Learn about AI-generated avatars, their applications and the future trends
Introduction: AI Avatars and the Future of Digital Content
An AI avatar is a digital character that looks, speaks and behaves like a person and is powered by artificial intelligence. It combines a visual body (realistic or stylized), a synthetic or cloned voice, and an AI “brain” that decides what to say. As a result, an AI avatar can present content, answer questions and hold a conversation without a human on camera.
The industry of virtual and digital characters based on artificial intelligence is currently considered one of the most promising and rapidly growing. According to GMI estimates, the AI Avatar market was valued at $5.9 billion in 2023 and is expected to grow at an annual rate of 30%, reaching $57.9 billion by 2031.
It’s worth noting that this is quite a conservative estimate. Grand View Research valued the AI Avatar market at $18.19 billion and predicts it will grow to $270.61 billion by 2030. According to Kings Research metrics, these figures would be $21.50 billion in 2023 and $454.75 billion in 2031, respectively. For more numbers, see our AI avatar statistics.
This discrepancy in estimates is primarily related to the difficulties in analyzing specific markets, especially the Chinese market. Additionally, it’s challenging to determine the role of AI Avatars in the film and television industry.
AI avatars are going mainstream across numerous industries. We’re seeing them take off especially in sales and marketing, training and education, customer support, video production and social media.
This guide explains what an AI avatar is, how it differs from a chatbot, the main types and how businesses use them. It also includes three things you won’t find in most AI avatar guides: results from eight real Pitch Avatar implementations, a simple model for choosing how interactive your avatar should be, and a practical checklist for consent and disclosure.
What Is an AI Avatar?
An AI avatar is a virtual character built with artificial intelligence that can do on-camera tasks just like a human would. The most common form today is the AI video avatar, a talking presenter in a video, but AI avatars also appear in chat windows, on websites, inside presentations and in virtual spaces.
Every AI avatar is made of four layers:
- A visual body: the face and figure you see on screen, from a photorealistic person to a stylized 3D character.
- A voice: speech generated from text, either a stock voice or a cloned voice of a real person.
- An AI brain: usually a large language model (LLM) that understands questions and writes answers.
- An interactive purpose: the avatar is designed to communicate with people, not just to play back a recording.
A simple way to remember it: the avatar is the face, and the AI model (or AI agent) behind it is the brain. For a closer look at each layer, read our explainer on how AI avatars work, step by step.
The capabilities of an AI avatar depend entirely on how it is configured and what data it has been trained on. Depending on what they’re designed for, AI avatars can:
- Host shows, give presentations, narrate content and play characters in videos
- Respond to viewer questions and comments
- Give users advice on different topics
- Act as an AI version of their creator (also known as a “digital clone” or “digital twin”), with the creator’s face and voice
- Have natural back-and-forth conversations
Today’s AI avatars can do all this while making human-like facial expressions and gestures, speaking with the right tone and emotion for whatever situation they’re in. The best ones are so convincing that at first glance, you might not even realize you’re not looking at a real person.
The Evolution of AI Avatars: A Brief History
The concept of the modern AI avatar did not appear overnight. It is the result of three distinct technological streams converging over decades: virtual worlds, conversational AI, and generative models.
- The Vision: Science Fiction and Virtual Worlds. The cultural imagination for avatars was largely seeded by science fiction. Neal Stephenson’s seminal 1992 novel, Snow Crash, introduced the “Metaverse”, a persistent virtual reality inhabited by users represented by their “avatars”. Stephenson’s avatars were remarkably prescient, described as having diverse appearances, from hyper-realistic to abstract, and capable of complex, nuanced social interactions, including body language and facial expressions. This vision set the stage for virtual worlds like Second Life and the modern gaming landscape, establishing the avatar as a key component of digital representation.
- The Voice: Conversational AI and Chatbots. Parallel to the development of virtual worlds, researchers were working on teaching machines to talk. The history of AI traces back to the 1950s, with a key milestone being the creation of ELIZA in 1966. ELIZA was the first “chatterbot,” a program that could simulate a conversation with a human using natural language processing (NLP). While simple by today’s standards, ELIZA was the ancestor of all modern chatbots and virtual assistants, providing the foundational technology for the “voice” of an AI avatar.
- The Face: The Generative AI Revolution. The final piece of the puzzle arrived with the “AI boom” of the 2010s and 2020s. This period saw massive leaps in deep learning, driven by powerful graphics processing units (GPUs) and new AI architectures like transformers. This led to the rise of generative AI – AI that can create new, original content. Technologies like Generative Adversarial Networks (GANs) and diffusion models made it possible to generate photorealistic human faces from scratch, while advanced text-to-speech (TTS) models could create incredibly natural-sounding voices. The release of powerful LLMs like GPT-3 in 2020 made the “brain” for these avatars widely accessible.
It was the convergence of these three streams (the virtual vision, the conversational voice and the generative face) that made the modern AI avatar possible.
Milestone |
Year |
Significance |
|---|---|---|
|
The Turing Test Proposed |
1950 |
Alan Turing proposed a test for machine intelligence, laying philosophical groundwork for AI. |
|
Term "AI" Coined |
1955 |
John McCarthy coins the term "Artificial Intelligence" at a Dartmouth workshop. |
|
ELIZA Chatbot Created |
1966 |
The first chatbot, demonstrating early Natural Language Processing. |
|
"Uncanny Valley" Hypothesized |
1970 |
Masahiro Mori describes the unsettling nature of near-perfect human replicas. |
|
Snow Crash Published |
1992 |
Neal Stephenson's novel popularizes the concepts of the "Metaverse" and "avatars". |
|
Deep Learning Breakthrough |
2012 |
Deep learning models achieve breakthrough performance in image recognition, fueling the AI boom. |
|
GANs Introduced |
2014 |
Generative Adversarial Networks are introduced, enabling the creation of hyper-realistic images. |
|
ChatGPT Released |
2022 |
OpenAI's ChatGPT makes powerful Large Language Models widely accessible to the public. |
How AI Avatars Differ From Traditional Avatars and Chatbots
One of the best ways to understand a new technology is to compare it with familiar ones. People often wonder if an AI avatar is simply a fancy chatbot, or the same thing as a video game avatar. The table shows the key differences.
| Feature | Traditional avatar (e.g., game character) | Chatbot (e.g., text-based support) | AI avatar |
|---|---|---|---|
| Visual form | Yes (stylized or realistic) | No (text or voice interface) | Yes (generated, realistic or stylized) |
| Interaction | User-controlled actions | Conversational (text or voice) | Conversational + visual (expressions, gestures) |
| Intelligence | Pre-programmed behavior | Natural language processing (NLP), often rule-based | Generative AI, large language models (LLMs) |
| Autonomy | None (direct user control) | Limited to the conversational flow | Can be programmed for autonomous tasks |
| Primary use | Representation in virtual worlds | Information retrieval, simple tasks | Communication, training, sales and virtual assistance |
An AI avatar combines the visual form of a traditional avatar with the conversational intelligence of a chatbot, and adds generative AI on top of both. Two more comparisons come up often:
- AI avatar vs. virtual assistant (Siri, Alexa): a virtual assistant is typically voice-only. An AI avatar adds a visual, human-like presence, which makes the interaction more personal.
- AI avatar vs. AI agent: an agent is the software that plans and takes actions; the avatar is how that agent appears and speaks to people. Read more about AI avatar agents and assistants.
Types of AI Avatars
AI avatars differ by what they do, how they are created and where they appear. These are the main types.
Presenter (scripted) avatars
A presenter avatar reads a prepared script over slides, PDFs or videos. It is the most common type in business: sales decks, training modules, product explainers and announcements.
Conversational avatars
A conversational avatar answers questions in real time, usually from a knowledge base that the company provides. Typical jobs are customer support, lead qualification and onboarding Q&A.
Agentic avatars
An agentic avatar does more than answer: it takes actions toward a goal, such as booking a meeting or updating a CRM record.
Digital twin avatars
Digital twin avatars are AI avatars that copy a specific real person’s face, voice and manner of speaking, usually built from a short video recording and a voice sample. We call them personal avatars in the rest of this guide. Executives use them for internal updates, experts for courses, and founders for multilingual pitches. In engineering, the same term also describes a live data model of a person or object; read how the two ideas connect in AI avatars in the generative-AI landscape. Personal avatars always require the person’s documented consent (see the checklist below).
Stock avatars
Stock avatars are ready-made characters from a library. This is the fastest way to get started since you don’t have to film anyone.
Game, metaverse and XR avatars
In games and extended reality (XR), avatars represent players or act as AI-driven characters. Some examples:
- Apple Vision Pro creates a Persona, described as “a dynamic, natural representation of your face and hand movements,” for calls and apps.
- Meta’s research team released the Ava-256 Codec Avatars dataset with 256 subjects and more than 200 million images, intended for photorealistic telepresence.
- NVIDIA uses its ACE digital human technologies to build AI teammates in games that react to what the player is doing.
These avatars are mostly consumer technology today, but they show where business avatars are heading: real-time, 3D and present in shared virtual spaces.
Assistive and companion avatars
Assistive and companion avatars support people in daily life: they remind, explain, keep company and help with simple tasks. Early results are encouraging but need care. New York State’s Office for the Aging reported that its AI companion program for older adults achieved a 95% reduction in loneliness among more than 800 participants (self-reported program data). In contrast, a four-week randomized study with 981 participants by MIT Media Lab and OpenAI found that people who voluntarily spent more time with a chatbot had relatively worse outcomes for loneliness and emotional dependence. Regulators are reacting: California’s SB 243 adds safeguards for companion chatbots, including reminders for minors that they are talking to AI.
Across all types, avatars also differ in style. Some aim for photorealism, others are deliberately stylized. More realism is not always better for business content (read how realistic AI avatars should be).
AI Avatar Interactivity Ladder
Most guides classify avatar types. In practice, the more useful question for a business team is: how interactive does this avatar need to be? Each new level of functionality increases the value and volume of preparatory work, as well as the associated risks. Use this model to choose the optimal starting point for each project.
| Level | What the viewer gets | Setup effort | Main risk | KPI to track | Typical use |
|---|---|---|---|---|---|
| 1. Recorded human video | A person on camera | Filming and editing for each version | Slow and costly to update or localize | Views, watch time | Brand stories, executive keynotes |
| 2. Scripted avatar video | An avatar presenting a prepared script | Script preparation, avatar creation and voice cloning | Generic content, mispronounced names | Completion rate, cost per finished minute | Explainers, compliance refreshers, newsletters |
| 3. Interactive avatar presentation | An avatar presenting slides, asks questions, polls, forms and scheduling | Level 2 with interactive elements | Viewers skip interactive steps | Slide-by-slide drop-off, form fills, meetings booked | Sales decks, onboarding, webinars on demand |
| 4. Conversational avatar | Real-time answers from a knowledge base | Level 3 with a curated knowledge base and answer rules | Incorrect or outdated answers | Questions answered, handoffs to humans, chat-to-lead rate | Support, presales Q&A, training help desk |
| 5. Agentic avatar | The avatar takes actions: books meetings, updates records | Level 4 with integrations and permissions | Incorrect action in a connected system | Tasks completed, error rate | Lead qualification and routing, scheduling |
How to use it: start one level lower than you think you need, measure the KPI for that level, and move up when the data shows viewers want more. Level 3 is often a practical starting point: the content stays controlled, and slide-by-slide analytics show exactly who watched what.
How do AI Video Avatars Work?
Most AI avatars operate in similar ways at their core. They use machine learning to convert text into speech and match the avatar’s lip movements, facial expressions and gestures to what it is saying. The process has four steps:
- Input: a script, a presentation or a user’s question, plus a photo or video if you want a personal avatar.
- Face and voice generation: generative models build an animatable face and turn the text into natural-sounding speech.
- Animation and lip-sync: another model matches mouth movements to each sound and adds blinking, nods and small head movements.
- Intelligence layer: for interactive avatars, an LLM processes each question and writes a new answer, which then goes through steps 2 and 3 in real time.
Neural networks trained on thousands of videos of real people do the heavy lifting. These systems have learned to imitate human expressions, speech patterns and body language, which is why today’s AI avatars look so convincingly lifelike.
Read more: How AI avatars work: components, process and key terms and AI avatars in the generative-AI landscape.
How Businesses Use AI Avatars
The use of AI avatars is expanding rapidly. Film production, video games and television are the obvious examples, but it’s more interesting to look at how AI avatars are applied in everyday business work.
Sales
In online sales, AI avatars already serve as presenters, consultants and product guides. They present pitch decks, answer questions about the offer 24/7 and qualify leads before passing them to the sales team. Since there is no filming, adapting a deck for a new segment or market takes minutes.
Marketing and video ad production
Marketing teams use AI avatars to produce explainer videos, product announcements and ad variations without booking a studio. AI is already part of the video workflow: according to Wyzowl’s 2026 survey, 63% of video marketers have used AI video tools to create or edit marketing videos, up from 51% a year earlier, and HubSpot’s State of Marketing reports that 75% of marketers use AI for media production.
The practical gain is version control: one approved script becomes many variants for different segments, languages and placements, and every variant stays on message. Ad platforms now expect disclosure. TikTok, for example, asks advertisers to switch on the label “This ad contains AI-generated content” when an ad is completely generated or significantly modified by AI.
Read more about AI avatars in marketing and AI avatars in e-commerce.
UGC-style content at scale
UGC-style (user-generated-content-style) videos imitate the way a person talks to their phone camera: informal camera angles, direct eye contact, and short scripts. AI avatars make it possible to produce this format in large volumes. For example, TikTok offers advertisers ready-made avatars (digital images of real actors hired for commercial purposes) that speak more than 30 languages.
The line B2B teams must not cross is presenting an avatar as a real customer. The US Federal Trade Commission’s rule on fake reviews covers testimonials by “someone who does not exist, such as AI-generated fake reviews”. to explain product features, share helpful tips, or post announcements, but not to create fictional stories on behalf of customers, and you must label them as AI-generated.
Training, onboarding and education
AI avatars make creating and supporting educational videos much faster while keeping content quality high. They work in schools, higher education and professional training, and they deliver three practical gains:
- Consistent presentation quality. Many instructors haven’t had formal public speaking training, and like all humans they get tired, make mistakes and sometimes misspeak. An AI avatar delivers any script without verbal stumbles, with an appropriate tone for the content.
- Faster production. Creating an AI avatar video is much quicker than recording and editing a human performance. To update a lesson, you change the script and don’t re-record anything.
- 24/7 support. An avatar loaded with the right reference information takes questions from learners and finds the answers when they need them.
Read more: AI avatars for corporate training and AI employee onboarding.
Customer support
Conversational AI avatars change how support teams handle routine requests. They help:
- Handle tier-1 questions. With a well-crafted and regularly updated knowledge base, an AI avatar answers routine questions, so human agents spend their time on complex cases and on improving the knowledge base.
- Provide instant 24/7 support. Avatars respond exactly when the user asks a question. No more “Your request has been received. We will contact you shortly.”
- Keep answers consistent. An AI avatar won’t get confused or forget important information, and it will never get frustrated with demanding customers.
Localization
AI avatars can deliver the same presentation or training video in many languages. With AI dubbing and voice cloning, one recorded message becomes a set of localized versions in multiple languages, without booking voice actors or a studio for each market.
Healthcare and accessibility
In healthcare and accessibility, AI avatars can help people for whom standard video and text formats are ineffective:
- Sign language. Northern, a UK train operator, introduced British Sign Language announcements in which interpreters are filmed signing each station before AI editing software creates the video announcements. The accessibility guidelines WCAG 2.2 require captions for prerecorded video at Level A and include sign language interpretation at Level AAA.
- Voice for people losing speech. Voice-cloning companies now run programs that give people with ALS/MND access to a cloned version of their own voice.
- Patient education. Research on virtual nurses goes back years: in an early small study of hospital patients, 74% said they would prefer to receive discharge instructions from the virtual nurse.
In regulated areas, consult with medical, legal, and accessibility experts before publishing any content with AI avatars.
For language access and compliance in translated content, see AI translation compliance and accessibility.
For more scenarios, see the full guide to AI avatar use cases.
What We Learned From 8 Pitch Avatar Implementations
Standard guidelines can’t explain what happens when real organizations start using AI avatars. These are the published results from our case studies:
| Organization | Use case | Avatar setup | Reported result |
|---|---|---|---|
| Softprom (IT distribution) | SDR onboarding and product training | Training materials localized into 12 languages | "Onboarding time for new SDRs is reduced by 75%" |
| iSi Group (manufacturing | Internal newsletter in 6 countries | Custom cartoon avatar, 6 languages | "72% of employees were happy or more than happy" to get company news this way; production time dropped "from a few days to a couple of hours" |
| Ministry of AI and Digital Development, Kazakhstan | AI press secretary | Conversational avatar | "Over 100 inquiries handled from international journalists", with answers based strictly on the ministry's verified knowledge source |
| Fiona (our own project) | Demand validation and lead capture | AI Chat-Avatar widget | 1,600 sessions, 40% chat-to-lead conversion (leads = waitlist sign-ups), 6 min 45 s average session |
| Projector Creative & Tech Online Institute (online education) | Course localization | Voice cloning and AI dubbing | "Saved up to 90% of time and resources in dubbing lectures" |
| RoboLab (university lab) | Mandatory safety induction | Custom avatar that presents and answers questions | "100% of lab visitors complete a consistent and engaging induction" |
| KRITERO (cybersecurity consultancy) | Security awareness training | Interactive presentations with AI avatar | Qualitative: "noticeably higher engagement" than static PDFs |
| Green Tail (agritech) | Investor pitch | Founder's personal avatar in English, Ukrainian and Japanese | Qualitative: one multilingual pitch for four focus investment markets |
Four lessons repeat across these projects:
- The knowledge base determines answer quality. The Kazakhstan avatar answered only from verified ministry sources, while Fiona improved the results by analyzing real dialogue and refining the prompt.
- Localization is where time savings show first. In traditional production, every new language means a new recording session. With an avatar, it means a new version of the script.
- Realism is optional. iSi Group chose a friendly cartoon character for its newsletter, and employees accepted it.
- Structure drives completion. When the avatar is part of a required process, such as a safety induction, completion stops being the problem and the focus moves to understanding.
Benefits of AI Avatars
As AI avatars find their way into more professions every day, we can identify four main advantages of using video avatars across almost all fields:
Cost-effectiveness. Creating content with an AI avatar is cheaper than traditional video production. You don’t need to pay for camera operators, editors, equipment or studio space. Everything can be done on a single computer using one AI solution, like Pitch Avatar. Just add your text, adjust the settings, and the AI generates a finished video without multiple takes or edits.
Scalability. AI avatars adapt easily to tasks of different sizes. Say you need to adjust a video for audiences who speak other languages and live in different cultural environments. Translating it and switching the avatar’s appearance to something more appropriate takes a few clicks. If you produce videos from the same template every week, you change the text and appearance of your AI avatar in the same way, without a production team or live presenter, and without losing quality.
Personalization. Today’s AI avatar models let you create virtual characters that look and sound like specific people. You can create a personal AI avatar that will communicate with your audience on your behalf, or one that speaks in a style tailored to each audience, down to addressing viewers by name and mentioning their interests and occupation.
Audience engagement. People prefer video to text when they learn about products: in Wyzowl’s 2026 survey, 63% said they would most like to watch a short video, compared with 12% who prefer a text description. AI avatars make that video format affordable for content that used to stay as slides or documents, and interactive avatars add questions, polls and forms that keep viewers involved. Learning quality holds up: a study of 447 participants published in Computers & Education reports no statistically significant difference in test results between AI-generated and human-made training videos, although learners rated the human videos slightly higher. Engagement also depends on trust. An IAB study found that 82% of ad executives believe young consumers feel positive about AI-generated ads, while only 45% of those consumers do, which is one more reason to label content with an AI avatar clearly. More on the psychology behind this in why faces and voices outperform slides.
Thanks to these advantages, AI avatars have become one of the most effective tools for teams that want to automate and improve communication and scale their operations while keeping audience engagement and trust high.
How to Create AI Avatar with Pitch Avatar: Step-by-Step Guide
Let’s look at the process of creating a video avatar using artificial intelligence, using Pitch Avatar’s AI Chat-Avatar as an example:
1. On the My AI Chat-avatars page, click “Add new.”
2. In the appropriate fields, enter your avatar’s name, select a voice and language, then upload a photo or use one from the avatar library. Click “Next.”
3. On the next page, select your chat avatar’s role from the dropdown menu. Pre-configured roles include: Demo role, Support Agent, Sales Consultant, Customer Success Manager, and Coach. The settings for each role can be modified according to your preferences by activating or deactivating buttons on the corresponding panel. You can also customize your role.
This example shows a custom role created using the “Add own role” button.
4. Use the Built-in behavior functionality, which includes:
-
- Intro message: A greeting your AI Avatar plays at the beginning of a session.
- Goodbye message: A friendly farewell, your AI Avatar plays at the end of a session.
- About avatar info: A brief description of your avatar’s functionality and how it helps users.
- Malicious words: Select this parameter to prevent the use of inappropriate or unwanted language during sessions.
5. Click “Edit” to modify your AI Avatar’s preset responses according to your preferences.
6. Use the Built-in instructions functionality, which includes:
-
- Call human to join: Suggestion for the AI Avatar to connect a real person to the session or end the session when it can’t answer a question.
- Schedule meeting: Helps users book a convenient meeting time.
- Change language: Identifies the user’s language and switches accordingly.
- Pause mode: Pauses the session when users say “stop” or similar commands.
7. Click “Edit” to modify your AI Avatar’s behavior according to your preferences.
8. Use the Response control functionality, which includes:
-
- Pricing request: Control how your AI Avatar discusses prices. Add your price list or limit price discussions.
- Irrelevant request: Set how your avatar responds to questions outside its knowledge base.
- Need more info: Configure how your avatar asks for clarification when it doesn’t understand a request.
9. Click “Edit” to modify your AI Avatar’s behavior according to your preferences.
Feel free to guide your Chat-avatar by describing your target audience and providing clear instructions on how it should respond in the text box. For example:
When someone asks you: How can I contact Softprom’s main office?
You MUST answer:
You can reach Softprom’s main office via email at info@softprom.com, by phone at +43 1 402 57 39 (Austria), or through our contact form. For country-specific details, visit softprom.com/contacts. Our team is here to help during business hours.
10. Pitch content allows you to give your AI Avatar a presentation to show. You can either upload a new presentation or select one you’ve already uploaded.
11. Use the Knowledge source functionality. This trains your AI Avatar on what it needs to know for communication. Upload information to your avatar’s Knowledge base as files or links, and it will search them for answers to viewers’ and users’ questions.
Click “Edit” to modify your AI Avatar’s behavior according to your preferences.
Testing and finalizing
Test
Click Test to try your avatar. See how it talks and answers questions.
Create
If you like how it works, go back and click Create.
Share
Generate a shareable link by clicking Create, and send it to others.
In Pitch Avatar, you can add an AI avatar presenter to your slides, PDFs or videos, or create an AI Chat-Avatar with a role (for example, Support Agent or Sales Consultant), a knowledge base and built-in actions such as scheduling a meeting or inviting a human to join the session. On average, creating an AI Chat-Avatar takes 5–15 minutes and doesn’t require special technical skills. For the full walkthrough, see the AI Chat Avatar guide in our knowledge base.
Challenges, Ethics and Disclosure of AI Avatars
The development of AI technologies, as often happens with progress, has created new legal and ethical questions. Here are the main ones:
Deepfake content. Since AI avatars can convincingly imitate real people, the technology opens up possibilities for disinformation and misuse. It replaces reality in a way that can violate personal rights, including the right to one’s image and reputation. Such content becomes a legal problem when it is created and published without the consent of the person whose image is used. A person’s death doesn’t make their image and voice free material either; a deepfake might hurt the feelings of their relatives, friends and community. Using your own image and voice for an AI avatar, with your consent, has nothing to do with deepfakes.
Copyright. AI avatar technologies can bring to life characters created by artists, animators, filmmakers and other creative professionals. Such use may violate the copyright on these images, and the reaction of fans of the original works is worth considering as well.
Authenticity and the law. Many people want to know who they’re seeing on screen: a real person or an AI avatar. This is becoming a legal requirement. Under Article 50 of the EU AI Act, deployers of AI systems that generate deepfake image, audio or video content “shall disclose that the content has been artificially generated or manipulated”, and the European Commission states that the transparency rules come into effect in August 2026. Platforms apply their own rules too: Meta requires a disclosure label on photorealistic video or realistic-sounding audio that was digitally created or altered.
Consent and disclosure checklist
Use this checklist before you publish any avatar content:
- Written consent for every personal avatar and cloned voice: what the avatar may be used for, in which channels and languages, for how long, and how the person can withdraw consent.
- A plan for when people leave: decide in advance what happens to an employee’s personal avatar and voice when they leave the company.
- Clear labeling: tell viewers they are watching an AI avatar, in the video and in the description or ad settings.
- No fake customers: never present an avatar as a real customer, reviewer or witness.
- Licensed characters only: check the rights for stock avatars, voices and any character based on someone else’s work.
- A human owner for the knowledge base: someone is responsible for keeping a conversational avatar’s answers accurate and updated.
Read more: AI video ethics.
Future Trends: What's Next for AI Video Avatars?
It’s completely obvious that the technology for creating AI Avatars is only at the beginning of its journey and will continue to actively improve. The main directions for the development of AI-based video avatars include:
- Increased realism. Each year, AI Avatars will become more diverse, and their behavior more complex. The smoothness and naturalness of speech, the variety and appropriateness of facial expressions and gestures, interaction with other virtual objects and characters, the accuracy of reactions, and the depth of “improvisations” – all this will make the behavior of near-future AI Avatars practically indistinguishable from human behavior. (Read more about realistic AI Avatars)
- Free-form real-time interaction with people. Most AI Avatar models will eventually be configured, follow commands, learn, and so on, without a system of templates and settings. You’ll simply need to write or voice a requirement or task, and the model will perform it in real-time. In simple terms, to change the appearance, behavior, and skills of an AI Avatar, you’ll just need to voice your wishes or type them in free form. The same, of course, applies to interaction with viewers. Moreover, AI video avatars will learn to automatically adjust their communication style and even appearance to match the person they are talking to.
- AR/VR integration. Logically, AI Avatars will be used more actively as virtual and augmented reality technologies become more widely implemented. There is a belief that they will essentially become the main population of virtual space, acting as guides, assistants, consultants, online salespeople, and personal assistants. At the same time, the spread of AR software and devices will allow for more active use of AI Avatars outside the virtual world.
- The Rise of Agentic AI: Both Gartner and Forrester have identified “Agentic AI” as a top strategic technology trend for 2025. This represents a monumental shift. An agentic AI avatar is autonomous. It can be given a goal – such as “schedule a sales meeting” or “resolve this customer’s support ticket” – and it can then reason, plan, and execute the necessary steps to achieve that goal without human intervention. This involves interacting with other software, like calendars and CRMs. Gartner predicts that by 2028, at least 15% of everyday business decisions will be made autonomously by AI agents. This transforms the avatar from a tool into a digital colleague.
- Digital Twins and Hyper-Personalization: An AI avatar can serve as the interactive, conversational interface for a person’s “digital twin” – a comprehensive, dynamic data model of an individual. This digital twin could contain a person’s knowledge, work history, and even communication style. An executive could have a digital twin that sits in on meetings they can’t attend, or an expert could have one that fields questions from junior colleagues. This enables a level of hyper-personalization and delegation previously unimaginable.
- Interoperability and the Metaverse: As the concept of the metaverse (a persistent, shared virtual space) continues to develop, avatars will be our primary mode of existence within it. A key future trend is interoperability: the ability to take your unique AI avatar from one virtual platform to another, maintaining a consistent digital identity across different worlds and applications.
The capabilities of AI avatars will grow together with AI technology. In the foreseeable future, we can expect multifunctional AI avatars that work with people as universal assistants, in video, in chat and in virtual spaces.
See an AI avatar presenter on your own slides. Book a demo or create your account.
Frequently Asked Questions
