The advent of the Internet has had a significant impact on globalization and completely changed how we communicate, learn, and work. However, it seems that the Internet is only ‘stage one’ in a much bigger technological revolution – the one of Artificial Intelligence (AI).
The emergence of AI has the potential to transform many fields radically, from retail and manufacturing to defense, finance, healthcare, and casual everyday life. Today, one of the hottest topics is the impact of generative AI on content creation. Is this the start of a new era that will put the best professionals in the field – from copywriters and screenwriters to designers – out of work?
From sound to visual: AI’s role in content creation
In an impressively short period of time, AI can process huge amounts of data. For this reason, the content marketing landscape is already being shaped by generative AI solutions.
AI-powered data solutions can analyze market trends, customer behavior patterns and preferences, as well as feedback on review sites or forums. This helps brands get very targeted insights into which products, designs, tone of voice, or form of content resonates the most with their customers and prospects.
Armed with these insights and trending search topics, brands can employ generative AI tools to create engaging content that reaches their target more effectively and fills the market gaps. For example, if competitors focus their content on innovation, the company can use AI tools to generate omnichannel content emphasizing price (and vice versa).
Thus, generative AI already assists marketers in creating content aligned with granular segmentation of the target audiences, including content in diverse languages. This is a big win for retailers, translation, media and PR agencies, copywriters, bloggers, video or photo content creators, podcasters, etc., and the list is expanding.
Because of AI, various content marketing tasks became less time-consuming, from creating social media posts, newsletter campaigns, and press releases to photo post-production. The most important benefit is that anything AI can do, it can do at scale. On the other hand, human involvement remains essential because, currently, there is no reliable AI tool which could handle the entire process — from collecting and analyzing public web data to making strategic content decisions — alone.
New technologies, same dilemmas: quality or quantity?
Several advantages of using generative AI for content marketing can be distinguished at this point. AI can help save time and costs, boost productivity, and simplify workflows. In some areas, AI might also help create unique content for granular audiences in multiple formats and maintain its regularity.
However, generative AI (even advanced versions of it, such as premium ChatGPT) still makes factual, grammatical, and stylistic mistakes. The creative potential of AI is noticeable, but the generated text often sounds bland, clichéd, biased, lacking empathy and emotional weight. The quality of AI outputs can be improved by very precise prompt engineering, but, in this case, can we really say that generative AI is a democratic and widely accessible technology if it requires niche prompting skills to get quality outputs?
Under these circumstances, a professional specialist is mandatory to ensure the quality of AI-generated content by reviewing, evaluating, and adjusting it. The question about the quality of content provided by AI is still open, so the brands face an uneasy choice: is it better to focus content marketing strategy on quantity or quality?
Moreover, using AI for content creation poses additional challenges and risks that should be treated even more seriously, such as narrow contextual windows, hallucinations, biased outputs due to biased training data, and echo chambers. Moreover, AI-powered content generation tools make it easier to implement malicious agendas by spreading misinformation, deepfakes, and manipulated content. It is increasingly used for consumer spamming and commercial fraud.
In summary, AI tools can be of great help, but to achieve authentic, creative, organic, factual, and ethically correct content and to minimize the potential bias of AI algorithms, it is important to maintain a balance between AI-generated content and the content marketer’s input. For sure, human content creators aren’t going to go anywhere, at least for now. And yet, considering the pace of AI advancement, one might wonder if the situation isn’t going to reverse soon.
Mapping the future
AI tools already offer a great choice of content creation and project management features that might help individuals and entire teams work smarter, increase productivity, and scale their businesses. However, some experts believe that in the future, generative AI tools like ChatGPT will become autonomous in managing all content workflows, from data ingestion to content planning, creation, collaboration, and publishing.
This could indeed be revolutionary and transform various industries and sectors. Furthermore, considering that modern web scraping tools open AI creators vast possibilities of using publicly available data on the Internet for constant AI training and retraining, such progress seems entirely possible.
Publicly available web data contains accessible knowledge from various sources and domains, covering a wide range of topics, language nuances, cultural references, and even dialects and slang. It can be extracted from forums, blogs, public social media posts, academic and news articles, and other sources that allow for improving both factual AI knowledge and contextual understanding.
Nevertheless, AI makers and we, as a society, will have to find ways to contain the challenges and risks that using AI for content creation will bring. It is often believed that the more data an AI system is trained on, the better and more contextually relevant the results of the AI-generated content will be. However, the bigger the scale of web data collection, the harder it is to audit inherent biases and avoid legal and ethical issues, i.e., accidentally using private data or copyrighted materials. It is also still under question how people could be trained to recognize manipulated content and deepfakes.
Fortunately, being a problem, AI can also become a solution to it — AI tools for recognizing artificially created content already exist and are getting more precise. Combined with web scraping technologies, in the future, they can open the possibility to monitor the Internet for malicious and manipulated content way more efficiently.
Final thoughts
There is no denying that AI capabilities to create various content might seem impressive, but so far, AI is only as powerful as the content marketer’s skills to ask the right question and make a precise prompt. Although, for many brands, AI helps to understand user behaviour better than ever before, it is essential to remember that generative AI also raises serious concerns about data privacy and ownership, manipulation, and deepfakes.
AI companies collect publicly available web data for AI training purposes, so it is important to take the ethical and legal aspects into account. Training data must comply with privacy laws (GDPR, CCPA) and respect copyright protection regulations to avoid plagiarism.
On the positive side, invoking AI for content creation brings inspiration and ideas, saves some time and money, and allows for a bigger scale of marketing actions. Even so, human empathy, sensitivity, and creativity remain a unique and unbeatable force. We are yet to see if machines will ever be able to truly surpass it.
Author: Andrius Palionis, Head of Enterprise at Oxylabs