AI-generated avatars and synthetic voices have advanced to the point where they can
convincingly mimic human appearance and even speech. Today’s marketers use AI avatars or
voice clones to personalize ads, automate customer interactions, or even replace human
influencers. Yet these techniques raise serious ethical questions. Voices carry emotion and
personal identity, using them without thought risks misleading consumers. As mentioned in a
recent analysis of AI voice cloning, celebrity like synthetic voices increases the trust building
qualities of voices in marketing contexts (Lutz, 2025). At the same time, regulators are trying
to catch up. The EU AI Act will require all AI-generated audio to be clearly labelled as such. This
essay examines the ethical and legal boundaries of employing AI avatars and voice clones in
marketing, covering law, privacy, psychology, labour, misinformation, culture, and responsible
principles, with recommendations for businesses, regulators, and technologists.
Legal and Regulatory Framework
AI avatars and voice clones sit at the intersection of multiple laws. In Europe, data protection
law treats voiceprints as personal data. For example, processing voice recordings to create a
clone requires a legal basis under the GDPR, since voice features (like pitch and speech
patterns) qualify as biometric or identifying data (Lutz, 2025). As one legal review notes, “like
a person’s face, a voice may be regarded as a direct identifier” under EU law (Lutz, 2025). This
means marketers must justify voice use by contract or consent, mindful of strict EU rules on
special category data. Similarly, in the US such as Illinois classifies voiceprints as biometric data
under laws like BIPA, requiring consent for collection.
Beyond privacy, the EU AI Act directly governs voice clones. Under the Act, most voice cloning
tools won’t be labelled high risk by themselves, but any use of cloned voices for interactive
marketing (e.g. chatbots or phone ads) triggers transparency requirements. Companies must
inform users when they are hearing an AI voice (Lutz, 2025). In fact, realistic voice clones
(deepfakes) used in public content must be labelled as synthetic no later than the first
exposure (Lutz, 2025). Moreover, from August 2026 the AI Act mandates explicit human and
machine-readable labels on all AI-generated media, including audio ads, to prevent deception.
These EU rules apply extraterritorially. Meaning any AI-generated voice used on the EU market
must meet them (Lutz, 2025). In the US, federal and state laws are evolving. The FTC (Federal
Trade Commission) has warned against deceptive AI practices, and new bills such as California’s
AI deepfake law make it illegal to use cloned celebrity voices without consent.
On intellectual property and publicity rights, permission is crucial. Voice recordings are often
copyrighted, so using them to train or output a clone requires licensing (Lutz, 2025). Even
more, a person’s voice is treated as part of their right of personality. In many jurisdictions (Lutz,
2025). this means an individual can object if their voice likeness is used without consent (as
actress Scarlett Johansson famously did when an AI clone mimicked her voice (Lutz, 2025).
Both EU and US systems generally require a contract specifying allowed uses of a voice clone
and forbid sell-out of a person’s identity without safeguards. This means marketers must
navigate GDPR, AI regulations, IP law and publicity rights. The emerging consensus is clear
consent and transparency are legal prerequisites for ethical AI voice use.
Privacy and Informed Consent
Voice cloning relies on personal data. Every marketing campaign using synthetic voices should
begin with informed consent. Ethically, voice data embodies identity. It can reveal age, gender,
mood, health and even the speaker’s unique vocal characteristics. EU regulators emphasize
that any processing of biometric voice data demands careful justification. As one guide states,
ethical voice cloning hinges on explicit consent, transparent disclosure, and legitimate
purpose. In practice, that means a company must obtain clear permission from the person
behind any cloned voice, specifying how and where the clone will be used (Lutz, 2025).
Consent should be freely given, specific, informed, and revocable, aligning with GDPR norms.
Marketers must also respect customer privacy when using avatars. If an AI avatar is generated
from a user’s likeness or biometric scans, it too should be treated as personal data. Researchers
argue that an avatar closely resembling its creator should count as biometric data, requiring
privacy safeguards akin to fingerprint or facial recognition. This means designers should
minimize collected data and anonymize features wherever possible. Furthermore, any profiling
or personalization of avatars must be disclosed and governed by users’ privacy rights.
In sensitive cases (e.g. children’s voices or vulnerable populations), extra caution is warranted.
For example, EU law bans using biometric profiles of children without parental consent.
Similarly, using voice clones to sway political opinions could trigger additional rules on
electoral integrity. Marketers should also maintain data security (encrypt voice files) and clear
retention policies. Overall, the ethical axis here is: do not use anyone’s voice or likeness
without their permission, do not mislead people about how their data are used, and treat
voices as the sensitive biometric identifiers that they are (Lutz, 2025).
Psychological Effects on Consumers
AI voices can powerfully influence audiences because humans instinctively trust voices.
Psychologists find a “default to human” bias. Listeners hearing an AI-generated voice that
sounds familiar or local tend to assume it’s a real person. One study in Scotland showed people
exposed to an AI-modified voice mirroring their own accent overwhelmingly believed it was
human, even when it wasn’t. Likewise, a security survey found 70% of people could not reliably
distinguish a cloned voice from the original (Barrington et al., 2025). These findings imply
marketers could intentionally exploit this bias, for example by giving an avatar a matching
regional accent or tone to build rapport. However, this raises concerns. If consumers assume
a voice is human when it is not, their autonomy in processing the message is compromised.
Empirical marketing research warns about these risks. A recent study of TikTok ads found that
AI-generated voices elicited lower engagement than human voices (Wang et al., 2024).
Viewers subconsciously notice a lack of warmth or subtle inflection. The researchers found
that simply lowering the pitch of the AI voice helped narrow the gap in consumer engagement
(Wang et al., 2024). Moreover, ads using AI-cloned celebrity voices achieved engagement
comparable to real celebrities, but at the cost of potential deception. These results suggest
that while AI voices can be optimized for effectiveness, they still suffer an authenticity deficit
for many consumers. If trust is undermined (as some voice actors warn, people do not bother
with their audiobooks when narrated by a “soulless” AI. In short, the long-term effect could be
negative word of mouth or brand distrust.
There is also an uncanny valley in speech. A voice that sounds almost real but not quite can
feel unsettling or manipulative. Importantly, consumers often don’t realize they’ve been
manipulated. Humans have an instinct that familiar voices are real and that makes AI voices
both persuasive and stealthy. Ethically, marketers must consider listener psychology. Deploying
a lifelike AI voice without clear disclosure capitalizes on this subconscious trust and arguably
violates the spirit of honest communication. Responsible use would demand that consumers
be informed whenever an AI is speaking and not a human.
Impact on Creative Labor and the Job Market
AI voice cloning poses a potential disruption to voice artists, radio hosts, and customer service
roles. Already, industry groups warn that thousands of voice talents could be displaced. For
instance, the Australian Voice Actors Association estimated 5,000 local actors’ jobs at risk from
inexpensive AI clones (Taylor, 2024). Their concern is not anti-technology per say, but that
employers might opt for cheaper AI voices for narration, ads, and announcements. One actor
accurately notes that companies may come to regret the lack of human connection if the voice
reading an audiobook is AI-generated. Listeners feel nothing, less connection, when hearing a
synthetic voice.
Union agreements are beginning to address this. Voice actor unions like SAG-AFTRA have
negotiated deals ensuring members retain rights over digital replicas and can earn residuals
when their clone is used (Carras, 2023). Such frameworks suggest an ethical middle ground.
Empower artists to consent and license their voice clones, rather than banning the technology
outright. On the other hand, proponents argue AI can create new opportunities. E.g., voice
actors diversifying into voice tech, or smaller businesses affording voiceover services.
Culturally, there is a concern about eroding craft. A richly performed voice conveys nuance and
improvisation. An AI model can sound smooth but lacks genuine spontaneity. From a consumer
standpoint, the loss of human artisanship may degrade the quality of ads and entertainment.
Companies might save costs short-term, but brands known for authenticity may suffer if
consumers react negatively. Ethically, then, marketers should weigh not just profits but the
social value of creative labour. Responsible strategies might include co-creating with voice
artists (using AI as a tool rather than replacement) and ensuring fair compensation in any use
of voice clones (Lutz, 2025).
Complementing these concerns, smaller-scale voice roles (customer service, e-learning) are
already prone to automation. Yet even here, companies often rely on synthetic voices for
consistency or accessibility. An ethical approach could involve offering users choices (e.g., an
option to talk to a human agent) and retraining displaced workers for higher-value creative
tasks. In short, the job-market impact of AI voices is significant but not wholly negative.
Societies must develop policies like fair bargaining and upskilling, so that the technology uplifts
rather than merely replace talent.
Misinformation and Consumer Trust
AI voice cloning intensifies disinformation risks. Audio deepfakes such as a fake recording of a
celebrity or official are increasingly convincing. UNESCO warns that scammers use just seconds
of someone’s voice to generate urgent calls for money, tricking victims with familiar voices
(Vellani & Common, 2025). Studies confirm that people cannot consistently identify these
fakes (Naffi, 2025). This has two marketing implications. First, if a company’s ad uses a cloned
voice without disclosure, consumers may feel deceived if the truth later emerges, eroding
brand trust. Second, even truthful ads could suffer. Under scepticism, audiences may doubt
real endorsements by saying “that’s probably AI”.
The broader impact is even more concerning. In an era where seeing and hearing are no longer
believing, all audio claims face suspicion. For marketers, this means any synthetic voice content
may be scrutinized or distrusted. Platforms also bear responsibility. Social media that
algorithmically personalize ads might amplify deepfakes through filter bubbles, leveraging the
illusory truth were repeated exposure breeds belief.
Ethically, marketers must avoid contributing to this misinformation ecosystem. Best practice is
clear disclosure. As one recommendation emphasizes, hybrid or AI-generated content should
only be presented without labels if it is purely informative and fact-checked. Otherwise, visible
warnings are needed. This is not only legal (under upcoming EU rules) but also fosters
consumer trust in the long run. In regulated advertising, trade standards could require any
synthetic voice ad be explicitly marked. Companies should also vet AI-generated content
carefully to avoid inadvertently spreading false or biased claims (since text-to-speech models
can introduce errors). By committing to transparency and accuracy, marketers can use AI voices
without compromising consumer trust or contributing to disinformation.
Cultural and Social Considerations
AI voice technology can inadvertently reflect and amplify social biases. For example, linguistic
research shows most AI voice models are trained on mainstream American English (Abate,
2023), sidelining accents and dialects of other communities. Speakers of non-standard English
report frustration at the homogeneity of AI accents. They feel the tools were built with some
other people in mind. In marketing, this matters, if an AI avatar or voice sounds neutral or
stereotypically global (read U.S. accent), it may alienate audiences elsewhere or erase regional
identity. Worse, accent biases in voice clones could reinforce prejudice (studies have shown
people with certain accents are unfairly judged less favourably).
Cultural representation in avatars also raises questions. Companies can choose any avatar
appearance. From skin colour, gender to style, etc. Ethically, these choices send messages. A
recruiting video featuring a diverse AI avatar can inspire underrepresented job seekers but
could backfire if the company’s real workforce is homogenous, feeling it’s mere tokenism.
Similarly, using a youthful avatar for a serious product might unintentionally convey ageism or
bias. Marketers must reflect on what their avatars symbolize. Are they reinforcing stereotypes
(e.g. an animated “sexy” persona for soft drink ads) or genuinely representing the brand’s
values?
Global context is also key. An AI voice that is acceptable in one culture may be unsettling in
another. For instance, certain tonalities or speech patterns have different connotations
worldwide. Ethical marketing should be sensitive to these cultural nuances, ensuring AI
characters do not offend or miscommunicate. In short, social and cultural ethics demand that
AI avatars and voices be chosen thoughtfully. they should avoid bias, reflect diversity in a
genuine way, and respect the cultural identities of target audiences.
Ethical Principles and Best Practices
Drawing together the above, the ethical deployment of AI avatars and voices should follow
core principles of trustworthy AI. The EU’s AI Ethics Guidelines are instructive. AI systems must
be lawful, ethical, and robust (European Commission, 2024). In practical terms, this means
respecting human autonomy (provide user control and awareness), ensuring privacy and data
protection, and maintaining fairness and non-discrimination. For voice clones, human
oversight is crucial. A person should review any synthetic content before release, especially in
sensitive ads. Transparency demands that consumers know they are hearing an AI, not be
unknowingly misled (Lutz, 2025).
Privacy and data governance, another core principle. Translate into treating voice data as
securely as biometric identifiers. Companies should document how they obtain and use voice
data, conduct impact assessments if analysing sensitive traits, and allow individuals to
withdraw consent. Non-discrimination implies testing voice generators for bias (e.g. not
defaulting to one accent or gender) and ensuring accessibility (e.g. providing transcripts or
options for those who find certain AI voices hard to understand). Societal well-being suggests
evaluating broader consequences. If an AI campaign might stir controversy or harm vulnerable
groups, marketers should err on the side of caution. Finally, accountability means keeping
audit trails and allowing redress. E.g. offering a human contact if an AI ad somehow violates
rights.
Recommendations based on Mentioned Sources
For Companies (Marketers & Advertisers):
- Adopt clear AI use guidelines. Treat AI voices like any brand asset, with approved
licenses and voice-alignment standards. - Ensure informed consent from any voice talent. Use formal contracts specifying how AI
clones may be used, with options to revoke permission (Lutz, 2025). - Label AI content visibly. If an advertisement uses an AI avatar or voice, disclose it
upfront to maintain trust and comply with regulations (Lutz, 2025). - Mitigate bias. Test voices on diverse focus groups, include varied accents/languages,
and avoid stereotypes in avatar design. - Engage human creativity. Use AI to augment, not replace, human actors when possible.
For instance, employ voice artists as consultants or supplemental characters rather
than eliminating them.
For Regulators and Policymakers:
- Enforce data protection laws on voice cloning. Require impact assessments and
stronger penalties for misuse of voice data. Clarify the status of public figures’ voices
as public data or not, to balance publicity rights with freedom of expression. - Update advertising codes to explicitly require disclosure of synthetic voices in
commercial messages. This could mirror rules for paid endorsement or sponsored
content. - Support workforce transitions. Fund retraining programs for performers and voice
artists and encourage ethical licensing agreements like those negotiated by SAG
AFTRA. - Promote AI literacy. Educate consumers about the existence of synthetic media so they
approach ads with healthy scepticism, and mandate fact-checking obligations for
platforms distributing deepfakes.
For Technology Developers:
- Embed privacy-by-design. Build consent management and data minimization into
avatar/voice tools. For instance, create default settings that do not retain raw voice
data unless needed. - Implement watermarking or authentication for synthetic voices, enabling machine
detection of AI-generated audio (in line with EU mandates). - Prioritize explainability: provide human users (both marketers and consumers) with
simple explanations of how voices are generated and their limitations, enhancing
informed use. - Foster multi-stakeholder collaboration. Work with ethicists, linguists, and disability
advocates when designing voice systems to ensure inclusive, respectful outputs.
In all cases, the goal is responsible innovation and leveraging AI avatars and voice clones can
bring marketing efficiencies and personalization, but only if balanced with respect for rights,
truth, and social values.
Conclusion
AI avatars and voice cloning are transforming marketing by offering new forms of personalized
content. However, as this analysis shows, their use is bounded by legal, ethical, psychological,
and social constraints. Companies must navigate data protection laws, obtain genuine consent,
and avoid deceptive practices that breach consumer trust. They must consider the human
effects. From potential job losses to the emotional impact on audiences. And honour principles
of transparency and fairness (Lutz, 2025). Regulators, for their part, are crafting rules (like the
EU AI Act) to curtail misuse, but enforcement will be key. Ultimately, ethical marketing in the
AI era requires clear frameworks and ongoing dialogue among all stakeholders. By adhering to
ethical guidelines and treating voice clones with the same care as any human medium, firms
can harness innovation without crossing into manipulation or harm.
List of references
Carras, C. (2023, listopad 13). What’s in the SAG-AFTRA deal? Here’s what the union has to say, including about AI terms. Los Angeles Times. https://www.latimes.com/entertainment-arts/business/story/2023-11-13/whats-in-the-sag-aftra-deal-contract-ai-terms
Lutz. (2025). The sweet voices of robots – cloning voices with AI. Financier Worldwide. https://www.financierworldwide.com/the-sweet-voices-of-robots-cloning-voices-with-ai
Wang, X., Zhang, Z., & Jiang, Q. (2024). The effectiveness of human vs. AI voice-over in short video advertisements: A cognitive load theory perspective. Journal of Retailing and Consumer Services, 81(C). https://ideas.repec.org//a/eee/joreco/v81y2024ics0969698924003011.html
Barrington, S., Cooper, E. A., & Farid, H. (2025). People are poorly equipped to detect AI-powered voice clones (No. arXiv:2410.03791). arXiv. https://doi.org/10.48550/arXiv.2410.03791
Taylor, J. (2024, červen 29). Cheap AI voice clones may wipe out jobs of 5,000 Australian actors. The Guardian. https://www.theguardian.com/technology/article/2024/jun/30/ai-clones-voice-acting-industry-impact-australia
Vellani, N., & Common, D. (2025, březen 20). Her grandson's voice said he was under arrest. This senior was almost scammed with suspected AI voice cloning. CBC News. https://www.cbc.ca/news/marketplace/marketplace-ai-voice-scam-1.7486437
European Commision. (2024). Ethics guidelines for trustworthy AI | Shaping Europe’s digital future. European Commision. https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai
Naffi, N. (2025). Deepfakes and the crisis of knowing | UNESCO. https://www.unesco.org/en/articles/deepfakes-and-crisis-knowing
Abate, T. (2023). Automated speech recognition less accurate for blacks. https://news.stanford.edu/stories/2020/03/automated-speech-recognition-less-accurate-blacks
