The evolution of design tools with Artificial Intelligence has gone from being a futuristic experiment to becoming part of the daily lives of designers, marketers, and content creators. Features like automatic image generation, infinite layout variations, and even style replication no longer surprise anyone. In fact, they define a new standard of productivity and market expectation. With the arrival of recent Canva updates, accompanied by high-visibility campaigns such as those starring Xuxa and Gracyanne, the debate has ceased to be technical and has occupied a social space: after all, who is the author of an art piece created by AI? The designer who guides? The system that generates? The company that provides the trained model? And, expanding the discussion further, to what extent does this process preserve originality, creative value, and the necessary ethics in the use of third-party images and data?

These questions are not abstract; they directly impact contracts, deliverables, brand identity, legal liability, and the practices of those working in communication. Amid the enthusiasm for automation and efficiency, there is also a growing need to understand the limits, risks, and opportunities that arise when technology and creativity merge. This article dives into these points so that professionals can adopt AI in a safe, strategic, and ethical way, maintaining human authorship as a differentiator, not as a secondary detail.

What has changed: AI design tools and recent Canva features

Key features and what's new in Canva
Canva has evolved from just an editing tool to operating as a complete AI creation hub. Features like Text-to-Image and Magic Media allow users to generate images, videos, and style variations from a simple prompt, eliminating the need for stock image libraries or external production. Magic Design creates complete layouts, text, typography, and composition based on a description, while tools like Magic Edit, Magic Expand, and Magic Eraser enable quick adjustments that previously required advanced software. All of this is integrated into Magic Studio, making the editing and experimentation workflow more direct and centralized.

Practical impact for creative teams
In the routine of designers, agencies, and social media teams, these innovations mean speed and scale. The production of art, variations, and A/B testing happens in minutes, reducing costs and operational time. Small teams can deliver more without increasing their workload, and experienced professionals gain autonomy to focus on creative direction while AI handles repetitive tasks. In addition, the unification of palette, style, and automatic format variation facilitates the consistent creation of multi-platform campaigns, which is essential for brands that need to maintain a solid visual identity with high publishing frequency.

Recent cases that sparked debate (campaigns with Xuxa and Gracyanne)
Canva's recent campaigns in Brazil, starring Xuxa Meneghel and Gracyanne Barbosa, reignited the debate over transparency, image rights, and ethical limits in the use of AI for advertising creation. In Xuxa's case, the “Só para Adultinhos” (Only for Little Adults) campaign presented fictional products generated by AI, highlighting how the platform creates images, objects, and concepts that look real. As for Gracyanne, the “Faz Bonito” (Do it Well) action simulated the launch of a fictional gourmet egg brand, “Gracyovos”, with a visual identity, videos, and packaging created entirely within Canva. 

The campaign went viral because many believed the brand actually existed before the reveal, raising discussions about how much AI can confuse the public when there is no clarity about the creative process. These cases left an immediate lesson for the market: when using celebrity images or creating fictional products with realism generated by AI, it is essential to communicate transparently, respect image rights, and make it explicit when content is artificially produced, to avoid misinterpretations and ensure ethical responsibility in design.

Originality vs. derivative generation: the ethical and technical issue

The rise of generative AI has brought an inevitable tension between what can be considered truly original and what is merely a recombination of existing works. Since these models are trained on large databases of images, texts, and styles produced by humans, the generated content never emerges “from scratch”: it is statistically derived from learned patterns, especially since, in the world of ideas and things, there is no genuine originality. Everything is built on “something already done or already said.” This creates an ethical and technical challenge, because the designer using AI may believe they are creating something new, when in practice they are remixing references that belong to third parties.

Additionally, techniques like prompt engineering amplify this discussion, as different instructions can bring the result closer to recognizable styles or even specific artists. This fact limits the ability to claim full originality and opens up questions about authorship, copyright, and even unintentional plagiarism. The core point is that AI accelerates creation but does not eliminate the need for critical awareness: understanding where these data come from, how they are combined, and the boundary between inspiration and appropriation is essential for any professional who wants to use technology without compromising credibility and creative integrity.

Authorship and copyright: legal framework and current uncertainties

The current copyright legislation in Brazil, Law 9.610/1998, protects “creations of the mind expressed by any means or fixed in any medium,” provided they result from a human creative process. This means that works generated exclusively by AI tools, without significant creative contribution from a natural person, find themselves in a legal gray area: AI itself is not recognized as an “author,” as it lacks legal personality or creative consciousness. 

Several studies and legal analyses point to this regulatory gap. For example, academic reviews show that attributing copyright to works created by AI challenges traditional notions of authorship and originality, since AI can combine, remix, or transform data from pre-existing human works without “conscious creation.”

On the international stage, responses vary. Some countries or jurisdictions (like the UK) already consider that the person who “operates the AI”—meaning the one who provides the prompt, defines parameters, and curates—can be recognized as the author, provided there is significant human contribution. On the other hand, in more rigid systems (such as in the US), recent rulings confirm that works produced entirely by AI, without real human intervention, are not eligible for copyright protection.

This uncertain legal landscape creates practical challenges for design professionals, agencies, and clients, especially when the final piece relies heavily on AI, which leads us to an important reflection in light of recent advertising campaigns. When an AI design platform dictates that “anyone can create their own brand from scratch,” as occurred with Canva's campaign with Gracyanne Barbosa, the discourse sells the idea of autonomy and creative empowerment. However, in practice, this discourse can devalue the work of specialized professionals (designers, art directors, creatives), while masking uncertainties regarding authorship, originality, and copyright.

Furthermore, reproducing this logic of “brand created with AI + celebrity” can foster a mindset of devaluing professional design, turning work that requires technique, originality, and visual consistency into mere “AI prompts,” reducing the perceived value and legitimacy of human authorship.

Good practices in the creative process with AI (workflow, documentation, and checkpoints)

Teams using AI need to maintain a clear and documented workflow: record important prompts, identify the source of all assets used, save intermediate versions, and ensure that the final stage has human review and decision-making. 
It is also essential to confirm permission to use third-party images, voices, or styles. Simple checklists and internal policies help standardize the process, and short templates can be included in briefings and contracts to define responsibilities, AI usage limits, and who owns the final ownership of the deliverables.

Transparency and ethics in communication with the public and clients

Being clear about the use of AI has gone from being an option to a practice of trust. Informing when a piece was created wholly or partially by AI avoids perceptions of deception and reduces the risk of crisis, especially in campaigns involving real people, sensitive brands, or institutional messages. Transparency can appear in small labels (“Image generated with the help of AI”), footnotes in ads, or mentions in the description of digital pieces. For clients, it is worth indicating in the delivery report which stages had human intervention and which were automated, reinforcing that creative responsibility remain with the team. 

This type of simple warning increases credibility, helps align expectations, and demonstrates maturity in using technology, strengthening the brand's reputation in the long run.

How to integrate AI without losing the human edge: creative and professional strategies

The true competitive advantage lies not in simply using AI, but in how it is used. Technology accelerates drafts, expands visual possibilities, and reduces repetitive tasks, but the differentiator remains human curation: interpreting context, understanding the audience, directing aesthetics, identifying cultural nuances, and translating brand identity into choices that no AI understands on its own. Art direction, manual refinement, narrative adjustments, selection of references, and conceptual decisions are stages where the human touch transforms a generic output into something authorial, coherent, and truly creative.

For teams, the most solid strategy is to treat AI as a multiplier of possibilities. This means using models to quickly explore pathways, generate variations, test styles, and accelerate prototyping, and then applying fine editing, creating original connections, adjusting details that reinforce purpose, and ensuring consistency with the brand's identity. This hybrid process increases speed without compromising depth.

Thus, authorship becomes defensible: the professional does not just accept what the AI delivers, but guides, selects, refines, interprets, and signs off on the result. The creative value remains in the human eye, and the AI works as an extension of artistic ability, not as a replacement.