The Evolution Of Transformative Search Engine Experiences

It's not entirely clear how generative artificial intelligence (AI) technology will help search engine optimization (SEO) professionals with campaigns. But one thing is certain: Google on Friday announced its AI model Bard is being launched in more than 20 programming languages including C++, Go, Java, Javascript, Python and Typescript to help with programming and software development tasks, including code generation, debugging and code explanation. 

There has been a never-ending flow of news and information associated with generative AI since OpenAI launched its chatbot technology late last year. To determine how this technology will affect and influence SEO professionals, I caught up with Jim Yu of BrightEdge, which has been integrating traditional AI into its platform for more than 12 years.

We spoke about the technology’s traction in search engine marketing and how humans -- not just the technology -- will become crucial to the success of search and content marketing.



BrightEdge AI-led products such as Autopilot and SearchIQ will evolve, Yu said, adding that the company will release more capabilities in the coming months.

While AI integrated into search is not new, “the growth of conversational search and generative AI is new,” says Yu. “As big search players such as Bing and Google integrate chat and conversational-based technology into their engines, we will see an evolutionary change in search engine experiences in terms of how they look and how consumers extract information.”

The Evolution Of Search-Engine Experiences

Interest in AI continues to grow -- mainly because, for the first time, it has allowed people to interact and use an interface directly. There are two significant differences to be aware of when talking about generative AI, says Yu. He explains it like this:

1. Stand-alone generative AI applications. These have been created via Open AI’s chat revolution. This has led to a flood in the market of conversational-based AI tools focusing on specific and niche tasks such as content creation, editing and copy, customer service bots, visual imagery creation, and much more.

2. Integrated generative AI in search engines: This is where search engines themselves integrate conversational and generative AI into their platforms directly.

For example, Bing relies on ChatGPT-4 and has incorporated it into its search engine first, which prompted a lot of interest in Bing.

On the other hand, Google’s Bard is based on its own Language Model for Dialogue Applications (LaMDA) technology. While both offer different experiences and result types, it is clear that the former has driven the latter as search engines add more tailored and diverse experiences than ever before.

What It Means For SEO And Content Marketers

Earlier this month, Google announced that it would be integrating more AI into its search engine directly, and last week alluded to the integration of the technology into its advertising platforms. By using large language models (LLMs), which can simulate human responses to questions, it aims to enhance user experiences.

Yu said marketers could expect Google to integrate automated search phrases into the Bard chatbot, add command-based interfaces in its search engine, and launch new user interfaces with traditional and conversational search boxes.

Yu also believes that by working with Google’s latest announcement about Project Magi, it will introduce a new type of search engine to make search more conversational with more personalization. Google has 160 engineers working on Project Magi, according to The New York Times.

Some advice For SEO And Content Marketers

1. Be prepared: People will always visit websites, and the core fundamentals of SEO will be vital. Ensure that your site is optimized for conversational search queries and is technically sound with regard to Core Web Vitals such as page speed and structure. Focus on designing content with context to provide as many signals as possible to help generative AI models understand the context with schema. Follow Google’s E-E-A-T and Helpful Content best practices in terms of content.

2. Experiment with patience: It is a great time to experiment and test to understand where, how, and when to use conversational AI, but with AI-generated content be aware of its limitations and ensure human input and supervision are vital to any publication process. As AI develops, things change -- and while search engines adapt, be patient, as no one has all the answers right now.

3. Remain agile. Change is the main constant in search. Agile SEO professionals responsive to change gain a competitive advantage.

Generative AI Shortfalls

It may not see this way today, but Yu believes humans will become drivers of AI performance, and symbiosis will be crucial. This is because AI’s success -- particularly conversational AI -- depends on human input and supervision. Generative AI cannot replicate key human traits such as creativity, empathy, and experiences, he says.

Artificial Intelligence can interpret emotional expressions, but it cannot feel emotion, and falls short when it comes to forming real connections with consumers. A human must be behind that connection.

AI is often capable of complex problem-solving, but it can still lack the ability to interpret abstract concepts or apply logical reasoning. This lack of understanding can give incorrect responses leading to awkward situations and inaccurate conclusions.

According to Yu, In the future, humans will become AI managers and supervisors at the front and the end of processes.

From prompt experts to fact-checkers and editors who add the vital human element differentiating content and search experiences in and out of search engines.

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