It wouldn’t be wrong to say that there’s been an explosion of AI content in the last 2-3 years. In fact, according to Ahrefs, in April 2025 alone, 71.7% of newly published content was created with the help of AI. That’s not a small percentage, by any means.
The problem is that as the use of AI for content creation dramatically increases, so do the difficult questions about ethics, authenticity, and accountability.
Is it acceptable to pass off AI-written articles as human work? Is it ethical to use AI-generated content? Does the way AI works to create content truly stand the scrutiny of ethical and moral standards?
Marketers are now walking a tightrope between innovation and integrity. On one side, AI boosts productivity like never before. On the other hand, the moral and ethical lines have started to become murky.
The million-dollar question is, where do marketers draw the line between using AI as a creative ally and relying on it as a crutch that has the power to erode the very authenticity and trust that brands spend years building.
Let’s try to find out with the help of this article.
What are the Ethical Considerations of AI in Writing?
Here are the ethical lines that AI seems to cross when creating content for you:
1. Plagiarism and copyright issues
AI relies on pattern recognition of vast datasets. The dataset consists of a large number of writings by human writers, which, once trained, the AI can imitate. Sometimes AI produces content that’s eerily similar to existing work, and the writer using it might not even realize they’re just republishing someone else’s ideas.
Traditional plagiarism used to be a clear concept of cut-and-paste theft. But what do we call it when an AI reassembles concepts it absorbed from thousands of sources? The intent might not be malicious, but the result can still be ethically questionable.
The case for copyright infringement also stems from the same problem. Some of the content AI is trained on can be sole copyright and intellectual property of the authors. Something very similar to this happened when Andrea Bartz and several other authors sued Anthropic for training its AI model on their pirated books.
2. Misinformation and hallucinations
AI is also notorious for creating false and misleading information out of nothing. It can cook up some very convincing fabricated content that does not necessarily have a reliable source. Ask it to write about a historical event, and it might confidently state complete fiction. Request health advice, and it could create dangerous recommendations that sound perfectly credible.
Two such cases are worth mentioning here:
- Apple’s AI-generated news summary falsely reported that the BBC had published an article about the suicide of Luigi Mangione, a person arrested for murder.
- In New York, a lawyer used ChatGPT to do legal research. ChatGPT presented fake legal cases, which the lawyer included in his filings. Needless to say, when the issue surfaced, the federal judge barred lawyers from using Gen AI to draft legal filings.
3. Transparency
Should readers know when they’re consuming AI-generated content? Many marketers believe no – if the content is good, does it matter who wrote it? But that misses the point. People make judgments about credibility based on who’s behind the content.
A survey conducted by Bynder reveals some interesting insights in this regard:
- 50% of participants were able to spot the AI-generated copy.
- 52% of consumers were less engaged by the copy that they suspected was AI-generated.
- 26% of the participants felt that the brand using AI to write website copy is impersonal, and 20% straight out called it lazy.
When a brand shares its perspective, customers assume humans at that company actually hold those views. But if AI wrote it and no human really stands behind it, they might even feel deceived.
4. Privacy concerns
Another area where AI content ethics has an impact is the privacy of users and their data. Every time someone feeds information into an AI tool to generate content, they have to share sensitive data. Company strategies, customer insights, or unpublished research, it all goes into the AI’s system.
There is a very valid concern here, since that information can be stored and reused without explicit consent. And even if that data is not completely reused as it is, AI is good at pattern recognition and inference.
This means that AI could piece together sensitive information from multiple inputs and inadvertently reveal it in future outputs for other users. Imagine feeding customer demographic data into an AI to create a marketing report, only to have that AI later generate similar insights for your competitor because it learned patterns from your data.
The uncomfortable truth is that we’re in a grey area. Even AI companies are still figuring out their data handling practices, and regulations are racing to catch up. That gap between innovation and oversight is already showing cracks. For instance, South Korea’s Personal Information Protection Commission recently suspended new downloads of the AI app DeepSeek after the company admitted it hadn’t fully complied with the country’s privacy rules.
5. The credit problem
Next comes the question of credit. Who owns AI-generated content? If AI writes an article, does the company using the AI own it or the AI company? What about all the original creators whose work trained the AI, don’t they also deserve recognition?
But can we really call AI systems authors? Because this is not just about attaching a label; that authorship is accompanied by responsibility and accountability. Ethically, this responsibility should fall on the shoulders of humans, who can be held accountable in a court of law.
Writers, artists, and creators are suing AI companies for using their work without permission or compensation. This is a legal minefield that courts are still sorting out. Meanwhile, marketers are publishing AI content, assuming they have full rights to it. They might not. And by the time the legal dust settles, brands could find themselves on the wrong side of copyright law.
6. Social and cultural biases
AI mostly learns from the internet, and the internet is not safe from human biases, stereotypes, incomplete information, or skewed representations. This has a direct impact on the type of content AI produces.
Maybe the AI consistently describes leaders as “he” or portrays certain demographics in limited roles. Perhaps it uses language that unintentionally excludes or marginalises groups.
The bias obviously isn’t intentional, but that doesn’t make it harmless. When marketers use AI content at scale without careful review, they risk spreading biased narratives under their brand name. And unlike a human writer who is sensitive to such biases or can be educated, AI will keep making the same mistakes until someone notices and intervenes.
7. Job losses
At last comes the ubiquitous fear of job displacement. This elephant in the room just refuses to leave since the whole AI fiasco started, fuelling public anxiety about the future of work.
And let’s be honest, this fear isn’t irrational. When a single marketer with AI tools can produce what previously required a team of writers, editors, and strategists, companies start doing the math. Why pay five content creators when one person with ChatGPT can churn out the same volume?
But here’s where the ethics get blurred. Companies framing AI as a productivity tool are often using it as a replacement tool. They’re substituting human creativity. The writer who remains isn’t elevated to do more strategic work; they’re relegated to being an AI editor, cleaning up machine-generated content for less pay than they earned creating original work.
The ripple effects extend beyond obvious job losses. When experienced writers can’t make a living, they leave the field. The next generation sees no viable career path and chooses other professions.
We end up with a knowledge gap, which means fewer people who actually know how to craft compelling narratives, understand audience psychology, or communicate complex ideas clearly. And then what? We’re fully dependent on AI trained on the work of writers who no longer exist to train the next generation of AI.
There’s also a class dimension that often gets ignored. High-level creative directors and brand strategists aren’t losing their jobs; they’re using AI to become more efficient. It’s the entry-level and mid-career professionals who are getting squeezed out. Where once they were allowed to build expertise and climb to senior roles, they’re now being locked out before they even begin.
What is the Way Forward for Marketers?
When AI comes with so many ethical concerns, how do marketers make sure that they are not sucked into this whirlwind and remain on the right side of moral and ethical grounds?
The stark reality is that AI is here to stay, and completely swearing off it is not very prudent. The smarter move will be to regulate it, consciously and ethically.
Marketers need to be intentional about how they use AI: not just as a replacement for human creativity, but as a tool that amplifies it.
Here are some tips for marketers to use AI responsibly:
- Never use only AI to do your research, and always fact-check the information generated by it.
- Keep in mind AI biases and stop using any AI tool that provides consistently biased results.
- Don’t use AI for creative purposes. Instead, try to leverage it only for getting inspiration or just forming a base.
- And if you do have to use AI-generated content, give your audience a disclaimer that contains proper explanation about why and where AI was used.
- Evaluate the effectiveness of your AI tool on a regular basis.
Wrapping Up
Every ethical concern we’ve discussed comes down to one simple choice: will we use AI to support human creativity, or let the chase for efficiency destroy the trust that marketing depends on? Marketing has always been about building relationships based on trust. And trust isn’t something AI can easily generate, no matter how sophisticated the prompt. It’s earned through consistent integrity, transparency, and the courage to do what’s right even when no one’s watching.
That principle defines how we approach content creation here at Ukti. We prioritise authenticity and accountability over automation, and make sure that every piece of content is supported by real research, human judgment, and ethical intent.
We believe that meaningful marketing begins with honesty, and that’s a standard no algorithm can replicate.
Contact us today to learn more!