Last update: Dec 7, 2024
Reading time:
3 Minutes
Search has owned the internet for over two decades—more specifically, Google has owned the internet. Over 98% of all web searches originate from Google and Google platforms.
The rise of AI models like ChatGPT and Bard has increased concerns about the future of Google Search.
Most specifically around the businesses that currently rely on Google Search for a significant portion of their business.
Google CEO, Sundar Pichai spoke recently in an interview on where things are headed for 2025.
Watch the interview here: Watch Now
It’s no secret that every major tech company is investing in AI to stay ahead of the competitive bell curve.
So far however, Google has had minimal success with their own AI models compared to the success of OpenAI’s ChatGPT and even Meta’s LLaMA 3 model.
Catching up and ultimately winning this AI race is the most urgent priority in Google’s plans for 2025. The shake-up of traditional search is the single biggest threat to their business.
Just this year Google rolled out Search Generative Experience (SGE) which adds AI results to the top of many searches you may complete on a regular basis.
This feature was widely well received and we can expect to see a lot more AI features and functionality coming out as early as Q1 2025.
Pichai cited that many of the easiest breakthroughs have already been made. That further innovation in 2025 would be more challenging for the company than some of the previous iterations.
With the focus being more so on technical breakthroughs impacting back-end systems what I’m hoping to see is dramatic iterative improvements to the Google Search algorithm to improve overall ranking factors.
This could lead to a shakeup in current rankings as algorithm changes often do.
However, algorithm changes almost always result in good companies, publishing good work, and getting featured at the top more often.
(If you’re a 2POINT client you can breathe a sigh of relief)
Additionally, to organic search, I’m optimistic about changes to the Google Advertising Auction system.
As of now, the system is very straightforward but as a result can be hard to customize or even automate specific advertising criteria.
Budgets are liable to see big swings in performance based on the auction competitiveness and there are only a few rudimentary safeguards for control.
AI implementation and machine learning could dramatically improve the ability to automate certain aspects of advertising.
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