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Since ChatGPT launched in November 2022, AI has become as ubiquitous in marketing and SEO as bacon and eggs are for breakfast.
While the last two years saw a lot of people going a bit wild with AI tools—cranking out content non-stop and calling themselves pros at tools barely out of beta—this year will see people become smarter at how they utilize Generative AI (GenAI) tools.
Thanks to the kind of smarts you can gain only with actual experience, we now know where AI really works for us—and where it’s just hype. We also have a clearer idea of how to systematically integrate AI into the mix while keeping the campaign goals at the forefront.
So what does this year hold for AI trends in marketing and SEO? We asked subject matter experts what they think. Keep reading to find out.
1. Less Quantity, More Quality
There was a time when publishing more content actually gave you a better probability of being seen online or ranking for keywords in the SERPs. With AI tools making it easier than ever to create a large volume of content, quantity is no longer a flex.
“More content, more promotion, more touchpoints — it’s a lot of noise, and “more” isn’t helping anyone stand out,” notes Miranda Miller, the author of multiple AI Content marketing books.
With attention spans being so short and content being mass-produced like never before, she predicts that marketing that stands out will have to be brutally direct and concise.
“This is a major shift for a lot of people, but clarity and conciseness are core qualities of solid writing. No one cares what you want to say; you need to understand what they want to hear. That doesn’t change in an AI-fuelled world. If anything, it’s amplified, so you need a solid editorial process more than ever to ensure your messaging is going to hit the mark”.
Her idea is also echoed by Google itself, which has released multiple spam updates to tackle the evergrowing amount of AI content it has to now crawl and index.
So how do you please both search engines and humans in 2025 amidst such chaos?
Reuben Yau, our VP of SEO at Vizion, who spends countless hours experimenting with AI, shares some timeless advice that works here:
“While AI technologies are fun and provide new opportunities, the core tenant of creating authentic, original, and expert content that resonates with users will always be important. We’re ultimately creating content for prospects, customers and people. The technologies that consume our content are merely pathways to showcase it in front of people.”
2. SGE Will Change How We Approach SEO (Possibly Forever)
Search Generative Experience (or SGE) is Google’s AI overview feature that gives quick, conversational answers by combining information from different sources. It appears above other results in the SERPs and acts like a “SERP within the SERP.”
There is a consensus among most SEO circles that this will inevitably lead to a loss of SERP clicks and website visits. So what happens next?
According to Yau, SGE doesn’t mark the end of SEO; it merely demands that we reframe the approaches that have dominated traditional SEO. For instance, the focus will now shift to understanding how users interact with AI snippets in the SERPs rather than how many keywords you rank for.
He also thinks that SGE also serves Google’s original mission “to organize the world’s information and make it universally accessible and useful”.
“It’s a new step towards a different way that people can get access to not just information, but insights, summaries, examples, and other related content. It reminds me a lot of what WolramAlpha tried to accomplish in 2009 but couldn’t”, he adds.
Since SERPs generate significant revenue for Google through ads, it’s also unlikely that completely dismantling SERPs would align with Google’s financial motives. There’s a likelihood that SGE will cater to most (or all) informative queries. However, commercial searches and some expert-backed original content (like case studies or blog posts with unique angles) will probably continue to be shown as organic search results.
The idea is to stop lamenting over changes you can’t control but adapt SEO strategies to focus on content visibility within SGE.
“Brands should continue to invest in content based on Google’s EEAT framework and generate more evergreen pieces to fuel the Large Language Models (LLMs) like Gemini. In return, they will get rewarded with links from within the SGE”, Yau advises.
3. AI Will Make Data Analysis Easier Than Ever Before
While some people are still primarily using GenAI to create content or summarize text, Reuben Yau believes that the use of AI in data analysis will gain popularity this year.
He uses it as a second pair of eyes on his data to pick up on things he may have missed — allowing him to do more high-level tasks, without involving a second human being.
“My prediction is that large marketing and marketing automation platforms will integrate AI technologies into their stacks to deliver better insights. We have already seen that AI is great at sifting through vast amounts of data and uncovering anomalies in data. When this is built into the systems from the get-go, it will prove to be a game-changer”, he added, while giving a hat tip to Google Analytics for providing a widely recognized example of this.
Google Analytics is already showing Analytics Intelligence insights to help users identify changes in traffic, conversions, and more easily.
Unique AI tools designed solely for data analysis have also arrived on the scene, such as Tableau. These will also shape how marketers utilize data.
On an individual level too, AI is likely to enable faster analysis of smaller data sets and the generation of scripts and content to semi-automate many tedious tasks. This trend is already emerging and is likely to gain more traction as AI advancements continue, making these tools more accessible and powerful for marketers.
Reuben shares a unique way in which he utilized AI’s data analysis capabilities:
“I used ChatGPT to generate the latitude and longitude coordinates for several businesses, then plot them on an interactive map.
Then I had it calculate the distances between each location to find the ones closest to one another. In less than an hour, I was able to generate client-ready materials with insights and an interactive visual map by just writing a few prompts and providing a CSV file of addresses.”
He recommends other marketers to try different LLMs for different tasks as they all possess unique capabilities.
For instance, he prefers using Claude to analyze keyword patterns and grouping sets of keywords into semantic themes. On the other hand, he uses ChatGPT to create Python scripts to manipulate data and reformat content.
4. Human-AI Collaboration is the Future of Success
As of Nov 2022, 14% of workers claimed they had already lost jobs to AI. There were real concerns that AI would take over content creation processes entirely and there will soon be no room for more than a small fraction of marketers to have a place in it. And the frenzy that ensued after did point to it, with many content marketing departments being laid off and replaced by AI that year.
Come 2025, the mania has died, and balance has returned to the conversation. After separating the wheat from the chaff, we realize that while AI is good at some things, it is seriously lacking in others. For instance, AI tools are great at creating filler content for “What is” type of questions but are notoriously famous for being unreliable at research and fact-checking.
The consensus today is that human-led marketing that utilizes AI as a mere tool in the process is the way to go.
But how do you go about it the right way?
Kevin Meng, an AI consultant for SEO agencies and brands, and the creator of a course on AI content editing, shares his approach to integrating AI into content creation.
His approach involves using AI to generate the majority of the content, while using human editors to enrich it with unique anecdotes, data, and testimonials to add authenticity and originality.
He has now trained a custom GPT to write in his brand voice by feeding it his own content as a frame of reference. Now the GPT also adds unique information, personal anecdotes, or customer testimonials to make his AI content sound human.
This approach has also worked well for him, reducing his weekly workload of writing 5000+ words to a single day.
“I worked with one client who was getting 0 clicks across all of his articles after creating them with AI. The reason was that all of his articles sounded like a robot and not a real brand. After using AI to fix his tone of voice, add unique value, and include pain points the reader was experiencing, clicks went through the roof to 10,000+”, he adds.
5. Marketing Teams Will Need to Prove Where AI is Truly Effective
There has been an incessant push from executives in almost every tech and marketing company to get departments to use AI since 2022. Many creatives found themselves in a place where they were using AI for the sake of it — even if it ended up taking up more time to clean up the output for publishing than creating it from scratch.
This brings up the quote from Jurassic Park, “They were so busy proving they could, but forgot to ask themselves if they should”.
This year, it’s likely to change.
After two years of testing, many companies have realized that while AI can support various stages of the writing process—such as analyzing user data, building personas, offering copy variations, and creating summaries for different channels—AI-driven content still requires a strong human editorial and marketing process to avoid adding to the noise.
Miranda Miller, whose content studio had to process 30+ blog and white paper submissions monthly in 2022, quickly learned this lesson after using Chatgpt regularly for six months.
She found that it was great to do an initial proof of ESL (English as a second language) content to get it to a state where the human editor can focus on the technical details and finer points of writing. Her team also found it useful for producing title variations, reformatting such as converting paragraph text into bullet lists, writing synopses, fine-tuning tone of voice, ensuring adherence to brand guidelines, and other use cases like that.
“But you cannot trust it for anything to do with research, validating, information, etc. I’ve often caught AI making things up or inserting statistics that don’t exist. It wants to be helpful and give you an answer even if it’s not the right one”, she added.
Publishing content riddled with issues like that without human editing can risk your brand’s reputation.
“At the enterprise scale, this means marketing teams need to be experts in how this technology works, and truly understand its strengths and limitations. You can waste a lot of time and create risk to the brand by relying on AI in the wrong places,” she advises.
Ultimately, every brand needs to evaluate how AI fits into their proprietary marketing processes — and see where they make sense and where they do not.
Conclusion
This year will see people becoming better at creating systems to use AI effectively in ways that produce results and save time. These changes will be fueled by advances in SGE, new GenAI, changes in Google algorithms, and more.
Adopting a “we will evolve with these changes” approach rather than a “gloom or doom” one is the best way to approach the new future of AI-led marketing.