The evolution of AI in content strategy

AI has completely changed content creation and strategy over the last year or so.

There was a time when every blog post was written entirely by a human, ideas were developed from scratch, and pages were built around a single keyword. Today, the process looks very different. AI has not only changed how content is produced, but also how it needs to be written in order to perform well.

From early automation to generative AI: how AI evolved content creation

Today, AI is being used across almost every business, every industry and every age group. Between 2020 and 2025, the number of SMEs using AI has grown significantly, rising from 5.6% to 54%. But even with lots of businesses now using AI, not all of them understand how it works and impacts search, or how to use it to get the best out of content creation.

In this article, I break down the full evolution of AI in content, from where it started to where it is today, how the marketing industry and other businesses have adapted their expectations, and the best practices you should be using right now.

The early stages of AI

AI has been around since the 1950’s, but the early AI tools were very limited. In 1980, early machine learning meant AI could automate small tasks, analyse data and support simple processes, but it lacked real understanding or context. AI made things more efficient, but it couldn’t create meaningful content or provide strategic insight.

At this time, AI in marketing was used for email automation, recommendation engines, keyword research and basic chatbots. These tools helped organise information and spot patterns in data, but they couldn’t generate anything original or particularly useful on their own.

The development of machine learning and LLMs

The start of deep learning and generative AI began in 2010, and things have moved on quickly since then. We’re now surrounded by generative AI tools that can produce blog posts, campaign ideas, images and more in mere seconds. AI isn’t just in standalone tools anymore; it’s built into almost everything we use and has moved from just analysing content to actually creating it.

Large language models (LLMs) are trained on vast amounts of online data. This means they’ve been exposed to a huge range of content, topics and writing styles. Instead of pulling from a single source, they recognise patterns in how information is written and use that to generate responses that match a user’s search intent. If the information you’re asking about exists online, there’s a strong chance the model has seen similar examples before. It then uses those patterns to produce a response that mirrors existing information, often in a new or reworded way. That’s why they’re so effective for tasks like drafting, summarising or explaining topics quickly. But it’s also why they can lack originality or produce incorrect information if not reviewed properly.

This shift has been significant for marketers. AI is no longer just supporting data analysis or automating smaller tasks, it is now directly involved in creating content itself. As a result, the way we work has evolved. Tasks like ideation, outlining and drafting can now be completed much faster, which has accelerated content production across the board.

However, with this increased efficiency comes a shift in expectations. When content is easier to produce, the standard for what is considered valuable rises. Quality, clarity and usefulness matter more than ever, as simply publishing more content is no longer enough to stand out.

The biggest change is not just how widely AI is being used, but how embedded it has become in day-to-day workflows. What was once seen as a helpful addition for businesses, is now something most teams rely on as part of their core process, even for things as simple as wording emails.

This growing reliance on AI is not only changing how content is created, but also how it is discovered. As AI becomes more integrated into search, it is reshaping the way users find information and, in turn, how content needs to be written.

How AI is changing search

A recent study (March 2026) found that nearly 25% of teams now see LLMs as their primary content audience, which shows just how quickly things are shifting. But it doesn’t mean we should just put all of our focus there. SEO, website optimisation and social media are just as important as ever.

The introduction of LLMs and AI Overviews (AIOs) has changed how people search. Users are now asking longer, more conversational questions and expect direct answers without having to click through multiple pages. Because of this, content needs to be structured in a way that’s easy for AI to understand, extract and surface in results. To get more accurate performance data, we now look at:

• Organic traffic
• Keyword rankings
• AI visibility (AIOs, LLMs)
• Commercial vs informational performance
• Social media performance
• Brand presence

Organic traffic on its own does not mean much if it is not converting, especially as search behaviour continues to evolve. People, especially younger generations, are no longer relying on Google, and 74% of Gen Z’s use TikTok as their primary search engine. This makes overall brand presence more important than ever.

To add to this, AI is also pulling content from Reddit, Instagram, LinkedIn, TikTok and YouTube into AI Overviews, so having a consistent and well thought out content strategy across all channels is essential.

It is also important to remember that visibility alone is not enough. Many businesses are starting to appear more frequently in AI results, but not always for queries that drive real commercial value. At Quibble, we are seeing clients show up in AI Overviews for informational searches, which is great for awareness, but it does not always lead to conversions. Therefore, a big part of our focus for our clients is shifting that visibility so that content is not just being found, but appearing for the queries that actually matter to the business and turning into conversions.

What should companies focus on when producing content?

Content needs to properly answer questions and give real value. Producing loads of content for the sake of it doesn’t work anymore.

What actually works now:

• Depth over volume – Answer all of your customers’ potential questions. Not just “it’s made using a durable stretchy fabric”. But, what makes it durable and stretchy? What is the fabric composition and construction that allows this? How does this beat competitors?
• Clear structure and easy readability – Split out content into subtitles with clear sections and use formats such as tables and FAQs to display key information.
• Answering real user questions – Use tools such as Also asked and fan out query to ensure you are covering all topic gaps and relevant questions.
• Balancing informational and commercial intent
• Adding genuine insight or experience, showcasing the company’s value and expertise – This is vital!

AI Do’s and Don’ts for Content

Do	Don’t
Use AI to speed up research and processes	Publish AI content without reviewing it
Create proper, detailed briefs	Rely only on AI for strategy
Add your own insights and examples	Ignore tone of voice
Keep content structured and clear	Chase quantity over quality

How we use AI in practice at Quibble

We’ve spent a lot of time testing and refining how we use AI and LLMs so we can actually get the best out of them for our clients. It’s not about using AI for the sake of it, it’s about understanding how it works and where it adds value.

What we’ve built is a process that combines AI efficiency with human input, real data and actual experience. AI helps us move faster and spot patterns, but the strategy, direction and quality always come from us.

Here’s what that looks like in practice:

Initial Interviews, research & persona development

We always start with real people, real questions and real information:

• Founder interviews
• Sales insights
• Most asked customer questions
• Goals for the company’s future
• Target audience

AI helps us organise and analyse this faster, such as writing up meeting notes and transcripts, but it doesn’t replace us actually taking the time to understand the brand’s voice and audience.

Content strategy

When it comes to content strategy, we combine human insight with AI driven analysis. We start by pulling together all of our research, including team interviews, SEO documents, keyword data and competitor analysis, then layer in tried and tested AI systems to strengthen and scale the process.

This allows us to:

• Run query fan outs
• Analyse AI responses in depth to uncover hallucinations, gaps in knowledge and competitive opportunities

All of this feeds into our content strategy that considers every area of your brand’s visibility, from AI visibility and SEO through to social search. By combining this with real industry knowledge and an understanding of current trends, we can quickly identify priorities and keep content relevant to your audience.

We are also continuously testing new AI-powered tools and softwares to improve efficiency, uncover additional insights and add additional value for our clients.

Content creation

The key to good AI content creation is all in the information you feed it. We use AI to streamline our content creation process by:

• Providing AI with detailed, fully human-written briefs and breakdowns
• Reviewing keyword, competitor and fan out query research to identify content gaps and opportunities
• Creating projects within LLMs which outline the brand tone of voice and key information about the company and its target audience
• Supplying all data to ensure accuracy
• Always proofread and edit using a human to ensure accuracy and quality. The better the input, the better the output. It’s as simple as that.

But remember, content isn’t just written anymore; we also utilise AI for video editing and image generation. Tools such as CapCut, Figma, Canva and Photoshop all feature AI editing tools which help create social content and infographics.

We also utilise a range of other AI tools to:

• Transcribe videos
• Create video scripts
• Collecting meeting notes
• Identifying thin or overlapping pages
• Produce FAQ’s for a whole site in 5 mins
• Reply to customer reviews

Across all of this, human input is what ties everything together. AI helps us move faster, but it’s the real data, experience and thinking behind it that actually drives results.

The risks of using AI to create your content

While AI offers efficiency and scale, it is not without risks. Ethical concerns remain at the forefront. Questions around plagiarism, copyright and ownership are ongoing. The introduction of the EU AI Act reflects how seriously regulators are taking transparency and accountability in AI development and use.

AI can replicate tone to a degree, but it often struggles with nuance, lived experience, brand voice and genuine insight. When businesses rely too heavily on AI, the result is often content that feels generic and interchangeable rather than distinctive and authentic.

There is also the issue of hallucinations. AI tools can produce confident but incorrect information. Without human oversight, this can damage credibility very quickly.

The BBC and European Broadcasting Union conducted a study analysing more than 3,000 AI responses across 18 countries and 14 languages. The research tested four major AI platforms to find the most reliable one:

AI Platforms	% of Mistakes Reported	Most Common Issues	Explanation
Gemini (Google)	76%	Sourcing errors, misattribution	Gemini had the highest rate of significant issues, largely due to incorrectly attributing claims to publishers.
Perplexity	~33%	Misrepresentation of information, inaccurate summaries	Responses sometimes distorted original reporting or presented incomplete context.
Copilot (Microsoft)	~33%	Misinterpretation of context, sourcing errors	Copilot occasionally misrepresented facts or attributed claims incorrectly when summarising news content.
ChatGPT (OpenAI)	~33%	Hallucinations, factual errors, outdated information	ChatGPT sometimes generated inaccurate summaries or invented details when responding to news queries.

AI assistants are already beginning to replace traditional search engines for many users. In fact, according to the Reuters Institute’s Digital News Report 2025, “7% of total online news consumers use AI assistants to get their news, rising to 15% of under-25s.” This highlights why human oversight is still essential when using any AI platform. Without careful review, inaccurate information can easily slip through and potentially damage a brand’s credibility and trust.

Research also shows that if you create content with AI it performs great at first, but then “tanks” soon after. After three months, research from SE Ranking showed that none of their fully AI-generated articles were in the top 100 anymore. They disappeared as if they’d never existed. This is because they didn’t have any authority, show any E-E-A-T, or follow a real SEO foundation.

Yes, AI search is all new and exciting, but the fundamentals of SEO have not changed. Strong rankings, and more importantly, rankings that last, still come down to providing real value to the user, building trust and demonstrating expertise in your field.

That is exactly why you cannot rely on AI to create content on its own. It can support the process, but it should never replace your input. The content still needs to sound like you, reflect your knowledge and offer something that is unique.

The future of AI in content creation and strategy

AI is not going anywhere. If anything, it will become embedded more and more in everyday life.

The businesses that benefit most will be those that use AI strategically rather than reactively. That means using it to streamline research, automate repetitive tasks and enhance data analysis, while keeping humans at the centre of creative and strategic decisions.

Personally, I like to think of AI as my personal copywriting freelancer. I still provide the brief, the data, information on the client, feedback and add my own tweaks. All it really needs to do is fill in my gaps.

When used properly, AI does not replace creativity and strategy; it creates more time for it.

What AI in content means for marketing agencies today

For marketing agencies, expectations have shifted. Clients know AI exists and that it can generate content quickly, so naturally, they expect faster turnaround times and greater efficiency. However, what clients and AI cannot generate on their own is strategic insight. They cannot replicate technical SEO expertise, years of industry knowledge, collaboration across a team of specialists, or the ability to align content with wider commercial goals. That is where agencies still provide real value, and I don’t believe this will ever change.

The use of AI has changed my role quite a bit over the past year. I have refined my content creation process, and with the help of my personal AI copywriting freelancer, I now have more time to focus on strategy. Instead of getting caught up in manual tasks, I can spend more time thinking about what actually matters for our clients, how content performs, how it supports the wider business and how it delivers real results.

It has also pushed me to learn more about AI and stay close to what is changing. You have to be more adaptable and more creative in how you approach strategy in this AI world, and due to that, there is less manual work and more thinking about how content fits into the wider SEO and business strategy. That is where I think the real value for clients is anyway.

Is it hard to keep up? Definitely. Things are constantly changing, with new tools, new features and new ways people search. But instead of trying to jump on everything, we have focused on building solid processes at Quibble. That allows us to adapt quickly without everything falling apart every time something shifts.

For me, AI is just a tool. It makes things quicker, but it still needs direction, experience and proper thinking behind it. That is the difference between content that is just fine and content that actually performs.

AI in Content Marketing: Where do we go from here?

Despite all of these changes, the fundamentals of effective content marketing remain the same. Strong content still relies on expertise, creativity and clear strategic thinking. AI can support that process and improve efficiency, but it cannot replace the human insight that makes content genuinely valuable.

The future belongs to marketing agencies and businesses that know how to balance both and use them to their advantage.
Find out more about how AI has evolved in SEO, or to understand how your business’s content currently performs on AI search, send us an email to hello@quibblecontent.co.uk