Synthetic Media

Synthetic Media is content created or heavily modified by AI, including generated images, AI voiceovers, video avatars, and AI-produced music or sound.

Also known as: AI-generated media, generative media, AI media

Synthetic Media is content created or heavily modified by AI, including generated images, AI voiceovers, video avatars, and AI-produced music. It spans anything where the final asset was machine-made rather than recorded from the physical world or drawn by a human. The economics changed; the responsible use questions are still being worked out.

What Synthetic Media Means

Synthetic Media covers images, video, audio, or voices generated or substantially altered by AI rather than captured from the real world. It lets marketing teams produce visuals and audio quickly and at lower cost, supporting localization, personalization, and rapid iteration. A single script can become voiceovers in many languages, or product imagery can be generated without a photoshoot, which changes the unit economics of creative production at scale. The category includes generated illustrative imagery, AI voiceovers, video avatars, and music or sound effects produced by AI, but typically excludes light retouching of real photos, which generally falls outside the term.

How Synthetic Media Works

A Synthetic Media workflow starts with a prompt, brief, or source asset and runs it through a generative model trained for that modality. Image models use diffusion or related architectures to produce visuals from text descriptions. Voice models can clone a specific voice or generate generic narration from text. Video models stitch together generated frames or animate avatars. Production setups often layer multiple steps: a copywriter's brief becomes generated imagery, which is reviewed and refined before being assembled into a final asset. Rights, licensing, and disclosure questions belong in the workflow from the start, since handling them after the fact tends to be more expensive than designing for them upfront.

Common Pitfalls and Misconceptions

The important nuance about Synthetic Media is responsible use. It raises questions of consent, disclosure, rights, and authenticity, especially with synthetic voices and likenesses. A common pitfall is generating cloned voices or likenesses of real people without clear consent and rights checks, which carries real legal and reputational risk. Another is producing synthetic testimonial-style content using non-existent people, which sits on the wrong side of the line in almost every brand context. A third is failing to follow emerging disclosure norms and platform rules, which are evolving quickly and tend to land in favor of transparency, particularly for B2B brands where trust is a core asset.

Synthetic Media in Practice

The practitioner position taking shape across marketing organizations is to draw a clear internal line between Synthetic Media that augments creative work and synthetic media that imitates real people. Generated b-roll, illustrative imagery, and synthetic background voices tend to land safely with audiences when used transparently; AI-cloned voices of real spokespeople, deepfaked likenesses, or testimonial-style content using non-existent people sit on the wrong side of the line in almost every brand context, regardless of what the technology can technically produce. A short written policy that names approved uses, disclosure requirements, and off-limits content keeps decisions consistent across the team rather than left to individual judgment.

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Synthetic Media

Frequently asked questions

  • What counts as synthetic media?

    Any content generated or substantially altered by AI, such as generated images, AI voiceovers, video avatars, and machine-produced music or sound effects. Light retouching of a real photo generally falls outside the term, while a generated image or cloned voice clearly fits it.

  • How does synthetic media help marketing teams?

    It speeds production and lowers cost. Teams can create localized voiceovers, generate product visuals without a shoot, and iterate on creative quickly across many variations. The economics make some kinds of campaign work feasible that traditional production budgets would have ruled out.

  • What risks come with synthetic media?

    Issues of consent and likeness rights, the need for disclosure, and the potential to mislead audiences. Synthetic voices and faces are especially sensitive and need careful, transparent use, since the public response to undisclosed synthetic likenesses tends to be sharply negative.

  • Should brands disclose synthetic media?

    Disclosure norms and platform rules are evolving, and in many cases disclosure is expected or required. Being transparent protects audience trust and reduces legal and reputational risk, particularly for any use that could otherwise be mistaken for a real person or event.

  • Is AI-edited content the same as synthetic media?

    Minor edits usually are not. Synthetic media refers to content that is generated or substantially created by AI. Light retouching of a real photo generally falls outside the term, while heavy regeneration or replacement of subjects, voices, or scenes does.

  • What policy should a B2B marketing team have on synthetic media?

    A short written policy on which uses are approved, when disclosure is required, what rights checks must happen before publication, and what types of synthetic content are off-limits. Drawing a clear line between augmenting creative work and imitating real people keeps decisions consistent across the team.

  • How is synthetic media regulated?

    Regulation is emerging quickly, with rules around disclosure, deepfakes, and likeness rights varying by jurisdiction. Watching this space and erring toward transparency tends to age better than waiting for specific rules to land, particularly for B2B brands where trust is a core asset.