Stratistics MRC에 따르면 세계의 생성형 인공지능 시장은 2025년 853억 달러를 차지하며, 예측 기간 동안 CAGR 39.6%로 성장하여 2032년까지 8,819억 달러에 이를 것으로 예측됩니다.
생성형 AI는 학습된 데이터와 유사한 새로운 데이터 출력을 생성하도록 설계된 인공지능 시스템의 카테고리입니다.
2023년 업계 전문가에 따르면 87%의 사용자는 대화형 AI/채팅봇이 전반적인 생산성을 향상시키는 데 도움이 될 것이라고 생각합니다.
디지털 미디어 및 엔터테인먼트 성장
디지털 미디어 플랫폼과 컨텐츠 주도의 비즈니스 모델의 확대가 애니메이션, 게임 디자인, 버추얼 프로덕션에 걸친 생성형 AI 솔루션 수요를 촉진하고 있습니다. 메타버스 이니셔티브와 디지털 아바타의 보급에 힘입어, 생성형 AI는 차세대 미디어의 에코시스템의 중심이 되고 있습니다.
규제 틀의 부족
AI가 생성하는 컨텐츠에 대한 명확하고 통일된 규제가 없기 때문에 업계 이해관계자들은 운영상의 불확실성과 윤리적 딜레마를 느끼고 있습니다. 오보나 브랜드의 안전성에 대한 우려가 박차를 가해, 규제의 갭이 신뢰를 저해하고, 혁신을 지연시키고 있습니다.
다른 AI 용도과의 통합
NLP, 추천 엔진, 컴퓨터 비전과 같은 보완적인 기술과 생성형 AI를 통합하면 자동화와 인사이트의 새로운 차원이 열립니다. 엔터프라이즈 수준의 디자인, 컨텐츠 제작 및 프로토타이핑에 있어서 AI의 도입으로 이어져, 생성형 AI는 독립형 툴의 영역을 넘어가고 있습니다.
오해를 초래하는 컨텐츠 생성에 악용
매우 현실적인 텍스트, 음성, 비주얼을 창조하는 생성형 AI의 능력은 여론을 조작하고 소비자를 속일 가능성에 대한 경계심을 높여주고 있습니다. 액세스에 대한 장벽이 낮고 추적성이 최소한으로 뒷받침되며, 딥페이크와 합성 컨텐츠가 소셜 플랫폼 전체에 확산되고 있습니다.
COVID-19의 대유행은 디지털 툴의 채용을 대폭 가속화하고, 생성형 AI를 원격 크리에이티브와 컨텐츠 자동화의 중요한 실현 요소로 자리매김했습니다.
예측 기간 동안 이미지 및 동영상 생성 모델 부문이 최대가 될 전망
영상 및 동영상 생성 모델 부문은 디자인, 마케팅, 엔터테인먼트, 시뮬레이션 업계에서 채용의 급증에 추진되어 예측 기간 동안 최대 시장 점유율을 차지할 것으로 예측됩니다. ML과 같은 오픈소스 툴과 기반 모델에 힘입어 이 기술은 현재 기업과 독립형 크리에이터가 모두 사용할 수 있게 되었습니다.
예측 기간 동안 적대적 생성 네트워크(GANs) 분야의 CAGR이 가장 높을 것으로 예측됩니다.
예측 기간 동안 적대적 생성 네트워크(GANs) 부문은 포토리얼리틱한 출력을 생성하는 탁월한 능력에 영향을 받으며 가장 높은 성장률을 보일 것으로 예측됩니다. 하이테크 선도 및 연구소의 투자 증가에 힘입어 GAN 기반 아키텍처는 보다 높은 정확도와 제어성을 목표로 개선되고 있습니다.
예측기간 동안 아시아태평양은 적극적인 디지털 전환에 대한 대처와 AI 인프라 투자 증가로 최대 시장 점유율을 차지할 것으로 예측됩니다. 자금 조달과 정책 틀 등 AI 개발에 대한 정부의 강력한 지원에 힘입어 이 지역의 채용은 가속화되고 있습니다.
예측 기간 동안 북미는 가장 높은 CAGR을 보여줄 것으로 예상되며, 강력한 R&D 투자, 상업 전개, AI 혁신자의 밀집이 그 원동력이 되고 있습니다. 벤처 캐피탈의 지원과 IPO 활동에 힘입어 일부 생성형 AI 기업은 프로토타입에서 주류 채용으로 확대되고 있습니다.
According to Stratistics MRC, the Global Generative AI Market is accounted for $85.3 billion in 2025 and is expected to reach $881.9 billion by 2032 growing at a CAGR of 39.6% during the forecast period. Generative AI is a category of artificial intelligence systems designed to create new data outputs that resemble the data they were trained on. These systems use models capable of learning the underlying structure and patterns of data, enabling them to generate original content such as text, images, or code. Unlike discriminative models, which classify or predict outcomes, generative models aim to produce new, synthetic data that is statistically consistent with their training inputs.
According to an industry expert in 2023, 87% users believe that conversational AI/chatbots help increase the overall productivity.
Growth in digital media and entertainment
The expansion of digital media platforms and content-driven business models is fueling demand for generative AI solutions across animation, game design, and virtual production. Propelled by the need to generate engaging, hyper-realistic content at scale, studios and creators are adopting AI models to expedite production cycles.Backed by the proliferation of metaverse initiatives and digital avatars, generative AI is central to next-gen media ecosystems. Motivated by cost-efficiency and content localization needs, the entertainment sector continues to integrate generative AI into its workflows.
Lack of regulatory frameworks
The absence of clear and uniform regulations regarding AI-generated content has created operational uncertainties and ethical dilemmas for industry stakeholders. Driven by evolving questions around copyright ownership, consent, and deepfake misuse, many organizations hesitate to deploy generative AI tools at full scale. Spurred by concerns over misinformation and brand safety, regulatory gaps undermine trust and delay innovation. Guided by the need for transparent usage policies and auditing mechanisms, companies are lobbying for balanced frameworks that protect creativity and accountability.
Integration with other AI applications
Integrating generative AI with complementary technologies-such as NLP, recommendation engines, and computer vision-is unlocking new dimensions of automation and insight. Spurred by this convergence, enterprises can now build context-aware virtual agents, auto-generate synthetic datasets, and enhance visual search capabilities.Guided by the adoption of AI in enterprise-level design, content creation, and prototyping, generative AI is moving beyond standalone tools. Backed by developer-friendly APIs and open-source frameworks, integration across AI stacks is scaling rapidly.
Misuse for generating misleading content
The ability of generative AI to fabricate hyper-realistic text, audio, and visuals has raised alarm over its potential to manipulate public opinion and deceive consumers. Spurred by political misinformation campaigns and fraudulent media, malicious use of generative models threatens public trust and digital integrity. Fueled by low barriers to access and minimal traceability, deepfakes and synthetic content are proliferating across social platforms.Guided by increasing global scrutiny, calls for responsible deployment and watermarking standards are intensifying.
The COVID-19 pandemic significantly accelerated the adoption of digital tools, positioning generative AI as a key enabler of remote creativity and content automation. Spurred by limitations on live production and physical collaboration, companies turned to AI to simulate, animate, and localize content virtually.Backed by the shift to digital-first marketing and e-commerce, demand for AI-powered visuals and copywriting surged. Motivated by these changes, the post-pandemic era has embraced generative AI as a core component of creative pipelines.
The image & video generative modelssegment is expected to be the largest during the forecast period
The image & video generative modelssegment is expected to account for the largest market share during the forecast period,propelled by surging adoption in design, marketing, entertainment, and simulation industries. Driven by open-source tools and foundation models such as DALL-E and Runway ML, the technology is now accessible to both enterprises and independent creators. Backed by scalable cloud infrastructure and GPU acceleration, rendering and inference processes are becoming faster and more economical. Guided by advancements in image fidelity and prompt engineering, image & video generation remains a dominant use case.
The generative adversarial networks (GANs) segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the generative adversarial networks (GANs) segment is predicted to witness the highest growth rate, influenced bytheir unmatched capabilities in generating photorealistic outputs. Driven by academic research and industrial experimentation, GANs continue to evolve through innovations like StyleGAN and CycleGAN. Backed by rising investment from tech giants and research labs, GAN-based architectures are being refined for higher accuracy and control. Motivated by the need to simulate real-world scenarios digitally, the segment is poised for substantial expansion.
During the forecast period, the Asia Pacific region is expected to hold the largest market share, fuelled byaggressive digital transformation initiatives and rising investment in AI infrastructure. Driven by the presence of major tech players in China, South Korea, and Japan, the region is leading in both generative AI research and commercialization.Backed by robust government support for AI development, including funding and policy frameworks, regional adoption is accelerating.Motivated by the demand for scalable content generation in gaming, e-learning, and retail, Asia Pacific continues to dominate in generative AI deployment.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, driven bystrong R&D investments, commercial deployments, and a dense concentration of AI innovators. Propelled by widespread enterprise adoption in sectors like media, healthcare, and finance, generative AI is scaling rapidly. Spurred by venture capital backing and IPO activity, several generative AI firms have expanded from prototype to mainstream adoption. Backed by increasing enterprise cloud migration and demand for automation, North America is emerging as a global growth engine in generative AI.
Key players in the market
Some of the key players in Generative AI Market include NVIDIA, Adobe, Amazon Web Services (AWS), Autodesk, Baidu, Google LLC, IBM, Lighttricks, Meta, Microsoft, Synthesis AI, SAP SE, Accenture, Rephrase.ai, Genie AI Ltd., MOSTLY AI Inc., and D-ID.
In June 2025, NVIDIA launched an advanced generative AI platform for real-time content creation. Leveraging GPU technology, it enables creative industries to produce high-quality graphics and videos, streamlining workflows and enhancing productivity.
In April 2025, Amazon Web Services unveiled a generative AI service for automated content generation. It supports e-commerce and marketing, creating personalized content to enhance customer engagement and streamline campaign production processes.
In March 2025, Autodesk launched a generative AI tool for automated 3D modeling. It optimizes design processes in architecture and engineering, enabling faster, more efficient creation of complex models with AI-driven insights.