How to use AI content gen­er­a­tion for your website

AI content refers to the automated creation of texts, images or videos with the help of ar­ti­fi­cial in­tel­li­gence (AI). This approach makes it possible to ef­fi­ciently produce content for websites without having to rely on manual processes.

What is AI generated content?

The term ‘AI-generated content’ refers to content created with the help of ar­ti­fi­cial in­tel­li­gence. AI models like GPT-4 and DALL·E use al­gorithms and vast datasets to generate text, images or even videos based on user inputs, trans­form­ing the content strategy of many busi­nesses.

By learning from millions of examples, AI can produce content that closely resembles human-created work. As a result, AI content is in­creas­ingly used in marketing, website creation and general content pro­duc­tion. With auto­ma­tion, AI-driven content creation becomes an efficient and cost-effective al­tern­at­ive to tra­di­tion­al manual methods.

What content can be generated with AI?

AI content is extremely versatile and can be generated in various formats.

Text

AI can be used to generate various types of text content. For instance, large language models can create blog posts on a wide range of topics by syn­thes­iz­ing in­form­a­tion from multiple sources and struc­tur­ing it into SEO-optimised texts. AI is also useful for gen­er­at­ing product de­scrip­tions, enabling e-commerce websites to auto­mat­ic­ally create de­scrip­tions based on product features. Beyond websites, AI can also generate per­son­al­ised marketing emails tailored to customer behaviour and pref­er­ences.

Images

AI can also be used to create visual material. AI image gen­er­at­ors like DALL·E, Mid­jour­ney and Stable Diffusion can generate high-quality images and graphics based on text de­scrip­tions provided by users. This is es­pe­cially useful for companies that need visual content quickly. Ad­di­tion­ally, logos and other graphic elements can be created by spe­cify­ing design re­quire­ments, allowing for cus­tom­ised visual assets in a short amount of time.

Videos

AI content also extends to video pro­duc­tion. Some AI tools like Synthesia and Google Veo can auto­mat­ic­ally create simple ex­plan­at­ory videos or an­im­a­tions for use on websites or social media. Ad­di­tion­ally, AI is in­creas­ingly used for automated video editing, sig­ni­fic­antly speeding up the video pro­duc­tion process by cutting footage, adding trans­itions and gen­er­at­ing subtitles.

Voice content

AI-supported speech synthesis enables the gen­er­a­tion of realistic voices for videos, podcasts or other audio content that can be used on websites. Tools such as El­ev­en­Labs create voices that are almost in­dis­tin­guish­able from real speakers.

What are the ad­vant­ages and dis­ad­vant­ages of AI content?

Using AI content offers numerous ad­vant­ages, but it also comes with chal­lenges that need to be carefully con­sidered.

Ad­vant­ages

✓ Scalab­il­ity: AI enables the creation of content on a large scale, making it es­pe­cially be­ne­fi­cial for companies with extensive content needs.

✓ Time savings: One of the major ad­vant­ages of AI is its speed. Tasks that would take human authors or designers hours or days can be completed in minutes by ar­ti­fi­cial in­tel­li­gence.

✓ Cost ef­fi­ciency: With less human labour required, companies can reduce costs, par­tic­u­larly when producing content in large volumes.

✓ Per­son­al­isa­tion: AI can generate per­son­al­ised content based on users’ pref­er­ences and be­ha­viours, enhancing the overall user ex­per­i­ence.

Dis­ad­vant­ages

✗ Quality: While with the right prompt AI can generate content quickly and ef­fi­ciently, it often falls short of the quality produced by human authors or designers, es­pe­cially in creative fields. Since AI relies on existing content, the risk of duplicate content should not be un­der­es­tim­ated. ✗ Bias and hal­lu­cin­a­tions: AI models can contain sys­tem­at­ic biases because they are based on data sets that reflect social ste­reo­types or are in­com­plete. They can also generate hal­lu­cin­a­tions, i.e., plausible but factually incorrect or fab­ric­ated content that misleads users and reduces the re­li­ab­il­ity of the output. ✗ Ethical issues: AI models and their machine learning al­gorithms are trained on existing content, raising questions about the ori­gin­al­ity of AI-generated work and whether it con­sti­tutes a re­pro­cessing of existing material. ✗ Copyright: The legal situation sur­round­ing AI-generated content remains unsettled. Under UK law, computer-generated works can qualify for copyright pro­tec­tion even where there is no human author. In such cases, the author is defined as the person who made the ar­range­ments necessary for the creation of the work (Section 9(3) CDPA). However, how this rule applies to modern gen­er­at­ive AI systems is still evolving in practice.

What tools are there for AI content?

A variety of tools are now available for creating AI-generated content:

• ChatGPT: ChatGPT is probably the best-known AI model for text gen­er­a­tion. It’s based on the GPT-4 algorithm and creates texts that are often almost in­dis­tin­guish­able from those of human authors.

• Jasper AI: Jasper is an AI tool that was developed spe­cific­ally for creating marketing content. It generates emails, social media posts, articles and other content.

• Writeson­ic: Another AI content creation tool that is par­tic­u­larly suitable for copy­writ­ing, blog posts and social media posts.

• DALL·E: DALL·E is an AI model from OpenAI that generates images from users’ text de­scrip­tions. Companies can use DALL·E to quickly create visual content such as il­lus­tra­tions.

• Pictory: Pictory is an AI tool that auto­mat­ic­ally creates videos from text de­scrip­tions. Pictory is par­tic­u­larly suitable for creating ex­plan­at­ory videos and marketing clips.

• Momentum Team: Momentum Team from IONOS gives you access to spe­cial­ised as­sist­ants for content, design, and code. All data is stored and processed securely in data centers within the EU in ac­cord­ance with the GDPR.

How is copyright handled for AI content?

As AI-generated content is a re­l­at­ively new tech­no­logy, the issue of copyright remains largely un­re­solved and raises numerous legal questions.

Legal un­cer­tain­ties currently exist primarily in relation to the following issues:

• Training data: Is it lawful to use copy­righted works to train AI models under UK copyright law, including the UK’s text and data mining ex­cep­tions?

• Liability: Who is re­spons­ible if AI-generated content infringes third-party rights: the model developer, the platform provider, or the user?

• In­ter­na­tion­al dif­fer­ences: Reg­u­la­tions vary greatly depending on the jur­is­dic­tion.

Under the Copyright, Designs and Patents Act 1988 (CDPA) copyright pro­tec­tion generally requires an iden­ti­fi­able author. Section 9(3) CDPA spe­cific­ally addresses ‘computer-generated‘ works. Where a work is generated by a computer in cir­cum­stances such that there is no human author, the author is defined as the person by whom the ar­range­ments necessary for the creation of the work are un­der­taken.

This provision means that computer-generated works may qualify for copyright pro­tec­tion in the UK. However, how this rule applies to modern gen­er­at­ive AI systems has not yet been com­pre­hens­ively tested in the courts. Questions may arise as to who has made the ‘necessary ar­range­ments’, for example, the developer of the system, the operator, or the user.

Pro­tec­tion for computer-generated works lasts 50 years from the end of the year in which the work was created. For website operators, this means that AI-generated content may in some cases qualify for copyright pro­tec­tion under UK law. In practice, however, the right to use such content will usually depend on the con­trac­tu­al terms and licence con­di­tions of the AI provider. The broader legal framework continues to evolve.

Please see the legal dis­claim­er for this article.