Create Scalable, Cost-Effective AI Videos for Training & Coaching

AI-generated video is rapidly changing the way training and coaching content is produced across industries. From corporate learning and development to fitness coaching and education, more companies are using AI avatars and synthetic voices to produce video faster and at lower cost.

Advances in generative AI will make it possible to use lifelike virtual presenters, add automated voiceovers in multiple languages, and even create interactive coaching tools.

This report provides a complete overview of the latest trends, top platforms, production implications, market adoption, and key challenges as AI video becomes a widely used tool in training, e-learning, and coaching.

Current Trends in AI-Generated Training and Coaching Videos

AI video generation for training is evolving with several notable trends:

• AI Avatars as Virtual Presenters: Highly realistic digital avatars are now being used as on-screen instructors and coaches, removing the need for human actors and film crews. These avatars look photorealistic and can copy natural facial expressions and gestures, helping the training feel more human. Platforms like Synthesia, HeyGen, and others offer hundreds of avatar options, covering different ages, genders, and ethnicities. Users simply choose an avatar to read their script. This technology allows organizations to create personalized, lifelike, and dynamic videos in just minutes and at scale—making expensive video shoots and hiring on-screen talent less necessary. Studies show that, when done well, AI presenters can be just as effective as real ones. For example, research from the University of South Florida found no major difference in how much information people remembered, how engaged they felt, or how much they trusted the content—whether it came from a human speaker or a highly realistic AI avatar. However, there is one challenge: the uncanny valley. If an avatar looks almost human but not quite right, it can make viewers feel uncomfortable. The goal is to reach a level of realism that feels natural and authentic, without becoming creepy. Acceptance of AI avatars also depends on the region. They are widely used in Asia, such as AI news anchors in China and South Korea. In contrast, audiences in Western countries have been more cautious, though attitudes are starting to shift as the technology improves.
• Advances in Voice Synthesis: Modern text-to-speech (TTS) voices are much more natural and expressive than they were just a few years ago. In AI-generated training videos, these voices are combined with digital avatars to create lifelike presentations. The synthesized voiceovers can capture different tones, accents, and even emotions. Creators can choose from large voice libraries. For example, Vyond’s avatar platform offers over 2,700 voices in more than 70 languages, with options to adjust tone, speed, and pitch for more realistic delivery. These AI voices are often hard to tell apart from real human narration and can be adapted to match local dialects. Advanced providers like ElevenLabs—which integrates with platforms such as Synthesia—offer nearly human-like expressiveness and even voice cloning. This allows companies to replicate the voice of a CEO or a familiar trainer for consistent messaging across all training content. When high-quality voice synthesis is paired with accurate lip-sync (so the avatar’s mouth movements match the spoken words), the result is believable multilingual videos. The AI can translate content and deliver it with a natural-sounding voice and proper lip movement in the target language. This makes it much easier and more affordable to produce training materials in multiple languages.
• Personalization at Scale: A key trend in 2024–2025 is the use of AI to create personalized training videos for individuals or specific audience groups. Instead of using the same video for everyone, AI tools can add personal touches—such as the viewer’s name, job title, or other details—directly into the narration or on-screen text. Platforms like Synthesia now offer “bulk personalization” features. This allows users to upload a spreadsheet with personal information and automatically generate hundreds of unique video versions without manual editing. In addition, Synthesia’s API lets companies automate video creation from templates. This is especially useful for making things like personalized onboarding videos for new employees or custom coaching videos for each sales representative. This level of personalization can boost engagement by making learners feel the content is speaking directly to them. In employee training, it might address each person by name and focus on their department; in education, a teacher could create slightly different explainer videos tailored to each student’s proficiency level. Such video personalization at scale was impractical before AI but is becoming straightforward with these tools.
• Localization and Multilingual Training: With teams and customers spread across the globe, more organizations are turning to AI video to localize training content into multiple languages. AI-generated video allows companies to create one master version of a training video and then automatically add voiceovers and subtitles in many target languages. In 2024, Synthesia reported that over one million people were using its platform to create content in more than 130 languages. The company also launched a one-click translation feature that instantly produces translated videos with synchronized voice and lip movements. Similarly, HeyGen offers translation into over 175 languages and dialects, while keeping the speaker’s natural voice and accurate lip sync. This means a training video originally recorded in English can now be delivered to employees in Latin America, Europe, and Asia—each in their native language—within minutes. In the past, this process would have required re-recording with multilingual speakers or using dubbing services. Multilingual AI video greatly expands the reach and accessibility of training content. It also helps maintain consistent messaging across global teams. For example, Heineken uses Synthesia to train over 90,000 employees in 170 countries. With Synthesia’s one-click translation feature, they can quickly localize videos to reach everyone in their preferred language. This level of localization—combined with diverse avatar options—makes training more inclusive and culturally relevant.
• Interactive & Adaptive Video Content: The newest development in AI video is making it interactive—turning passive watching into an active coaching experience. In 2025, we’re seeing the rise of AI avatars that can interact with users in real time, powered by large language models for conversation. This goes beyond traditional video, allowing the avatar to answer questions or hold a simulated dialogue with the viewer. For example, VirtualSpeech has introduced AI avatars that let learners practice soft skills like job interviews or sales pitches through role-play. These avatars can respond naturally to what the user says, thanks to advanced natural language processing, and they even give real-time feedback—such as analyzing speaking pace or emotional tone. This trend effectively creates AI coaches or tutors – sometimes called AI agents – that personalize the learning experience through interaction. A trainee could practice a customer support call with an AI character that listens and responds like a real customer, or a language student could have a conversation with an AI tutor avatar. The content can branch based on learner responses, making it a two-way experience rather than a fixed video. While still emerging, such interactivity is poised to make coaching simulations more accessible at scale. Even the standard video platforms are starting to explore interactivity – Synthesia’s roadmap, for example, envisions avatars that “can interact with users” and be placed into different virtual environments to demonstrate tasks. This points toward training videos that double as virtual reality-style trainers or intelligent assistants, adapting in real time to each learner.

Trend	Description	Example
AI Avatars	Lifelike virtual presenters replace human actors in videos. Avatars mimic facial expressions and gestures, creating an engaging human-like presence.	Digital trainer avatars deliver HR onboarding videos, achieving similar viewer trust and retention as real instructors.
Voice Synthesis	Natural-sounding AI voices narrate scripts in multiple languages and tones. Can clone voices for consistency and sync speech to avatar lips.	Over 2,700 voice options in 70+ languages let creators give each avatar a fitting voice, with accurate lip-sync in each language.
Personalization	Automated tools create hundreds of video variants tailored to individuals (name, role, etc.) or groups, using template scripts and data inputs.	A sales manager generates personalized coaching videos for each rep by uploading a CSV of names and performance tips, yielding unique video messages for all.
Localization	Rapid translation of videos into many languages with AI-dubbed voiceovers and subtitles, extending content to global audiences with minimal effort.	Heineken localizes training videos for 90k employees across 170 countries “in minutes” via one-click AI translation, each with native-language narration.
Interactivity	AI-driven avatars can engage in two-way interactions, responding to user questions or simulating real conversations for practice. Videos become dynamic coaching tools.	A virtual AI interviewer avatar conducts mock interviews with job candidates, listening and providing on-the-spot feedback on their answers.

Table 1: Key Trends in AI-Generated Training Videos (2024–25)

Top Platforms and Tools Shaping AI Video Production

Several AI video generation platforms have emerged or grown significantly in 2024–2025, offering easy-to-use tools for creating training and coaching videos. Below is an overview of some leading platforms and what they can do:

• Synthesia: Synthesia is widely seen as a leader in AI video creation. It offers an easy-to-use, browser-based studio where users can create videos with talking AI avatars. As of 2025, the platform includes over 230 avatars and supports more than 140 languages and accents. Users simply type a script, and the avatar delivers it on screen. Synthesia also includes more than 60 video templates for common use cases, such as training, onboarding, and internal communication. Its API allows for automated video generation, making it ideal for companies that need to create content at scale. The platform is especially popular in corporate learning and development (L&D), with most companies using it for training videos and other eLearning content. One of Synthesia’s main strengths is speed—users can produce professional videos in minutes, without needing video production experience. Many learning teams report cutting production time by 62%, saving about eight days per video compared to traditional methods. Synthesia also offers advanced features for large teams, such as collaborative workspaces, closed captions, one-click translation, and voice cloning (including the option to clone your own voice). These tools make it easy for companies to scale their video creation while maintaining quality and consistency. The platform’s strong performance is shown by its wide adoption. Synthesia is used by over 50,000 companies—including major brands like Amazon, Zoom, and Reuters—and by more than 60% of Fortune 100 firms. In early 2025, the company raised $180 million in Series D funding, reaching a valuation of $2.1 billion to further improve avatar quality and interactivity. With over one million users, Synthesia has become a central platform in the AI video space, especially for corporate training and communication.
• HeyGen: HeyGen is another leading AI video generator, known for its strong multilingual and personalization features. The platform offers over 500 avatars, including photorealistic presenters and cartoon-style characters, and supports text-to-video creation in more than 70 languages and 175 dialects. This makes it a powerful tool for fine-tuned localization. HeyGen’s goal is to make “visual storytelling accessible to all businesses,” from small companies to large enterprises. In real-world use, it’s popular for creating marketing videos, customer updates, training content, and internal communications. One of HeyGen’s key strengths is AI-powered localization. The platform can automatically translate a video into multiple languages while keeping the original speaker’s voice and matching lip movements. For example, a training video of a CEO speaking English can be instantly delivered in Spanish or Mandarin with the same voice and synced mouth movements. HeyGen also supports personalization at scale. Users can insert tokens like names or job titles into scripts, and the system generates customized videos for each viewer. A recent feature, now in beta, is Interactive Avatars, which can be connected to chatbots or APIs to allow two-way interaction between the avatar and the user. HeyGen experienced fast growth in 2024. Its annual recurring revenue jumped from $1 million to $35 million in just one year, and it raised $60 million in Series A funding, reaching a valuation of around $500 million. It also holds a 4.8/5 rating on G2 and was ranked the #1 AI video tool of 2025. Companies are attracted to HeyGen because it “lets users create, localize, and personalize studio-quality videos without needing a camera, actors, or crew.” This significantly reduces the cost and time of video production, which can often reach $1,000 per finished minute using traditional methods. Overall, HeyGen is becoming a top choice for organizations that need fast, multilingual video content or want to explore interactive avatar technology for training and support tools.
• DeepBrain AI. DeepBrain AI offers the AI Studios platform, which focuses on creating ultra-realistic AI avatars. These avatars are widely used in corporate training, news broadcasting, and interactive kiosks. Built from real actors, DeepBrain’s avatars are known for their highly detailed facial features and natural-sounding voice quality. A standout feature is the ability to create a custom avatar of a specific person using just a few minutes of video. For example, a company can turn their real instructor or CEO into a digital avatar. Once created, new videos can be generated simply by entering a script for that avatar to speak. This makes it possible to reuse the same familiar face for training videos, customer service roles, or virtual presenters—without needing to film again. DeepBrain supports dozens of languages and includes a user-friendly studio interface with options for text input, voice selection, and background settings. In corporate L&D, the platform is often chosen for explainer videos, tutorials, and compliance training that require a more formal or human-like presence. It has been named “best for corporate & explainer videos” in independent reviews. The platform is especially popular in Asia, where companies have used it to automate employee training and customer education. DeepBrain also works with partners to integrate its avatar technology into other systems, such as language learning apps or virtual reality training tools. While it may not have as large a user base as Synthesia or HeyGen, DeepBrain AI continues to grow and innovate. Recent developments include 3D realistic avatars and AI that can hold real-time conversations. Its focus on hyper-realism attracts organizations looking for digital presenters that closely resemble real people. As AI video becomes more common, DeepBrain remains a key player—especially in the Asian market and among media and education companies seeking highly lifelike AI humans.
• Other Notable Tools: Beyond the platforms mentioned above, several other AI video tools have emerged by 2025, offering unique features for training and coaching use cases:
  • D-ID: Known for its Creative Reality™ platform, which can animate any photo of a face with synced voice narration. Users can create talking head videos using their own portrait. Originally focused on consumer applications, D-ID added an API and e-learning integrations in 2024. It supports voiceovers in over 100 languages and is valued for its flexibility—users can upload their own avatar images. However, the avatars are 2D photo animations, which are less dynamic than 3D models.
  • Colossyan: A newer competitor focused on speed and simplicity. In 2024, it launched an “Instant Avatar” feature that lets users create personal avatars using a short selfie video. These avatars can present in multiple languages. Colossyan targets educators and instructional designers, offering affordable plans and a growing library of templates for common training topics. It’s praised for fast rendering and frequent feature updates.
  • Rephrase.ai: An India-based startup offering large-scale, API-driven video personalization. Rephrase.ai is used for marketing and training videos, where personalized elements—like names or product info—can be added for thousands of viewers. It’s known for “video mail merge” campaigns and is often used to send out custom compliance training or tailored video learning paths.
  • Hour One: Focuses on creating virtual human characters for training, retail, and education. Businesses can build custom avatars and produce high volumes of content. Hour One has worked with language-learning companies to develop virtual teachers who speak multiple languages. Its key strength is the professional quality of its avatars, developed using actor likeness rights and studio-grade recordings.
  • Vyond: Traditionally known for animated explainer videos, Vyond introduced an AI Avatar feature in mid-2024. These photorealistic avatars can be placed into animated scenes, combining real-looking presenters with screen recordings or graphics—ideal for software training and scenario-based learning. This move highlights the broader trend: even established animation tools are adopting AI avatar technology to meet growing demand.

Platform	Avatars & Voices	Key Features	Primary Use Cases
Synthesia (UK)	230+ realistic avatars; 140+ languages (uses advanced TTS).	Easy text-to-video studio; templates; one-click translation; team collaboration; API for bulk creation.	Corporate training, e-learning, onboarding, internal comms. Widely used by enterprises (60k+ businesses).
HeyGen (US/CN)	500+ avatars; voices in 70+ languages (175 dialects); voice cloning for localization.	Emphasis on localization (auto-dubbing videos to other languages with lip-sync); personalization at scale; some interactive avatar capabilities.	Marketing content, global corporate training, L&D, sales enablement. Strong growth (ARR $35M in 2024).
DeepBrain AI (KR)	Dozens of hyper-real avatars (plus custom avatars from real people); multi-lingual voices.	Ultra-realistic video output; custom avatar creation service; can integrate into kiosks or live systems.	Corporate explainer videos, how-tos, customer service avatars, news/broadcast. Popular in Asia and with media firms.
D-ID (IL)	Unlimited avatars from any image; voices in 100+ languages.	Photo-to-video animation; API integration; live talking avatars via webcam input.	Personalized messages, education clips, marketing. Flexible but less 3D realism (animates 2D photos).
Colossyan (US)	30+ avatars; supports instant self-avatar creation; many languages via TTS.	Simple UI for rapid video creation; affordable plans; templates for training topics.	Training for SMBs, educators making lesson videos, quick how-to content.
Others	Various avatar and voice options.	Specialize in specific niches like mass personalization or virtual agents.	Rephrase.ai for personalized outreach training, Hour One for virtual instructors/characters.

Table 2: Leading AI Video Generation Platforms (2024–25)

How AI Impacts Production Time, Costs, and Learner Engagement

The rise of AI-generated video in training and coaching is mainly driven by major gains in production speed and cost savings, along with the ability to make content more accessible and engaging for learners:

• Dramatically Faster Production: AI video generators have accelerated the video creation process from weeks to hours. Learning and development teams no longer need to book film crews, set up cameras, record multiple takes, or spend days editing. Instead, a training manager can write a script-or reuse an existing document or slide deck-and produce a polished video the same day. A 2023 survey of L&D professionals found that modern AI tools reduce the average time to produce training videos by 62%, saving about eight days per video compared to traditional methods. This speed is especially important in fast-moving industries where training materials often need to be updated, such as for software tutorials or compliance changes. For example, if a policy changes, an AI avatar video can be updated by simply editing the script and regenerating the video. As one Heineken user put it, “You can update the script and have a new version of the video in minutes. This ability to quickly revise and publish content means that training stays up to date, and organizations can respond more quickly to change, making their learning programs more agile and effective.
• Lower Costs and Resource Requirements: AI-generated videos are much cheaper to produce because they remove many expensive steps—such as hiring actors, videographers, booking studios, and using professional equipment. While costs vary, traditional video production can cost around $1,000 per finished minute when you include planning, crew, talent, and editing. In comparison, AI video platforms usually charge a small monthly subscription or per-video fee. For example, Synthesia offers an entry-level plan for about $30 per month for 10 videos, and even enterprise-level plans are still far less expensive than live-action production. Heineken’s L&D team noted that switching to AI avatars “dramatically reduced the time and cost of video production.” For organizations that need to produce a high volume of training content, the savings are especially attractive. With the same budget that used to cover one professionally filmed video, companies can now create dozens of AI-generated ones. This change also makes video creation more accessible to smaller businesses, nonprofits, and educators who previously couldn’t afford it. Even a small HR team can now build learning content without hiring a production crew. All that’s needed is a computer—no cameras, studios, or advanced skills required. One person can create full training videos on their own. This shift is helping democratize video production. In one survey, 16% of respondents said they had never made training videos before using AI tools, mostly because it was too expensive, time-consuming, or required special skills. Now, those same professionals are creating content with ease—showing how AI is opening the door for more people to produce high-quality learning materials.
• Enhanced Scalability and Localization: AI-generated videos are easily scalable – once a script is ready, generating one video or a thousand variants is mainly a matter of computing time. This has transformed scalability in two ways: quantity and localization. In terms of quantity, companies can vastly increase their training video output (covering more topics or more personalized versions) since the marginal effort for additional videos is low. In terms of localization, as discussed, the ability to clone videos into different languages means a single master training module can effectively turn into 5 or 10 modules for different regions with negligible extra cost. This localization at scale was rarely achievable with conventional means, as it would require multiple re-shoots with translators or dubbing studios. Now a global company can ensure all employees receive the same quality of training in their preferred language. This not only improves access and comprehension but also saves costs that would have gone into hiring multilingual trainers or translators. For example, appliance-maker Electrolux used Synthesia to create training in 30+ languages, reaching 15,000 partners and employees across Europe with consistent messaging. The reach and consistency of training improve when AI can handle the heavy lifting of translation and content customization.
• Improved Engagement and Learning Effectiveness: Video is naturally engaging, and adding AI avatars and multimedia elements can make learning content even more interesting. L&D professionals widely agree that video is more effective than text-only materials. In one survey, 97% said video helps employees retain information better and is more effective than written documents. AI avatars add to this by providing a face and voice, which helps create an emotional connection with learners. People are naturally drawn to faces and social cues. One analysis found that “facial expressions activate brain regions for social interaction, making content more memorable.” Whether the face is real or digital, our brains still respond—so a well-designed AI coach can keep attention much like a human trainer. AI video tools also allow creators to add helpful visuals, such as slides or screen recordings, to support different learning styles—both visual and auditory. Some platforms even include interactive features like quizzes or clickable prompts during or after the video to further boost engagement. Early results show that these AI-created videos are effective. For example, Spirit Airlines reported a 76% drop in certain support requests after using AI video to explain employee benefits. This shows that the videos successfully helped staff find answers on their own. The rise of microlearning—short, focused video modules—also fits well with AI video tools, which make it easy to create many quick lessons. Personalization adds even more value: when a video is tailored to someone’s name, role, or department, they are more likely to pay attention. Looking ahead, interactive avatars that can respond to learners in real time may increase engagement even further—turning training into a two-way conversation rather than just a lecture.
• Increased Accessibility: AI-generated videos also improve accessibility in a broader way. These videos often include automatic captions, can be paused or replayed anytime, and are available on-demand. This is especially helpful for learners who prefer to study at their own pace—which, according to surveys, is the majority. Training videos created with AI can be accessed from any device, at any time, giving learners more flexibility. For organizations, having a library of AI-generated videos means employees can quickly find short explainers on specific topics without needing to read long manuals or attend scheduled workshops. This supports just-in-time learning, where employees can learn exactly what they need, when they need it. AI avatars also ensure consistency. Every viewer gets the same clear and structured explanation, avoiding the differences that can come from using multiple human instructors. Some also argue that AI avatars offer a non-judgmental learning experience. For sensitive topics, an AI avatar can deliver the message in a neutral and consistent tone, whereas human presenters may unintentionally show bias or variation in delivery. That said, human presenters can bring charisma and personal connection, which some learners find more engaging. In many cases, the best approach may be to combine both—using AI for clarity and scale, and human-led content for warmth and relatability.

Market Adoption: How Industries Are Embracing AI Video Solutions

The reception to AI-generated video in training and coaching has been largely positive in the corporate world, though it comes with some caution. Adoption rates increased rapidly throughout 2024. Many Fortune 500 companies have already tested or fully added AI video into their L&D strategies. Synthesia’s user base reached 60,000 businesses and over 1 million users by the end of 2024, showing how quickly this technology is being adopted. Notably, more than “60% of the Fortune 100” now use Synthesia, which suggests that many of the world’s biggest companies see clear value in using AI video for internal communications and employee training. Large global brands like SAP, Siemens, IKEA, Amazon, and Google are among those using these tools. In the education sector, adoption is still early but growing. Universities and e-learning providers are starting to use AI avatars to create lecture videos and language lessons more efficiently—usually as a way to support human teaching, not replace it. By the end of 2024, a number of ed-tech startups had also launched AI-powered tutors and course creation tools, showing strong interest in this space and pointing to a growing market.

The market for AI-generated training video is becoming increasingly competitive, showing just how much opportunity this space holds. In addition to the major platforms already discussed, big tech companies are starting to get involved. Microsoft, for example, has demonstrated its own AI presenter feature in PowerPoint, called “PowerPoint Presenter,” which uses an animated avatar. Adobe is also adding AI voice and avatar technology into its Creative Cloud suite. Investors are showing strong confidence in this space. In 2024, Synthesia raised $180 million and HeyGen secured $60 million in funding. These large investments suggest that AI video tools are expected to play a major role in enterprise learning and development. Analysts describe AI video and avatar platforms as one of the fastest-growing areas of generative AI. Some projections say the market could reach several billion dollars within just a few years. By 2025, AI video has become a regular topic at industry events. Conferences focused on training, HR, and ed-tech now often include sessions or demos on AI avatars and video learning systems—clear signs that the technology is moving into the mainstream.

Workforce and Industry Reactions: Inside organizations, the response to AI-generated video has been mostly positive, though not without mixed feelings. L&D teams especially value how AI tools help them create more content while staying within tight budgets. A common challenge in 2023 was simply not having enough time or resources to produce training videos—AI tools help solve that problem. In many cases, AI video acts as a force multiplier for L&D teams, not a replacement. Instructors and subject matter experts can focus on writing strong scripts, while the AI takes care of the video production. This allows them to scale their efforts and reach more learners. Some companies have gone a step further by setting up in-house AI video “studios,” where employees from any department can create training videos with guidance from the L&D team. This decentralized approach to content creation helps teams move faster while still maintaining quality.

However, there are also concerns and some resistance to using AI-generated videos. One common worry is that replacing human trainers with avatars might reduce the sense of human connection or make the training feel less authentic. While studies show that well-designed avatars can be just as engaging as human presenters, the effectiveness often depends on the context. In areas like executive leadership coaching or personal development, some experts argue that the human presence—even through a Zoom call—offers empathy and spontaneity that a pre-recorded avatar cannot fully provide. Learners may be less likely to ask questions or could miss the extra insights a live instructor might share during a conversation. To deal with this, many organizations are taking a blended learning approach. They use AI videos for delivering core or basic information, and then schedule live Q&A sessions or practice activities with human trainers to keep the personal and interactive side of learning intact.

Interestingly, employee feedback on AI-generated training videos is generally neutral to positive—especially when the content is clear and useful. If the avatar is high quality, many viewers may not even realize the presenter isn’t a real person at first. To maintain transparency, it’s becoming common for companies to include a note such as “(This video was created with AI)” either at the beginning of the video or in the description. As of 2024, there are no global laws requiring this kind of disclosure, but many see it as a best practice to build trust with viewers. In public-facing content, like coaching videos on YouTube, platforms have started requiring creators to label realistic AI-generated videos. This shows that industry standards are shifting toward greater transparency around AI use.

Challenges and Criticisms of AI-Powered Training Video Creation

Despite its advantages, AI-generated video does present several challenges and has faced criticisms that are important to consider:

• Authenticity and “Human Touch”: A common question is whether AI-generated coaches can truly match the authenticity of real human trainers. While avatars can look and sound very realistic, some learners say that knowing the video is AI-made can feel a bit impersonal or strange at first. Trust plays a big role—especially in sensitive topics like diversity training or mental health sessions. In these cases, employees may prefer seeing a real leader or expert on camera, as it shows the company is personally committed to the message. This ties into the uncanny valley effect, where an avatar that looks almost human—but not quite right—can feel unsettling and reduce the message’s impact. To avoid this, companies often use high-quality avatars and voices, or even choose slightly animated styles that don’t try to appear fully real. Cultural preferences also matter. In some regions, people may be less familiar with AI avatars and more hesitant to accept them as credible presenters. Still, research shows that when done well, AI videos can perform as well as live videos. Some studies show that viewers engage equally with both formats. To keep a sense of human connection, many programs use a blended approach—using AI videos to deliver the main content, while keeping real people involved for live discussions, Q&A sessions, or mentoring. This combination helps balance efficiency with authenticity.
• Content Quality and Accuracy: When AI is used to generate content—especially for writing scripts or answering questions in interactive formats—there is a risk of inaccurate or misleading information. Large Language Models can sometimes “provide incorrect or inaccurate information” if not carefully reviewed. In a training setting, this can be a serious issue—for example, an AI-written safety training video that contains a factual mistake could be harmful. To reduce this risk, most platforms ask users to supply their own scripts, with the AI focused mainly on rendering the video. However, as more tools now offer auto-generated content (where users enter a topic and receive a full script and video), it’s important for organizations to carefully review and edit AI-generated material to make sure the information is accurate. Another challenge is that AI avatars follow the script exactly and lack spontaneous expression. If the script is poorly written or lacks energy, the avatar will sound flat or robotic. Human trainers, by contrast, often tell stories, use natural emphasis, and adjust their tone based on how learners react—something a pre-recorded AI video cannot do. To make AI videos more engaging, content creators should focus on writing clear, interesting scripts and consider using shorter segments to help hold learners’ attention.
• Ethical and Regulatory Issues: The rise of realistic AI-generated people has sparked ethical discussions and the start of new regulations. One key issue is disclosure—viewers have the right to know whether they are watching AI-generated content or real footage. Regulators are beginning to respond. For example, California passed an AI Transparency Law that will require certain AI-generated media to include watermarks or disclosure labels by 2026. In internal training settings, this may not be legally required, but for external coaching or public-facing content, disclosure is becoming necessary to avoid misleading audiences. Another concern is the misuse of deepfake technology. The same tools used to create harmless AI avatars for training could also be used to produce fake videos of real people saying things they never actually said. This risk has made many people cautious about AI-generated content. To address these concerns, companies like Synthesia have put clear policies in place. They require informed consent to create a custom avatar of a real person and are part of the Content Authenticity Initiative, which promotes watermarking to distinguish authentic content from manipulated media. It is both a legal and ethical requirement to get permission before cloning someone’s face or voice. Cases of voice cloning scams have highlighted the need for stronger protections and more awareness around consent. For most corporate users who stick to stock avatars or use approved custom avatars, this risk is lower. Still, brand reputation is important. Companies must use AI video tools responsibly. For example, using an avatar to represent a real executive without telling viewers it’s AI-generated could damage trust.
• Job Impacts and Skills Shift: Another common concern is the possible impact of AI video on professionals in video production and training. If AI can create videos in just minutes, what happens to videographers, editors, voice-over artists, or on-screen trainers? In the short term, demand for live, high-quality video hasn’t disappeared—some projects still need the human touch. However, routine work like basic training videos or standard voice-over jobs may decline. This shift means that professionals will need to adapt. Video creators might focus more on writing strong scripts for avatars or take on creative tasks that AI can’t handle. Trainers may move into roles where they design learning experiences or guide live sessions, instead of appearing in every video themselves. While AI brings efficiency, it also creates new job opportunities. Titles like “avatar content director” or “AI curriculum designer” are starting to appear. The overall effect on jobs is still uncertain, but it’s a topic being actively discussed in the L&D field. Many professionals see AI video as a tool that supports, not replaces, human trainers—helping them reach more people and spend less time on repetitive tasks. Still, open communication with teams is essential. Explaining how and why AI is being used can help avoid misunderstandings or morale issues.
• Technical Limitations: Despite fast progress, AI-generated videos still have some limitations in 2024–2025. Most avatars only appear from the chest or waist up and can do simple gestures, but they aren’t yet able to perform full-body actions or physical demonstrations. For example, teaching a fitness class with full movements still requires real video footage, CGI, or motion capture—things current AI avatar tools don’t support. In these cases, avatars are often used as narrators over real exercise clips or animated visuals, rather than replacing human instructors. Creating longer videos (such as 15–20 minutes) can also take more time to render and may cost more, so many users prefer to stick to shorter training modules. Another issue is variety—if the same default avatar is used repeatedly, learners may begin to notice and lose interest (“It’s that same AI presenter again”). To avoid this, creators are encouraged to switch between different avatars and add other visuals to keep the content fresh. While AI voice technology is highly advanced, it can still mispronounce uncommon words, names, or technical terms. In those cases, script writers may need to adjust the spelling phonetically to get the correct pronunciation. These are minor challenges overall, and most are already improving as the technology continues to evolve.