Global AI-based 3D Asset Generation Software Market – Industry Trends and Forecast to 2031

The AI-based 3D Asset Generation Software Market is experiencing robust expansion, with market size projected to increase from (1.2 Billion) 2023 to (5.4 Billion) 2031, demonstrating a consistent year-over-year growth rate of 18.5%. AI-based 3D Asset Generation Software Market Size, Share, Competitive Landscape and Trend Analysis Report, by Types (Cloud-Based, On-Premises), by Applications (Large Enterprises, Small and Medium Enterprises (SMEs), Individual Creators) , by Industry Vertical (Gaming and Entertainment, E-Commerce, Architecture and Construction, Film and Animation, Education and Training) And Regions (North America (United States, Canada, Mexico), South America (Brazil, Argentina, Chile, Rest of South America), Europe (Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe), Asia Pacific (China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific), MEA (Middle East, Africa)) : Industry Forecast and Opportunity Analysis for 2023 - 2031

AI-based 3D asset generation software refers to AI-powered tools that automate the creation of high-quality 3D models, textures, and environments for apps such as games, AR/VR, product design, and virtual worlds. Taking advantage of deep learning, generative algorithms, and procedural techniques, these platforms interpret text warnings, images, sketches, or parameters to produce fully textured and often ready-for-equipment models. This simplifies workflows, allowing artists and developers to quickly prototype, iterate, and climb 3D content while reducing manual modelling time—ushering in a new era of creative automation and design efficiency.

AI-based 3D Asset Generation Software Report Highlights

Report Metrics	Details
Forecast period	2019-2031
Base Year Of Estimation	2023
Growth Rate	CAGR of 18.5%
Forecast Value (2031)	USD 5.4 Billion
By Product Type	Cloud-Based, On-Premises
Key Market Players	Google Masterpiece Studio Meshcapade Alpha3D Meta Gepetto.ai 3DFY.ai Kaedim Sloyd.ai Stability AI Luma AI Fotor Spline AI BrXnd.ai ChatAvatar (Deemos) NVIDIA Mochi
By Region	North America (United States, Canada, Mexico) South America (Brazil, Argentina, Chile, Rest of South America) Europe (Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe) Asia Pacific (China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific) MEA (Middle East, Africa)

AI-based 3D Asset Generation Software Market Trends

• Rise of text-to-3D and image-to-3D pipelines
  Generative AI models (such as GANs and diffusion networks) are allowing the creation of high-quality 3D assets directly from text prompts, images, or multimodal inputs, dramatically improving asset production workflows.
   
• Tech giants open-sourcing 3D tools
  Platforms like Tencent Hunyuan3D 2.0 are now available as "turbo" models of open source, generating 3D visuals in seconds, administering innovation, and reducing barriers to developers and creators.
   
• Surging adoption in gaming, AR/VR, and the metaverse
  Industries such as games, virtual retail, and immersive experiences are pushing massive demand for fast and scalable 3D content, pushing the strong adoption of AI-driven generation tools.

AI-based 3D Asset Generation Software Market Leading Players

The key players profiled in the report are BrXnd.ai, Alpha3D, NVIDIA, Google, Kaedim, Masterpiece Studio, ChatAvatar (Deemos), Meshcapade, Fotor, Gepetto.ai, Spline AI, Sloyd.ai, Stability AI, Luma AI, Meta, 3DFY.ai, Mochi

Growth Accelerators

• Advances in AI, ML, and Computer Vision
  Cutting-edge algorithms and deep learning allow fast and accurate generation of 3D models of images, text, and 2D sketches. This has significantly reduced the technical barrier to creating high-fidelity 3D content.
   
• Increasing demand for 3D content among industries
  Sectors such as games, architecture, e-commerce, real estate, and health care require scalable and real-time 3D assets for immersive experiences and product visualisation for widespread adoption.
   
• AI-powered cost and time efficiencies
  Automated asset creation tools reduce intensive manual modelling, accelerating development cycles and reducing costs, making 3D workflows accessible to smaller teams and companies.

AI-based 3D Asset Generation Software Market Segmentation analysis

The Global AI-based 3D Asset Generation Software is segmented by Type, Application, and Region.
By Type, the market is divided into Distributed Cloud-Based, On-Premises . The Application segment categorizes the market based on its usage such as Large Enterprises, Small and Medium Enterprises (SMEs), Individual Creators. Geographically, the market is assessed across key Regions like North America (United States, Canada, Mexico), South America (Brazil, Argentina, Chile, Rest of South America), Europe (Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe), Asia Pacific (China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific), MEA (Middle East, Africa) and others, each presenting distinct growth opportunities and challenges influenced by the regions.

Competitive Landscape

Main technology companies such as Nvidia, Unity, and Tencent (with their Hunyuan3D 2.0 open-source models) are leading the market, integrating robust AI resources in graphics and existing game development platforms. Specialised tools—on-mesh, spline, Rodin, and Sloyd-SE—concentrate on niche strengths, such as rapid 3D text prototyping, web-based collaboration, topology quality, and customisation to meet the accurate needs of designers. Additional players, including 3D AI Studio, Top AI, and Luma AI, offer customized game solutions, AR/VR, and product viewing. The field is marked by rapid innovation—with recent academic advances such as Hunyuan3D2.5 pushing fidelity and realism—and intense competition as platforms differ by speed, output quality, integration, and pricing.

Challenges In AI-based 3D Asset Generation Software Market

• Ambiguity in text-to-3D prompts
  Textual instructions often lack sufficient details for precise output, making spatial reasoning and understanding context. This makes the accuracy and specificity hard to achieve.
   
• Limited quality and quantity of training data
  Existing data sets are usually small, fragmented, or of low quality, limiting AI performance and hindering generalisation to new types or asset contexts.
   
• Heavy computational and integration costs
  The generation of consistent and high loyalty assets at the points of view needs immense computing power and resources. The integration of these AI tools in the current pipelines also presents the complexity of engineering.

 

 

Risks & Prospects in AI-based 3D Asset Generation Software Market

AI-based 3D asset generation software is positioned to dominate due to a powerful combination of factors: increasing demand in sectors such as games, AR/VR, e-commerce, architecture, and digital twins; quick advances in generative AI, photogrammetry, and computational vision that automate and suffer asset creation; and significant advocacy from Big Tech—Nvidia, Unity, Adobe, Tencent, and Autodesk—which are incorporating these tools into their ecosystems. These forces collectively allow faster, more accessible, and more economical workflows, making it feasible to create high-quality 3D content and accelerate adoption in global markets.

Key Target Audience

 , Designers use it to generate realistic 3D mock-ups of products—such as furniture, jewellery, or appliances—sketches, or images, simplifying ideation and visualisation., AAA and indie teams use AI tools to accelerate the creation of props, environments, and backgrounds, reducing manual modelling time and enabling rapid prototyping.
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Game developers and studios
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Product designers and industrial modellers
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AR/VR content creators
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, Augmented and virtual developers take advantage of AI to create immersive experiences, transforming text or images into real-time 3D assets that improve UX and interactivity.
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Merger and acquisition

• Chaos acquires EvolveLAB.
  In February 2025, visualisation leader CHAOS (former V-Ray Developer) purchased Germany's Evolvelab, known for its AI-driven architectural modelling tools. The agreement extends CHAOS' platform to include generative design, BIM integration, and AI documentation workflows.
   
• Hexagon acquires the Geomagic suite.
  In April 2025, Hexagon completed his procurement of the Geomagic software suite from 3D Systems. The integration brings powerful laser scan-based 3D modelling tools to Hexagon's manufacturing intelligence division.
   
• CoStar Group acquires Matterport.
  In February 2025, the CoStar Group completed the acquisition of Matterport, a leader in AI-enhanced 3D spatial mapping and digital twins. This feature accelerates AI-driven real estate insight and digital twin innovation in real estate.