bonus of creating high-quality, authoritative content is that it is more likely to be referenced by ChatGPT and other chatbots and AI tools.

Conclusion

Artificial intelligence, machine learning, and algorithms are key components driving the evolution of SEO. While AI provides the intelligence, machine learning offers the learning capability, and algorithms serve as the practical tools to execute these advancements. For businesses and digital marketers, staying informed about these technologies and understanding their impact on search engine rankings is essential for success in the digital landscape. As AI continues to grow, so too will the complexity and importance of SEO strategies that can adapt to these changes.

Tanjo Digital is a Toronto-based SEO and Digital Marketing agency who specialized in following data to insight. Got a question? We’d love to hear from you.