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Safe to say that every person on our planet has used AI-powered tools at least once since their introduction. I mean, climate impact and ethical considerations aside, they are too convenient to neglect. So convenient it’s even rumored that Donald Trump used AI to calculate the tariffs imposed on other countries. And judging by the outcomes, the rumors are justified.
But let’s leave politics for another day. From a content perspective, it is clear that AI chatbots have done their deed and the content landscape looks very different now. And I, your friendly neighborhood editor, want to discuss how exactly things have changed, not only how we read, but search for content, and will also share some of my team's experience. And there’s no better way to start this conversation than talking about how people use chatbots for writing content.
Writing is fast with AI bots
Quick question: How much content is AI-generated these days? 57%, according to Amazon. This fact is not a wake-up call to abandon technology. However, it’s proof that writing can now be automated. How? Two words: custom bots.
Let’s compare two workflows, one before AI tools were introduced and one after.
How it used to be
If you wrote an article before the ChatGPT era, you know how hard it was. You brainstorm the idea, then turn this idea into an outline to later turn it into a draft. Then you edit the draft, and, if luck is on your side, finally get it approved and published.
And what about the time? Based on my team's experience and a Reddit thread, it took around 6-8 hours (note that we're talking about technical articles here).
Now, let's look at the same workflow once you add a chatbot.
How things look now
Two years ago, I wrote an article on how to teach ChatGPT to become your personal writing assistant. Today, you can go beyond that and create a whole custom bot to help you write an article. An on-point example would be a chatbot our team created for one of our clients, VeePN.
Here's a story behind it.
VeePN wanted to speed up writers’ work without burning them out. As we developed their content strategy, we knew what content clusters were best suited for AI writing.
Using these clusters, we created a custom chatbot that allows you to write an article faster and without draining too much mental power.
As for the process, such things as preparing an outline or even writing a draft can now be done two times faster (2-4 hours vs 8 hours, according to the VeePN team) with the writer talking to the chatbot and making improvements where needed.
And in case writers could use some extra help, we wrote a guide on how to write with ChatGPT.
Now, would I recommend fully delegating content writing to chatbots? Hell no. Sure, automation is the best part of anything, but content-wise, my team and I wouldn't suggest using chatbots for anything more than speeding up the writing process. You can use bots for writing, but the result will be very surface-level and boring. And some more bad news, people might no longer read AI-generated slop like that.
People no longer need plain content without human insights
Content became much simpler to produce, but the expectations from it went much higher than before. I mean, AI assistants were taught on the whole Internet and are extremely flexible, so if you provide the same level of detail in your article as, say, Gemini, then what's the point? Let's compare how things used to be to how things look now for better clarity.
How it used to be
Before the AI takeover, people used to Google the information, both basic and highly specific. Blog posts and articles were a popular stop in this regard, and the answers to users’ queries were coming from them. The most AI thing was Siri, and her answers were, well, useless.
How things look now
I'll start with some tough love, sorry. According to an MIT study, people now prefer ChatGPT when it comes to delivering basic info over humans. We talked about the reasons a bit above: you just can't outperform something designed to answer every question in every form possible. But this doesn’t apply to highly specific info, which brings us to the second piece of the puzzle.
Recently, Google brought a minor, but a very huge update, changing the length of their search bar. This small change means that the search queries are now encouraged to become lengthier, as people want to add more context to their search intent.
And speaking of Google, it doesn't seem to embrace AI-generated content. The company has always been doubling down on original content in their guidelines, but right now, it seems like the tides are shifting towards EEAT content even more.
To see if we are not the only ones thinking that way, I've reached out to Dana, a CMO at Eleken and my old-time friend. And she tends to agree with this point:
“Google penalizes texts with low originality as they don’t meet the EEAT criteria. AI-generated content is just like that, very generic; that’s why we add our own perspective on things along with our personal insights.”
Bohdana Yatsenko, CMO at Eleken
Here's our company’s case in this regard. Our client, Kultprosvet, reached out to us to write an article about outsourcing software development in Ukraine. While we learned about people's experience of outsourcing Ukrainian developers, we also know about the situation in Ukraine first-hand, a key thing foreign businesses want to learn about. So we brought our personal experience in the article and asked the company’s CEO to share his own insights, which added value to the narrative.
The article is now doing great, sitting firmly in the top-10 search results and bringing leads to our client. And the best part? No heavy investment was involved in the article’s promotion.
Personal stories and insights can be seen in case studies, discovered through interviews, but most importantly, these are things shared by someone real, a person who experienced it. Most of the time, people crave such knowledge, and AI will always lag behind here. But what’s curious is that artificial intelligence is looking for unique insights too.
SEO now has a relative named GEO
The rise of AI has not only affected how people consume information, but had its impact on search engines. And given that ChatGPT is used by 400 million people weekly, businesses want to be mentioned by it. Companies want to get noticed by AI chatbots, which has led to a new trend in the content industry, GEO, or generative engine optimization, and ways to treat your content.
How it used to be
Before uncle GEO showed up, content optimization looked as follows:
- SEO experts had to find the right keywords, contextually relevant to the topic and with good search volume.
- Writers had to add these keywords, making them a natural part of the text. They also had to take care of placing additional materials, such as visual elements, CTA banners, and such, to make the article easier to read and improve the SEO performance (yes, images do improve the SEO).
The primary goal was always the same: to reach the number one spot on search engines.
How things look now
GEO is a brand new thing in the content industry, but it's already everyone's dream to master it. Ahrefs claim that GEO is an SEO sub-branch, so its further development will highly depend on SEO practices. Based on their logic, if you want AIs to notice you, you have to increase your visibility in data sources used for RAG training (in other words, Google and Bing).
ChatGPT trains on data from Bing search results. It’s official.
While true to some extent, we have our own standpoint. Julia, our content strategist, has written an article about the differences between SEO and GEO. She pointed out that GEO goes further than matching keywords and static ranking. For AI, context is more important, so your piece should not just tick all the SEO boxes. As said before, AI wants to learn more, so it is looking for new info to enrich its database rather than endlessly sifting through well-optimized, but unoriginal content.
What both Ahrefs and we agree on is that if you want your business to be recognized by ChatGPT or any other AI chatbot, you need to focus on your brand authority. The more expert-backed content related to your domain you post, the better.
While there is no viable strategy on how to master GEO yet, we have plenty of examples to confirm the positive effect of human insights for grabbing AI tools' attention. Through our collaboration with Flyaps, for instance, our expert-backed articles got recognized by Perplexity and ChatGPT. And contrary to Ahrefs' advice, we didn’t put any SEO effort into this article.
1LIMS, a laboratory information management system provider, also managed to catch ChatGPT’s eye and attract leads thanks to an expert article our team wrote.
Finally, let’s talk about the content creation process as a whole.
Content creation is now in “Always-on” mode
Shane Perrish once said: “Ideas are cheap. Execution is expensive.” But with AI tools, the execution has become really cheap. Music, arts, video – the list of things AI slashed costs on doesn't end. Of course, this reflected on content creation and content strategies.
How it used to be
Beyond the content team, many more people contributed to content behind the scenes. Designers helped create visuals that matched the brand from scratch, video editors stepped in for YouTube or TikTok ideas, and repurposing content into different formats meant hours of work and multiple teams involved.
Ultimately, all ideas were tread carefully because the effort was huge and the success was unknown.
How things look now
Now there's so much more room for creativity. For example, here’s my picture as an action figure:
Sure, this is a 2-month-old trend, but I thought it would be a great idea to include it in the article. Back in the day, if I had such an idea, I would have had to reach out to artists, wait for them to finish the drawing, and hope our visions aligned. And let's not forget about planning: I had to come up with this idea very early, so that the article would be done without delays.
AI has made content creation effortless, be it adding a video or a meme into an article or turning it into a LinkedIn carousel, the tools are ready. And AI is not just a way to test your wild ideas but also a source of insights, helping you brainstorm posts, create videos, and stay on top of trends with AI-powered analytics, all at your own pace.
In essence, content creation, repurposing, and distribution are now part of a continuous feedback loop fueled by AI. The loop begins with data on what works, moves into smart adaptation and reuse of content, and feeds back into strategy through ongoing performance analysis. So content marketing is now more agile, with AI acting as both the engine and the compass. The bad news? As Kate, our CEO, pointed out, there’s a high chance of your LinkedIn feed looking amazingly repetitive and boring these days.
So, what will happen to us once GPT-5 is out?
You know the worst thing that happened to me with generative AI on the market? I had to recall how to use an em dash. And trust me, no one, and I repeat, NO ONE, has ever been using it before. And now look at us, everyone is using the em dash like it's nothing.
But I don't think it's for the worse. In my opinion, only those unwilling to get better are scared of losing to machines. Those who let AI do all the work for them will get banished, but those who keep grinding and looking for new ways to improve their content with AI as a creativity fuel will succeed.
Just like interpreters didn’t fade away once Google Translate was introduced, AI chatbots are like exoskeletons for our brains – we can do creative stuff better and faster with them, but they won’t do things for us. And they surely can’t help you build your brand right, as machines, with all due respect, don’t care about people’s business. But we do, so let’s get your marketing done.
