{"id":7110,"date":"2026-05-21T12:24:53","date_gmt":"2026-05-21T19:24:53","guid":{"rendered":"https:\/\/www.visla.us\/blog\/?p=7110"},"modified":"2026-05-21T14:13:48","modified_gmt":"2026-05-21T21:13:48","slug":"what-gemini-omni-could-mean-for-the-future-of-veo-and-business-video-creation","status":"publish","type":"post","link":"https:\/\/www.visla.us\/blog\/news\/what-gemini-omni-could-mean-for-the-future-of-veo-and-business-video-creation\/","title":{"rendered":"What Gemini Omni Could Mean for the future of Veo and Business Video Creation"},"content":{"rendered":"\n<div class=\"wp-block-group has-base-2-background-color has-background has-global-padding is-layout-constrained wp-container-core-group-is-layout-1 wp-block-group-is-layout-constrained\" style=\"border-radius:20px;padding-top:var(--wp--preset--spacing--20);padding-right:var(--wp--preset--spacing--20);padding-bottom:var(--wp--preset--spacing--20);padding-left:var(--wp--preset--spacing--20)\">\n<h3 class=\"wp-block-heading is-style-asterisk\">Quick answer: What is Gemini Omni and Veo 4?<\/h3>\n\n\n\n<p>Veo 4 has not been officially announced by Google yet, but the timeline from Veo 3 to <a href=\"https:\/\/aistudio.google.com\/models\/veo-3\" target=\"_blank\" rel=\"noreferrer noopener\">Veo 3.1<\/a> suggests that Google is moving quickly toward AI video models with better audio, stronger visual consistency, more control, and more reliable scene generation. <a href=\"https:\/\/blog.google\/innovation-and-ai\/models-and-research\/gemini-models\/gemini-omni\/\" target=\"_blank\" rel=\"noreferrer noopener\">Gemini Omni<\/a> matters because it points to a broader future where AI video isn&#8217;t just text-to-video, but a multimodal, conversational creation process that can use text, images, video, and audio as references. For businesses, the main takeaway is simple: better video models will make AI-generated clips more useful, but teams will still need a complete workflow to plan, edit, review, brand, collaborate on, and share finished videos. That&#8217;s where platforms like Visla remain valuable, especially as next-generation models become part of everyday video production.<\/p>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Is Veo 4 coming?<\/h2>\n\n\n\n<p>As of May 2026, Google has not officially announced Veo 4. The most current official Veo model is Veo 3.1, which Google describes as its leading video generation model. We can talk about what Veo 4 might reasonably improve, but we don&#8217;t yet have release details, features, pricing, or availability. <\/p>\n\n\n\n<p>Still, the timeline gives us useful context.<\/p>\n\n\n\n<p><a href=\"https:\/\/blog.google\/innovation-and-ai\/products\/google-generative-ai-veo-imagen-3\/\" target=\"_blank\" rel=\"noreferrer noopener\">Google introduced Veo in 2024<\/a> as a major text-to-video model. <a href=\"https:\/\/www.cnbc.com\/2025\/05\/20\/google-ai-video-generator-audio-veo-3.html\" target=\"_blank\" rel=\"noreferrer noopener\">Veo 3 followed in 2025<\/a> with a major step forward: native audio. Instead of creating silent clips that needed separate sound design, Veo 3 could generate sound effects, ambient noise, and dialogue as part of the video. That was a meaningful shift because audio isn&#8217;t a finishing detail for business video. It affects comprehension, tone, pacing, and whether a clip feels usable.<\/p>\n\n\n\n<p>Then <a href=\"https:\/\/blog.google\/innovation-and-ai\/products\/veo-updates-flow\/\">Veo 3.1 arrived in Octob<\/a><a href=\"https:\/\/blog.google\/innovation-and-ai\/products\/veo-updates-flow\/\" target=\"_blank\" rel=\"noreferrer noopener\">e<\/a><a href=\"https:\/\/blog.google\/innovation-and-ai\/products\/veo-updates-flow\/\">r 2025<\/a>. Google positioned it around richer native audio, better narrative control, improved image-to-video generation, stronger prompt adherence, and better character consistency across multiple scenes. Google also added capabilities like reference images, scene extension, and first-and-last-frame control.<\/p>\n\n\n\n<p>That progression tells us something. Veo isn&#8217;t just getting more realistic. It&#8217;s getting more controllable.<\/p>\n\n\n\n<p>If Veo 4 follows the same direction, the most important improvements for businesses probably won&#8217;t be abstract model benchmarks. They&#8217;ll be practical gains: more consistent characters, better products and environments, fewer visual surprises, stronger motion control, and more reliable audio. <\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What Gemini Omni suggests about Veo 4 and Google&#8217;s AI video strategy<\/h2>\n\n\n\n<p><a href=\"https:\/\/blog.google\/innovation-and-ai\/models-and-research\/gemini-models\/gemini-omni\/\" target=\"_blank\" rel=\"noreferrer noopener\">Gemini Omni<\/a> isn&#8217;t Veo 4. Let&#8217;s be clear on that. It&#8217;s different Google model family built around multimodal creation and editing. <\/p>\n\n\n\n<p>Veo 3.1 is Google\u2019s specialized cinematic video generation model. Gemini Omni Flash points to something broader: AI video that can work from many kinds of inputs, including text, images, existing video, and audio. Instead of only asking a model to generate a clip from a prompt, users can start with source material, make changes in plain language, use references, and build toward a more coherent final output.<\/p>\n\n\n\n<p>Google also says Omni combines Gemini\u2019s reasoning and <a href=\"https:\/\/aiguide.substack.com\/p\/llms-and-world-models-part-1\" target=\"_blank\" rel=\"noreferrer noopener\">world knowledge<\/a> with generative media models, which is why the company frames it around coherent scene editing, physical logic, and reference-based control. That makes Omni important to a Veo 4 conversation because it shows where Google may be taking AI video overall: away from isolated clip generation and toward editable, multimodal video creation.<\/p>\n\n\n\n<p>For businesses, that may be the more important shift. Teams rarely start with a perfect text prompt. They start with product pages, decks, PDFs, scripts, screenshots, recordings, brand assets, and existing footage. A model that can understand and work across those inputs is much closer to how business video actually gets made.<\/p>\n\n\n\n<p>So Omni does not prove what Veo 4 will include. But it does show Google\u2019s larger direction: AI video is moving from one-shot clip generation toward multimodal, editable, reference-aware creation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Competition in the AI video space that Google might worry about<\/h2>\n\n\n\n<p>Google isn&#8217;t developing Veo in a vacuum. The AI video market is moving quickly, and competition is pushing every major player toward better quality, more control, and easier workflows.<\/p>\n\n\n\n<p><a href=\"https:\/\/openai.com\/index\/sora-2\/\" target=\"_blank\" rel=\"noreferrer noopener\">OpenAI\u2019s Sora 2<\/a> raised the stakes around physical realism, controllability, synchronized audio, and the ability to include real people through consent-based likeness features. Even though <a href=\"https:\/\/www.visla.us\/blog\/news\/openais-sora-what-happened-and-why-visla-isnt-worried\/\" target=\"_blank\" rel=\"noreferrer noopener\">Sora itself has been discontinued<\/a>, the model showed how quickly expectations for AI video can rise. Once users see more realistic motion, dialogue, and physics, they start expecting those capabilities everywhere.<\/p>\n\n\n\n<p>Runway has also been important, especially with <a href=\"https:\/\/runwayml.com\/research\/introducing-runway-gen-4\" target=\"_blank\" rel=\"noreferrer noopener\">Gen-4<\/a>. Runway has focused heavily on world consistency, including consistent characters, objects, locations, styles, and cinematic elements across scenes. That&#8217;s directly relevant to business video because companies do not just need beautiful visuals. They need a product, spokesperson, environment, or brand style to stay stable.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.adobe.com\/products\/firefly.html\" target=\"_blank\" rel=\"noreferrer noopener\">Adobe Firefly<\/a> takes a different angle. Its value proposition isn&#8217;t only generation quality, but commercial safety, creative controls, and integration with the Adobe ecosystem. That&#8217;s important because many companies care as much about risk and production workflow as they do about model quality.<\/p>\n\n\n\n<p>Taken together, the competitive landscape is pushing AI video in a clear direction. The winning tools will not just create better clips. They will help users control the output, keep assets consistent, reduce legal and brand risk, and fit AI generation into real production workflows.<\/p>\n\n\n\n<p>That&#8217;s exactly why a future Veo 4 would matter. It wouldn&#8217;t only compete with other models on realism. It would compete on whether it can become a dependable ingredient inside business video systems.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How businesses are using AI video models now<\/h2>\n\n\n\n<p>Businesses are already using AI video, but usually in practical ways. The clearest use cases aren&#8217;t full cinematic films. They&#8217;re repeatable business content where speed, scale, and easy updates matter.<\/p>\n\n\n\n<p>Marketing teams are using generative AI to create video ads, campaign variations, ecommerce visuals, product content, and social media assets. This is one of the strongest documented areas of AI video adoption. Advertisers want more creative versions for different audiences, channels, formats, and contexts. AI helps teams produce more variations without starting from scratch every time.<\/p>\n\n\n\n<p>L&amp;D teams are using AI video for training, onboarding, compliance, process education, and internal knowledge sharing. This makes sense because training content changes constantly. Processes update, policies shift, products evolve, and teams need clear materials that can be refreshed without a full production cycle.<\/p>\n\n\n\n<p>Communications teams are using AI video for company updates, project summaries, executive messages, and meeting replacements. This is less flashy than AI-generated ads, but it may be one of the most durable business uses. A short video can often explain context better than a long email or meeting invite.<\/p>\n\n\n\n<p>Customer success and support teams are using AI video to turn help articles, onboarding flows, support documentation, and knowledge-base content into short videos. This helps customers and support agents understand processes faster.<\/p>\n\n\n\n<p>Sales teams are beginning to use AI video for client communication, product explainers, account updates, and expert-led content. The strongest evidence here isn&#8217;t mass sales prospecting yet. 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40px 18px;\n        border-radius: 18px;\n      }\n\n      .takeaways {\n        grid-template-columns: 1fr;\n      }\n    }\n\n    @media (max-width: 640px) {\n      .ai-video-map {\n        border-left: none;\n        border-right: none;\n        border-radius: 0;\n      }\n\n      .legend {\n        align-items: flex-start;\n        flex-direction: column;\n      }\n\n      .legend-title { margin-bottom: 2px; }\n    }\n\n    @media (prefers-reduced-motion: reduce) {\n      *, *::before, *::after {\n        scroll-behavior: auto !important;\n        transition-duration: 0.01ms !important;\n        animation-duration: 0.01ms !important;\n        animation-iteration-count: 1 !important;\n      }\n    }\n  <\/style>\n<\/head>\n<body>\n  <section class=\"ai-video-map\" aria-labelledby=\"ai-video-map-title\">\n    <div class=\"header-row\">\n      <div>\n        <div class=\"eyebrow\">Evidence map<\/div>\n        <h2 id=\"ai-video-map-title\">Where business teams are using AI video today<\/h2>\n        <p class=\"dek\">AI video adoption is showing up most clearly where teams need speed, scale, repeatability, and easier updates. Bubble size represents the strength of available evidence, not exact adoption rate.<\/p>\n      <\/div>\n      <aside class=\"method-card\" aria-label=\"How to read this chart\">\n        <div class=\"method-label\">How to read it<\/div>\n        <p><strong>Large bubbles<\/strong> mean stronger public evidence, like survey-backed usage or multiple named business examples. Smaller bubbles mean early, adjacent, or less evenly documented use.<\/p>\n      <\/aside>\n    <\/div>\n\n    <div class=\"legend\" aria-label=\"Bubble legend\">\n      <span class=\"legend-title\">Bubble size<\/span>\n      <span class=\"legend-pill\"><span class=\"legend-dot strong\"><\/span>Strong evidence<\/span>\n      <span class=\"legend-pill\"><span class=\"legend-dot moderate\"><\/span>Moderate evidence<\/span>\n      <span class=\"legend-pill\"><span class=\"legend-dot early\"><\/span>Early evidence<\/span>\n    <\/div>\n\n    <div class=\"matrix-wrap\" role=\"img\" aria-label=\"Bubble matrix showing evidence strength for AI video use cases by business team\">\n      <div class=\"matrix\" aria-hidden=\"true\">\n        <div class=\"cell corner\">Team \/ use case<\/div>\n        <div class=\"cell column-head\">Campaign videos<br>&amp; ads<\/div>\n        <div class=\"cell column-head\">Training<br>&amp; onboarding<\/div>\n        <div class=\"cell column-head\">Internal<br>updates<\/div>\n        <div class=\"cell column-head\">Customer education<br>&amp; support<\/div>\n        <div class=\"cell column-head\">Sales \/ client<br>communication<\/div>\n        <div class=\"cell column-head\">Docs &amp; process<br>to video<\/div>\n\n        <div class=\"cell row-head\">Marketing<\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Advertising has the clearest survey-backed signal, plus named brand examples using AI for marketing content.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Marketing teams may use training-style videos internally, but this is not the strongest documented use.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Some overlap with campaign recaps and team updates, but limited public evidence.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Customer education can support marketing, but evidence is stronger under CS\/support.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Marketing and sales overlap on demos, explainers, campaign assets, and client-facing content.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Public examples support turning product pages, scripts, and existing assets into video.<\/span><\/button><\/div>\n\n        <div class=\"cell row-head\">L&amp;D<\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>L&amp;D may borrow campaign-style formats, but public evidence points more strongly to training.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Multiple business examples show AI video used for employee training, onboarding, and LMS content.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Learning teams use short video updates and refreshable content, especially for process changes.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Support-agent enablement and customer-facing learning overlap with L&amp;D workflows.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Sales training is plausible and adjacent, but direct evidence is less extensive here.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Training teams often turn documents, SOPs, help materials, and process knowledge into video.<\/span><\/button><\/div>\n\n        <div class=\"cell row-head\">Comms<\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Comms may create campaign-like announcements, but ad-specific evidence belongs to marketing.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Internal enablement and training-style videos often sit near comms teams.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Workplace video tools are explicitly used for announcements, project updates, summaries, and meeting recaps.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Some customer-facing communication overlap exists, but support evidence is stronger elsewhere.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Comms may support exec or client messaging, but evidence is more specific to finance and sales\/client teams.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Internal docs, meeting notes, and project materials can become short async videos.<\/span><\/button><\/div>\n\n        <div class=\"cell row-head\">Customer Success \/ Support<\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Support content can become promotional, but marketing-specific evidence is stronger.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Support-agent training and onboarding are documented in named business examples.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Support teams may use internal updates, but this is not the strongest public signal.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Customer education, support articles, and troubleshooting content are recurring AI video use cases.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>CS teams often support renewal, adoption, and client communication with educational video.<\/span><\/button><\/div>\n        <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble strong\">3<\/span><span class=\"tooltip\"><strong>Strong evidence<\/strong>Knowledge-base articles, help docs, process guides, and troubleshooting steps map naturally to AI video.<\/span><\/button><\/div>\n\n        <div class=\"row-last\" style=\"display: contents;\">\n          <div class=\"cell row-head\">Sales<\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Sales teams use demos, explainers, and personalized outreach formats, but less survey-backed than ads.<\/span><\/button><\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Sales enablement and role-based training are common adjacent uses.<\/span><\/button><\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Internal sales updates exist, but evidence is less visible publicly.<\/span><\/button><\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Sales may use customer education assets, but ownership often sits with CS\/support.<\/span><\/button><\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble moderate\">2<\/span><span class=\"tooltip\"><strong>Moderate evidence<\/strong>Client-facing expert videos and avatar-led communication are documented, though not yet universal.<\/span><\/button><\/div>\n          <div class=\"cell bubble-cell\"><button class=\"bubble-button\"><span class=\"bubble early\">1<\/span><span class=\"tooltip\"><strong>Early evidence<\/strong>Sales docs can become explainers, but this is less directly documented than training or support.<\/span><\/button><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n\n    <table class=\"sr-table\">\n      <caption>Accessible data table: AI video evidence strength by business team and use case. 3 is strong evidence, 2 is moderate evidence, 1 is early evidence.<\/caption>\n      <thead>\n        <tr><th>Team<\/th><th>Campaign videos and ads<\/th><th>Training and onboarding<\/th><th>Internal updates<\/th><th>Customer education and support<\/th><th>Sales and client communication<\/th><th>Docs and process to video<\/th><\/tr>\n      <\/thead>\n      <tbody>\n        <tr><td>Marketing<\/td><td>3<\/td><td>1<\/td><td>1<\/td><td>1<\/td><td>2<\/td><td>2<\/td><\/tr>\n        <tr><td>L&amp;D<\/td><td>1<\/td><td>3<\/td><td>2<\/td><td>2<\/td><td>1<\/td><td>3<\/td><\/tr>\n        <tr><td>Comms<\/td><td>1<\/td><td>2<\/td><td>3<\/td><td>1<\/td><td>1<\/td><td>2<\/td><\/tr>\n        <tr><td>Customer Success \/ Support<\/td><td>1<\/td><td>2<\/td><td>1<\/td><td>3<\/td><td>2<\/td><td>3<\/td><\/tr>\n        <tr><td>Sales<\/td><td>2<\/td><td>2<\/td><td>1<\/td><td>1<\/td><td>2<\/td><td>1<\/td><\/tr>\n      <\/tbody>\n    <\/table>\n\n    <div class=\"takeaways\">\n      <article class=\"takeaway-card\">\n        <div class=\"takeaway-number\">01<\/div>\n        <h3>Marketing has the strongest survey-backed signal.<\/h3>\n        <p>AI video is most clearly documented in ad creative, campaign variation, social content, and ecommerce marketing assets.<\/p>\n      <\/article>\n      <article class=\"takeaway-card\">\n        <div class=\"takeaway-number\">02<\/div>\n        <h3>Training and support are strong operational uses.<\/h3>\n        <p>L&amp;D and customer teams use AI video where content needs to be repeatable, searchable, updatable, and easier to understand.<\/p>\n      <\/article>\n      <article class=\"takeaway-card\">\n        <div class=\"takeaway-number\">03<\/div>\n        <h3>Comms and sales are growing, but less quantified.<\/h3>\n        <p>Internal updates, meeting recaps, client videos, and expert-led explainers are emerging uses, mostly supported by public examples.<\/p>\n      <\/article>\n    <\/div>\n\n    <aside class=\"source-notes\">\n      <h3>Method note<\/h3>\n      <p>This chart groups public evidence by business function. It should be read as a directional use-case map, not a market-share chart. Localization is not shown as a column because it cuts across several teams rather than belonging to one workflow.<\/p>\n    <\/aside>\n  <\/section>\n<\/body>\n<\/html>\n\n\n\n<h3 class=\"wp-block-heading\">Why businesses need more than a better AI video model<\/h3>\n\n\n\n<p>A better model solves one problem: the raw generation gets better. That matters, but it isn&#8217;t the whole job.<\/p>\n\n\n\n<p>Business video has more requirements. A team needs the message to be accurate. The video has to match the brand. Stakeholders need to review it. Legal or compliance teams may need to approve it. The script may need edits. The format may need to work for LinkedIn, an LMS, a product page, an email, or a help center. Someone may need to replace one scene next month without rebuilding the entire video.<\/p>\n\n\n\n<p>That&#8217;s why model quality alone ins&#8217;t enough.<\/p>\n\n\n\n<p>The difference between an impressive AI clip and a useful business video is the workflow around it. Without that workflow, teams can end up with beautiful fragments that are hard to revise, hard to approve, and hard to connect to a real business goal.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What complete AI video workflows should include<\/h3>\n\n\n\n<p>A complete AI video workflow should help teams move from source material to finished video with control at every stage.<\/p>\n\n\n\n<p>It should support many inputs, including prompts, scripts, webpages, PDFs, slide decks, recordings, audio, images, and existing footage. It should turn those inputs into a structured video plan. It should let users control scenes, visuals, voiceover, captions, music, aspect ratio, branding, and pacing. It should make editing simple after generation, not force users to regenerate everything. It should support collaboration, approvals, sharing, and versioning.<\/p>\n\n\n\n<p>Most importantly, it should help teams decide what should be generated, what should be recorded, what should use stock footage, what should use an avatar, and what should be edited from existing media.<\/p>\n\n\n\n<p>That mix matters. The future of business video will not be 100 percent AI-generated footage. It will be hybrid production, with AI helping teams choose the fastest and most appropriate path for each message.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How Visla brings next-gen models into real video production<\/h2>\n\n\n\n<p>This is where Visla\u2019s role becomes important.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.visla.us\/\" target=\"_blank\" rel=\"noreferrer noopener\">Visla<\/a> isn&#8217;t just a place to generate one single AI video clip. It&#8217;s a start-to-finish video production platform for recording, creation, editing, collaboration, and sharing. That makes the platform more valuable as models improve, not less.<\/p>\n\n\n\n<p>As models like Veo improve, Visla can bring stronger generation quality into workflows teams already need. A marketing team might start with a campaign brief and generate a video draft. An L&amp;D team might start with an SOP or slide deck and turn it into a training video. A customer success team might turn a help article into a customer-facing tutorial. A sales team might turn a product explanation into a polished, shareable video.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.visla.us\/ai-director-mode\" target=\"_blank\" rel=\"noreferrer noopener\">AI Director Mode<\/a> is especially relevant in this next era. Instead of jumping straight into random generation, teams can plan a video scene by scene, define characters, objects, environments, and brand elements, then decide which scenes should become AI-generated clips. That matters because better models still need direction.<\/p>\n\n\n\n<p>Visla\u2019s value isn&#8217;t only that it can use powerful AI models. It&#8217;s that it wraps them in a workflow designed for business output. That&#8217;s why when Veo 4 releases, Visla will become even better. <\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What teams should do now to prepare<\/h2>\n\n\n\n<p>The best way to prepare for Veo 4, Gemini Omni, and the next wave of AI video isn&#8217;t to wait for a model announcement. It&#8217;s to get your video workflow ready.<\/p>\n\n\n\n<p>First, organize your inputs. Gather brand assets, logos, product screenshots, approved images, voice guidelines, intro and outro templates, and example videos that show the style you want.<\/p>\n\n\n\n<p>Second, define your repeatable video types. Marketing might need product launch videos, campaign variants, social ads, and demo clips. L&amp;D might need onboarding, SOPs, compliance refreshers, and process explainers. Customer success might need tutorials, troubleshooting videos, and knowledge-base explainers.<\/p>\n\n\n\n<p>Third, create a review process. Decide who approves accuracy, who checks brand, who reviews compliance-sensitive topics, and who owns the final publishing decision.<\/p>\n\n\n\n<p>Finally, treat AI video as a workflow change, not just a new content button. The teams that benefit most will be the ones that know what they want to make, how it should sound, who needs to review it, and where it will be used.<\/p>\n\n\n\n<p>Veo 4 may bring a major step forward when it arrives. Gemini Omni already shows that AI video is becoming more multimodal, editable, and reference-aware. But the real business opportunity is bigger than any single model. The winners will be teams that pair better AI generation with better planning, editing, collaboration, and distribution.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/app.visla.us\/signup\" target=\"_blank\" rel=\"noreferrer noopener\">Prepare for the future with Visla<\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">FAQ<\/h2>\n\n\n\n<div class=\"schema-faq wp-block-yoast-faq-block\"><div class=\"schema-faq-section\" id=\"faq-question-1779316905716\"><strong class=\"schema-faq-question\">Is Veo 4 available yet?<\/strong> <p class=\"schema-faq-answer\">No. As of May 2026, Google has not officially announced Veo 4. Google\u2019s current public Veo page identifies Veo 3.1 as its leading video generation model, and Google\u2019s developer blog says Veo 3.1 was released on Oct. 15, 2025 with richer native audio, better image-to-video generation, improved prompt adherence, greater narrative control, and stronger character consistency across scenes. A future Veo 4 would likely build on that direction, but any specific Veo 4 features, release date, or pricing should be treated as unconfirmed until Google announces them.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1779317097915\"><strong class=\"schema-faq-question\">What is Gemini Omni, and how is it different from Veo?<\/strong> <p class=\"schema-faq-answer\">Gemini Omni is Google\u2019s multimodal creation and editing model family, starting with video through Gemini Omni Flash. Unlike a basic text-to-video tool, Omni can use different references, including image, text, video, and audio, to create or revise a single cohesive output. Google describes it as combining Gemini\u2019s reasoning with generative media models, with natural language editing, stronger world understanding, precise video editing, and better character consistency across scenes. Veo is best understood as Google\u2019s specialized cinematic video generation model, while Gemini Omni points toward a broader workflow where users can generate, edit, and refine video from multiple input types.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1779317103305\"><strong class=\"schema-faq-question\">Why do businesses still need an AI video platform if models like Veo and Gemini Omni keep improving?<\/strong> <p class=\"schema-faq-answer\">Better AI video models can generate higher-quality clips, but businesses still need a full workflow to turn those clips into usable videos. Teams need scripts, brand assets, captions, voiceover, review steps, approvals, scene-level edits, collaboration, sharing, and ways to update videos after they\u2019re published. Veo 3.1\u2019s progress around audio, narrative control, reference images, scene extension, and character consistency shows that models are becoming more useful for production, but business teams still need a platform layer that helps them plan, edit, brand, approve, and distribute finished videos.<\/p> <\/div> <\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Quick answer: What is Gemini Omni and Veo 4? Veo 4 has not been officially announced by Google yet, but the timeline from Veo 3 to Veo 3.1 suggests that Google is moving quickly toward AI video models with better audio, stronger visual consistency, more control, and more reliable scene generation. Gemini Omni matters because [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":7152,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":"","footnotes":""},"categories":[23],"tags":[],"class_list":["post-7110","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What Gemini Omni Could Mean for the future of Veo and Business Video Creation - The Visla Blog<\/title>\n<meta name=\"description\" content=\"Explore what Gemini Omni could mean for AI video and the future of Veo, and why businesses still need complete video workflows.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.visla.us\/blog\/news\/what-gemini-omni-could-mean-for-the-future-of-veo-and-business-video-creation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What Gemini Omni Could Mean for the future of Veo and Business Video Creation - 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Veo is best understood as Google\u2019s specialized cinematic video generation model, while Gemini Omni points toward a broader workflow where users can generate, edit, and refine video from multiple input types.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.visla.us\/blog\/news\/what-gemini-omni-could-mean-for-the-future-of-veo-and-business-video-creation\/#faq-question-1779317103305","position":3,"url":"https:\/\/www.visla.us\/blog\/news\/what-gemini-omni-could-mean-for-the-future-of-veo-and-business-video-creation\/#faq-question-1779317103305","name":"Why do businesses still need an AI video platform if models like Veo and Gemini Omni keep improving?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Better AI video models can generate higher-quality clips, but businesses still need a full workflow to turn those clips into usable videos. Teams need scripts, brand assets, captions, voiceover, review steps, approvals, scene-level edits, collaboration, sharing, and ways to update videos after they\u2019re published. Veo 3.1\u2019s progress around audio, narrative control, reference images, scene extension, and character consistency shows that models are becoming more useful for production, but business teams still need a platform layer that helps them plan, edit, brand, approve, and distribute finished videos.","inLanguage":"en-US"},"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/posts\/7110","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/comments?post=7110"}],"version-history":[{"count":44,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/posts\/7110\/revisions"}],"predecessor-version":[{"id":7156,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/posts\/7110\/revisions\/7156"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/media\/7152"}],"wp:attachment":[{"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/media?parent=7110"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/categories?post=7110"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.visla.us\/blog\/wp-json\/wp\/v2\/tags?post=7110"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}