What Is Synthetic Media? Types, Benefits, and Best Practices

That celebrity endorsement? Fake. The news clip you just watched? AI-generated. The podcast host’s voice? Entirely synthetic. 

On TikTok and Instagram, “babies” are posting emotional confession videos, only they’re not real infants but AI-generated faces trained to mimic human expressions. A deepfaked Tom Cruise casually cracks jokes and plays golf on social media. Virtual influencers like Lil Miquela, who are landing brand deals that most real creators could only dream of, are actually AI-generated. Even news outlets are experimenting with AI-generated anchors to deliver the day’s headlines.

Welcome to the uncanny frontier of synthetic media, where algorithms are the new artists and authenticity is a topic of debate. But what is synthetic media? 

Take a look at this video, for example. It's a clip created entirely using an AI video generator.

Synthetic media software like AI writers, AI image generator, AI video generators, AI music makers, and text-to-speech tools, can now produce entire pieces of content that once required human imagination and technical skill. In minutes, these tools can compose music, write articles, generate hyperrealistic imagery, or clone a human voice with uncanny accuracy.

It isn’t just reshaping entertainment; it’s rewriting how we perceive truth, trust, and creativity online.

In this article, we’ll explore how synthetic media works, where it’s being used, and why it’s rapidly becoming one of the most disruptive forces in digital content creation.

From AI-generated art to cloned voices and virtual influencers, you’ll see how this technology is transforming industries and challenging our very sense of reality. We'll also explore critical questions about ownership, consent, misinformation, and the future of creative integrity in a world where anything can be fabricated.

How does synthetic media work?

At its core, synthetic media is powered by generative AI models trained on vast datasets of text, images, audio, and video. These models learn patterns, how people speak, move, and write, and then use that knowledge to create new, realistic-looking (or sounding) content.

Different types of AI architectures drive different forms of synthetic media:

• Generative adversarial networks (GANs): Two AI models—the generator and the discriminator—work together to create and refine content. The generator produces new media, while the discriminator evaluates whether it looks authentic. This feedback loop enables GANs to create remarkably realistic images and faces.
• Recurrent neural networks (RNNs): Commonly used for text generation, RNNs predict the most likely next word in a sequence, allowing AI models to write coherent sentences, paragraphs, and even full-length articles.
• Deep neural networks: These models are trained to recognize and recreate complex visual and auditory patterns, making them ideal for synthesizing lifelike videos, speech, and human faces. Deep learning methods also power deepfakes, AI-generated videos that mimic real people’s expressions, voices, and movements.

Beyond these core architectures, technologies like transformers and diffusion models enable advanced text-to-speech and text-to-image generation. These systems can transform simple prompts into natural-sounding audio or hyperrealistic visuals, illustrating how quickly AI can turn language into media.

Together, these systems form the backbone of synthetic media—turning data into digital creativity at a speed and scale never seen before.

The result? Media that feels human-made but is entirely algorithmic, created not by cameras or microphones, but by code.

Synthetic media vs. non-synthetic media

Synthetic media is constructed partially or entirely by computers. Non-synthetic media refers to any media created conventionally, i.e., media produced with human input.

Think about it this way:

• A synthetic media example could be an AI-generated newscaster delivering headlines in a perfectly human voice, even though no real anchor or camera was involved.
• A non-synthetic media example would be a journalist filming and narrating that same segment themselves, using real footage and natural speech.

Both serve the same purpose of sharing information, but their origins are entirely different: one is driven by data and algorithms, while the other is driven by human intent and experience.

What are the different types of synthetic media?

Synthetic media comes in various forms, depending on the type of content being generated. While the technology behind each may differ, the goal is the same: to create human-like media more quickly, affordably, and at scale.

1. AI-generated text

From blog posts and news articles to marketing copies and stories and novels, AI writing tools can now create natural-sounding text based on prompts or datasets. Platforms like ChatGPT, Jasper, and Copy.ai use large language models to generate everything from marketing content to technical documentation. Take a look at ChatGPT generating a children's story below. 

2. AI-generated images

Text-to-image models, such as DALL·E, Midjourney, and Stable Diffusion, can transform short text prompts into detailed visuals — ranging from art and product mockups to photorealistic portraits. These systems are trained on vast image datasets and can blend concepts, styles, and emotions in entirely new ways. Here's an example of an AI-generated image of a city's skyline.
 

3. AI-generated video

Video generators, such as Synthesia, PiVideo generatorska, and Runway, allow users to create realistic video content without the need for cameras or actors. They can animate avatars, sync lip movements to scripts, or generate entire scenes with minimal input.

4. AI-generated audio and music

AI tools can compose background music, mimic instruments, or clone human voices. Examples include tools like Soundful and Suno for music, or ElevenLabs for realistic voice generation. This has major implications for podcasts, ads, and entertainment production. 

5. AI-generated avatars and virtual influencers

From lifelike brand ambassadors to digital personalities like Lil Miquela, AI avatars are reshaping influencer marketing and digital entertainment. These personas can be entirely fictional yet interact with their audiences in real-time.

These types of synthetic media highlight how deeply AI is blending into creative and communication workflows

What are the top applications of synthetic media in real world? 

Synthetic media is no longer confined to research labs or niche creative projects. It’s quietly becoming part of everyday workflows across industries.

With the rise of generative AI chatbots and creative tools, its use cases have expanded dramatically. People now use AI to write social media posts, blog articles, and emails; to design visuals for personal and professional brands; and to produce short-form videos for platforms like TikTok, Instagram, and YouTube. Synthetic media isn’t a niche technology anymore; it’s part of daily digital life.

On the business side, from marketing campaigns to entertainment and education, it’s transforming how content is made, personalized, and scaled. What makes it remarkable isn’t just the technology; it’s how seamlessly it’s blending into human creativity. The best results today don’t come from AI replacing creators, but from humans who know how to collaborate with it.

1. Marketing and advertising

Brands use AI-generated videos, voices, and visuals to create campaigns in multiple languages and styles without expensive studio setups. Virtual influencers and AI avatars are becoming brand ambassadors, offering a way to reach audiences 24/7 while staying perfectly on message.

For example, Coca-Cola’s “Create Real Magic” campaign let users generate custom artwork with OpenAI models, blending brand storytelling with consumer creativity.

2. Entertainment and gaming

Filmmakers and game developers are using AI to generate realistic characters, backgrounds, and even dialogue. Synthetic actors can perform without reshoots, and AI music generators are scoring entire soundtracks, cutting production time dramatically. In fact, people are even creating their own games using generative AI tools

Studios use generative models for rapid prototyping, character design, and trailer generation to test audience reactions before release.

3. Education and training

Synthetic media helps educators and organizations create immersive learning experiences. AI avatars and text-to-speech tools can turn written material into interactive video lessons, making content more engaging and accessible across languages.

Platforms like Synthesia enable instructors to generate multilingual training videos featuring virtual presenters without recording a single clip.

 4. Business communication and corporate training 

Companies are using synthetic media to scale internal communication, sales enablement, and onboarding. AI-generated training videos, personalized executive updates, and multilingual presentations can be produced in minutes, reducing costs while improving consistency and reach across global teams.

Beyond training, organizations are also turning to synthetic media for customer education, like creating quick product tutorials, onboarding walkthroughs, and help center videos without requiring a production team. HR departments use AI avatars for policy explainers and culture onboarding, making large-scale communication more engaging and human-like.

Some companies are experimenting with personalized internal messaging, where an AI-generated version of a company leader delivers tailored updates to different departments or regions.

 5. News and journalism 

Media outlets are experimenting with AI-generated anchors and automated news summaries to deliver faster, localized updates. This use case also highlights the growing need for transparency in AI-generated content.

For example, Xinhua News Agency introduced AI-powered news anchors capable of reading stories around the clock, demonstrating both efficiency and ethical complexity.

 6. Accessibility and inclusivity 

Text-to-speech and AI dubbing tools make content accessible to people with disabilities or language barriers. An AI voice can narrate written material for the visually impaired or instantly translate and voice over videos in multiple languages.

For example, YouTube’s automatic dubbing features and modern voice cloning tools help creators reach global audiences with natural-sounding multilingual narration.

What are the benefits of synthetic media?

Synthetic media tools are redefining our work with more intelligent, more efficient methods that produce media experiences of unprecedented quality. The primary benefits include:

• Speed and efficiency: Synthetic media can be created rapidly with minimal human input. What once took hours or days of production can now be generated in minutes using AI-powered tools.
• Personalization at scale: AI-generated media can be tailored to specific audiences, languages, and cultural contexts, making it ideal for global brands that need localized content without starting from scratch.
• Always accessible and dynamic: Synthetic media can be produced, distributed, or updated at any time, keeping content fresh and reducing the risk of it becoming stagnant.
• Versatile creative output: From text, images, and video to music and voice, synthetic media supports a wide variety of formats. This versatility enables creative experimentation across multiple content types.
• Cross-platform adaptability: Synthetic media can be integrated into websites, apps, VR/AR experiences, and games. Its flexibility makes it useful across industries—from marketing and education to entertainment, journalism, and design.
• Cost-effective production: AI-generated media can simulate the look and feel of authentic human-made content, allowing businesses to produce professional-quality campaigns or training materials without hiring actors, photographers, or large production crews.
• Consistency and quality control: Since AI can replicate tone, visuals, or messaging with precision, companies can maintain consistent branding and storytelling across multiple channels and markets.
• Democratization of artistry: Perhaps the most transformative impact of synthetic media is how it’s lowering barriers to creativity. Anyone with an idea, not just trained designers, musicians, or filmmakers, can now bring their vision to life using AI tools. This democratization is enabling a new wave of creators to experiment, produce, and publish content on a global scale.

What are the challenges, concerns, and implications of synthetic media?

Now, Synthetic media also introduces complex ethical, creative, and societal challenges that require careful navigation.

• Misinformation and deepfakes: Perhaps the biggest problem with synthetic media is that we can't tell whether the media is real or fake. The same tools that enable creative storytelling can also be used to spread false or misleading content. Deepfakes, AI-generated videos that mimic real people, pose significant risks for politics, journalism, and public trust. 
• Authenticity and trust: When it becomes impossible to tell whether content is real or AI-generated, audiences may grow skeptical of all media. This erosion of trust threatens not just individual creators but institutions built on credibility. The result is a growing “seeing is believing” crisis, where even authentic footage may be doubted.
• Copyright and ownership issues: Questions about who owns AI-generated content remain unresolved. If an AI system is trained on copyrighted material, does the output belong to the creator, the tool, or the original data owner? ChatGPT made it incredibly easy for everyone to create Ghibli images but the distinctive art style is still owned by Studio Ghibli. This raises a broader question: where does inspiration end and imitation begin? Until clearer copyright frameworks emerge, creators, brands, and AI developers all operate in a gray area of artistic ownership.
• Ethical use and consent: Using someone’s likeness or voice without permission raises legal and moral issues. Voice cloning, facial synthesis, and virtual doubles all demand new frameworks for digital consent. Cases of AI voice cloning used to impersonate celebrities and even scam victims show how easily these tools can be misused.
• Job displacement and creative disruption: As synthetic media automates aspects of production, some creative and technical roles risk being reduced or replaced. For instance, marketing teams increasingly use AI video generators for ad localization instead of hiring actors or production crews. The challenge lies in reskilling professionals to work with AI rather than compete against it.
• Bias and fairness: AI models are trained on human-generated data, which often carries biases. These biases shape the media, unintentionally reinforcing stereotypes or excluding certain voices. Image generators, for example, have been criticized for producing gendered or Western-centric depictions of professionals when given neutral prompts.
• Regulatory and governance gaps: Current laws lag behind the pace of AI development. Governments and platforms are only beginning to draft policies for labeling synthetic media, managing misuse, and protecting individual rights.

What are some best practices to follow when creating synthetic media?

Now, the challenges of synthetic media don’t mean we should avoid using it altogether. In fact, these tools are transforming how we work, communicate, and create, both personally and professionally. However, as the boundaries between the real and the synthetic blur, it’s essential to use them responsibly and transparently. Here are some key best practices to follow when creating synthetic media:

• Disclose when content is AI-generated: Be upfront about using synthetic media, whether it’s an AI-generated voiceover, avatar, or image. Transparency helps maintain trust with audiences and prevents confusion or misinformation.
• Respect copyright and intellectual property: Avoid using AI tools to directly imitate copyrighted art styles, music, or likenesses without obtaining the necessary permission. If you’re inspired by a brand or creator’s style, add your own originality instead of replicating it.
• Seek consent when using real identities: Never use someone’s voice, image, or name in synthetic content without their explicit approval. Even harmless parodies can cross ethical or legal boundaries when consent is missing.
• Prioritize truthfulness in informational content: If you’re generating educational, journalistic, or marketing material, verify facts and avoid presenting AI-created fabrications as real events. Synthetic content should enhance storytelling, not distort it.
• Use high-quality, unbiased data: When training or fine-tuning AI models, ensure the datasets are diverse and representative. This reduces the risk of perpetuating stereotypes, exclusion, or misinformation. If you’re using ready-made AI tools instead of building your own, take time to research them on G2. Reading authentic user reviews and real-world feedback on G2 can help you identify tools that prioritize data quality, transparency, and ethical AI practices.
• Label and watermark your content where possible: Watermarks, metadata tags, or on-screen labels can help signal that content is AI-generated. Many emerging frameworks, like the Coalition for Content Provenance and Authenticity (C2PA), are standardizing this approach.
• Balance automation with human creativity: AI should complement, not replace, human vision. Use synthetic media to accelerate workflows and spark ideas, but let human judgment guide quality, context, and emotion.

What are the top synthetic media tools to use? 

The market for synthetic media software is constantly developing as new competitors and cutting-edge technologies challenge established standards. These platforms give us complete control over our synthetic media, with stringent and comprehensive privacy standards to guarantee the tool is utilized safely.

Here are the top-rated tools to explore based on the G2 Fall 2025 Grid® for Synthetic Media Software:

• Canva: Best for all-in-one content creation and design
• Synthesia: Best for AI video creation and corporate communication
• Creatify AI: Best for short-form video ads and social media campaigns
• VEED: Best for video editing and repurposing content
• HeyGen: Best for AI avatars
• Murf.ai: Best for realistic AI voiceovers
• ElevenLabs: Best for voice cloning and audio storytelling
• AKOOL: Best for marketing visuals and creative automation
• Gemini: Best for multimodal content generation
• Adobe Firefly: Best for creative professionals in design ecosystems

Frequently Asked Questions (FAQ) about synthetic media

Q1. What is the future of synthetic media?

The future of synthetic media lies in real-time, hyper-personalized content creation. As generative AI models improve, we’ll see brands producing on-demand ads tailored to individual viewers, educators creating interactive learning avatars, and journalists using AI to generate localized stories. Regulation, ethical frameworks, and watermarking technologies will likely evolve alongside to ensure transparency and authenticity.

Q2. What are the risks of synthetic media?

The biggest risks include misinformation, copyright violations, and the misuse of someone’s likeness without consent. Deepfakes and voice clones can be weaponized for fraud or manipulation, while bias in AI datasets can lead to unfair or misleading outputs. That’s why responsible use, disclosure, and fact-checking are essential in any synthetic media workflow.

Q3. What skills are needed to create synthetic media?

You don’t need to be a programmer to create synthetic media today, but key skills help: basic understanding of AI tools, creative storytelling, video and audio editing, prompt writing, and data ethics. For advanced creators, familiarity with deep learning concepts, data curation, and model fine-tuning can unlock greater control and originality.

Q4. How to detect AI-generated content?

AI-generated text often shows subtle signs like overly polished tone, repetitive phrasing, or a lack of nuanced detail. AI content detectors like GPTZero and OpenAI’s classifier can help flag AI-written text. Always cross-check sources, verify quotes, and look for inconsistencies in context or tone.

Q5. How to detect AI-generated images?

Look closely for visual irregularities such as distorted hands, asymmetrical faces, inconsistent lighting, or unrealistic reflections. Reverse image search can reveal if a picture originated from an AI model. Tools like Hive AI, Reality Defender, and watermark detection systems can also identify synthetic visuals.

Q6. How to detect AI-generated video?

AI-generated videos may feature unnatural eye movements, inconsistent lip-syncing, or slight timing delays in gestures. Frame-by-frame analysis can reveal visual glitches or mismatched lighting. Platforms like Deepware Scanner and Sensity AI specialize in detecting deepfakes and synthetic video content.

A new era for media 

We are at the beginning of a paradigm change. Content creation is shifting from the physical to the digital realm, enabling us to produce work that we never could before. Synthetic media is gradually growing in terms of realism and simplicity of use while also producing excellent results. 

However, it’s also vital to note that AI and related technologies cannot be produced with ethics as a secondary consideration. Principles must be front and center, an inherent part of every organization, reflected in business policy, and in these revolutionary technologies.

If you’re intrigued by synthetic media, explore a little about the best generative AI tools that you can start using today to create visuals, videos, and content effortlessly.

This article was published in 2023 and has been updated with new information.