Transparency and Disclosure Concerns of AI-Generated Content
In this blog post, we briefly examine transparency and disclosure in the use of GenAI for content creation, including recreational, informational, marketing, advertising, and e-commerce purposes. We review key concerns surrounding AI-generated content, the transparency and disclosure requirements introduced by the EU AI Act and major online platforms, and the practical challenges of managing content disclosures at scale. Finally, we introduce vera[tag] and Kladero's broader approach to supporting effective AI transparency and disclosure.
Context
The use of generative artificial intelligence (“GenAI”) has become increasingly widespread in recent years. Users increasingly rely on GenAI tools, such as ChatGPT, Claude, Gemini, Canva, Adobe Firefly, and CapCut, for tasks ranging from research, writing, and software development to data analysis, planning, and creative work.
Of particular prevalence is the use of GenAI in the creation of content for social media, blogs, websites, and other online media. Content creators use GenAI tools to generate text, images, audio, and video, as well as to assist with editing and other content creation tasks. Some of this content is created for recreational or personal purposes. However, GenAI is also widely used for productive and commercial purposes, including the creation of promotional and marketing materials, advertisements, websites for products and services, and product descriptions for online shops [1], [2].
Concerns With the Use of GenAI
With the outputs of GenAI (“AI-generated content”) becoming increasingly difficult to distinguish from human-created content [3], the increasing use of GenAI as a content creation tool raises a number of concerns for the consumers of such content (e.g., website and blog visitors, social media users, and e-commerce customers).
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Misinformation. GenAI systems have known limitations in producing content that is factually accurate or up to date and may also hallucinate [4], [5], [6], [7] (i.e., generate information that is incorrect or unsupported while presenting it in a plausible and confident manner). Consumers of such content may thus be exposed to inaccurate or misleading information and, in turn, develop an incorrect understanding of the subject, product, or service being presented.
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Perception. Knowledge of AI involvement may affect how consumers perceive content in different ways. First, consumers may perceive AI-generated content as less credible or more prone to error, with studies reporting differences in perceived credibility between AI-generated and human-generated content [8]. Such skepticism may also be beneficial by prompting consumers to evaluate the content more critically.
Second, consumers may form different expectations about the human effort and creativity involved in producing content. In areas such as art, music, writing, games, and other forms of creative digital or physical work, consumers may place value on human authorship and creative effort. GenAI use for such creative work has repeatedly led to public criticism and backlash [9], [10], [11], [12].
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Fatigue. GenAI enables large amounts of content to be produced at very low cost. This has contributed to the proliferation of so-called AI slop (i.e., low-quality, mass-produced AI-generated content) on social media and other online platforms [13]. At scale, the influx of such content can negatively affect user experience; recent research suggests that perceived AI-content overload can contribute to user dissatisfaction and social media fatigue [14].
The three concerns discussed above, among others, make the provenance of content (including whether and to what extent GenAI was involved in its creation) relevant to content consumers. Transparency about the use of GenAI can provide consumers with additional information for assessing the reliability, origin, and nature of the content they encounter.
Transparency and Disclosure Obligations
The concerns introduced in the previous section have also been recognized by policymakers and online platforms, which have responded with regulations and platform rules addressing transparency and the disclosure of GenAI use.
EU AI Act
A particularly notable regulatory response is the European Union's Artificial Intelligence Act (“AI Act”). Adopted in 2024 and amended in 2026 through the Digital Omnibus on AI, the AI Act establishes a risk-based regulatory framework for the development and use of AI in the EU [15], [16]. The Act prohibits certain AI practices, imposes specific requirements on high-risk AI systems, regulates general-purpose AI models, and establishes rules for governance, supervision, and enforcement.
Of particular relevance here, the AI Act also establishes transparency obligations for certain AI systems and AI-generated content. Article 50 requires disclosure when individuals interact with certain AI systems, machine-readable marking of AI-generated or manipulated content, and disclosure of deepfakes and certain AI-generated text concerning matters of public interest [15]. These transparency obligations apply from 2 August 2026 [17].
Platform Rules
Major online platforms, including social media and e-commerce platforms, have also introduced their own rules and mechanisms for the disclosure and labeling of AI-generated content. These platform rules apply in addition to, and may complement, applicable national or regional regulation by imposing platform-specific disclosure or content-moderation requirements on their users.
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YouTube. YouTube requires content creators to disclose content that has been meaningfully altered or generated using AI when it appears realistic [18]. This may include, for example, realistic depictions of events that did not occur or of people saying or doing things they did not actually say or do. YouTube displays corresponding AI labels and may also apply them automatically, where possible, using its own detection systems [19].
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TikTok. TikTok similarly requires creators to clearly label AI-generated or significantly edited content that realistically depicts people or scenes [20]. Creators can provide this disclosure using TikTok's AI-generated-content label or through a clear caption, watermark, or sticker. TikTok can also automatically label content that it identifies as AI-generated or modified [21].
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Meta. On Facebook, Instagram, and Threads, users are required to disclose photorealistic video or realistic-sounding audio that has been digitally generated or altered using AI; failure to do so may result in penalties [22]. Based on these disclosures, Meta may display an
AI infolabel on the content. Meta may also apply such labels automatically when its own systems identify content as AI-generated [23]. -
LinkedIn. LinkedIn recommends that users disclose in their posts when they have relied heavily on AI to create or modify content [24]. For synthetic or manipulated media that could misrepresent real events, LinkedIn requires clear disclosure of the fake or altered nature of the content [25]. Separately, for images and videos containing appropriate metadata, LinkedIn may display provenance information indicating whether AI was used to generate or modify the content [26].
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Reddit. Reddit instructs users to disclose when permissible content has been generated or modified using AI, for example by adding a tag or other indication [27]. Its sitewide policy also prohibits presenting AI-generated content as human-generated. Individual subreddits may impose additional or stricter rules for AI-generated content.
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X. X provides a
Made with AIlabel for posts containing synthetically generated content, allowing users to disclose AI use directly on the post [28]. X may also apply labels to AI-generated or manipulated media identified by the platform [28]. In addition, X prohibits deceptively sharing synthetic or manipulated media when it may cause widespread confusion on public issues, affect public safety, or cause serious harm [29]. -
Amazon. Amazon imposes AI-disclosure requirements in several parts of its ecosystem. For books published through Kindle Direct Publishing, publishers must disclose AI-generated text, images, and translations to Amazon, while merely AI-assisted content does not require disclosure [30]. Amazon also requires sellers to identify product images or videos containing photorealistic AI-generated people; where applicable, Amazon uses this information to display an indicator to customers [31].
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Etsy. Etsy requires sellers to disclose when an item offered on the platform was created using AI [32]. In particular, seller-prompted AI creations must disclose the use of AI in the corresponding listing description [33]. The requirement therefore concerns not only AI-generated descriptions or advertising material, but also the use of AI in creating the product itself.
Challenges to Effective Disclosure
Implementing AI disclosure requirements in practice can be challenging, particularly for organizations that create and publish large amounts of content across multiple channels. Among these challenges, highly relevant ones are:
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Scale. Content creators and publishers may distribute content across many websites, social media platforms, online marketplaces, and other channels, each of which may have its own disclosure requirements and mechanisms. Changes in applicable requirements may also require previously published content to be reviewed and, where necessary, updated retrospectively. Thus, effectively managing disclosure at scale requires processes and tools that can (1) operate across different channels, (2) apply or update disclosures efficiently across an entire collection of AI-generated content, and (3) help identify where changes to existing disclosures are necessary.
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Changing rules and regulations. Transparency requirements and disclosure practices can change over time and may differ across jurisdictions and platforms. Content creators and publishers must thus keep track of these changes and understand how they affect their content in order to determine whether disclosure is required, what must be disclosed, and how the disclosure should be presented.
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Impact on engagement. AI content disclosures may affect how consumers perceive and interact with content. In particular, studies have found that AI-content disclosures can reduce consumer engagement [34]; reduced engagement may be especially problematic when content is used in connection with productive or commercial purposes, such as marketing, advertising, customer acquisition, or product promotion. Content creators and publishers may thus need to test different disclosure texts and ways of presenting those disclosures to maintain engagement, while ensuring that they remain clear and transparent.
How vera[tag] Can Help
If you are a content creator or publisher dealing with large volumes of AI-generated content and increasingly complex disclosure requirements, vera[tag] by Kladero is designed for you. Built around the practical challenges of AI transparency, vera[tag] provides the tools needed both to present disclosures to your audience and to manage those disclosures over time.
From the ground up, vera[tag] was designed for agencies, marketing teams, businesses, and anyone else who needs to manage disclosures across large volumes of content. With vera[tag], content creators and publishers manage disclosures across large content collections and multiple publication channels from a single, centralized dashboard. vera[tag] integrates with your existing publishing channels and allows you to add, review, and bulk-update disclosures across many pieces of content at once.
Consumer engagement is also easier to manage with vera[tag]. vera[tag] makes it straightforward to test different disclosure texts and presentation formats, helping you find content disclosures that sufficiently inform content consumers without unnecessarily reducing engagement.
To ensure that you can always manage your content disclosures easily and effectively, at Kladero, we continuously update vera[tag] with new features, integrations, and support for evolving disclosure requirements across platforms and jurisdictions. Get started with vera[tag] today and streamline your AI disclosure processes so you can focus on what matters.
At Kladero, we continuously update vera[tag] with new features, integrations, and support for evolving disclosure requirements across platforms and jurisdictions. Get started with vera[tag] today to spend less time managing AI disclosures and more time creating and publishing effective content.
How Kladero Can Help
Beyond vera[tag], Kladero's mission is to help you address the AI transparency and disclosure requirements specific to your needs. Through custom solutions, consulting, and targeted training, Kladero's experts can help you interpret applicable requirements, design effective disclosure processes, and implement them across your existing content creation and publication workflows. Get in touch with Kladero today and take your content disclosure workflows to the next level.
Summary
In this blog post, we briefly reviewed key concerns surrounding the use of GenAI for content creation and the growing importance of transparency about AI-generated content. We discussed disclosure requirements introduced by the EU AI Act and major online platforms, as well as some of the practical challenges of managing disclosures at scale. Finally, we described how vera[tag] can support the management and presentation of AI disclosures, and how Kladero can help address broader transparency and disclosure needs through custom solutions, consulting, and training.
Stay tuned for more posts in this series, where we will examine specific regulations, platform rules, and practical approaches to AI transparency and disclosure in more detail.
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