Generative AI has opened up new doors for creating personalized digital content at scale by leveraging powerful deep learning models. Generative AI systems can create novel images, videos, text and more based on a given prompt or dataset in a fraction of the time it would take humans. This emerging technology has applications across various industries for generating synthetic training data, personalized recommendations and consumable digital media.
The global generative AI market comprises various software and services that utilize deep learning techniques like self-supervised learning, transformer architectures and generative adversarial networks to rapidly produce customized digital outputs. Generative AI tools find widespread usage in e-commerce for product image generation, in media & entertainment for visual effects, animation and script writing, in education technology for adaptive learning content and in various enterprise functions for process automation through synthetic documentation.
Global generative AI market is estimated to be valued at USD 68.34 Bn in 2024 and is expected to reach USD 496.82 Bn by 2031, exhibiting a compound annual growth rate (CAGR) of 32.8% from 2024 to 2031.
Key Takeaways
Key players operating in the generative AI market are Anthropic, DALL-E, Stability AI, OpenAI, Anthropic amongst others.
The growing Generative AI Market Demand for personalized experiences is propelling the adoption of generative AI solutions across industries. Generative models can customize outputs to individual user preferences, behaviors and contexts at scale.
Many major organizations are investing in generative AI startups to gain early access to this promising technology and explore commercial applications. Increased investment and M&A activity is fueling the global expansion of the generative AI market.
Market Key Trends
Self-supervised learning is a key trend shaping the generative AI domain. By leveraging vast amounts of unlabeled data, self-supervised models are able to learn the inherent structures in the data distribution and generate highly realistic outputs after minimal fine-tuning on a target task. This makes generative AI more sample efficient and suited for a wider variety of applications.
Porter’s Analysis
Threat of new entrants: Generative AI requires a huge amount of data and high computational power which create entry barriers for new startups. Large companies have an established brand and market dominance.
Bargaining power of buyers: Buyers have moderate bargaining power as they can choose from various solutions as there are many players in the market providing similar products and services. Switching costs are low.
Bargaining power of suppliers: Suppliers have high bargaining power due to the specialized skills required and lack of substitutes. Data providers and chip makers dominate the market.
Threat of new substitutes: Potential threats come from alternative emerging technologies like neural architecture search which can emerge as substitutes.
Competitive rivalry: Intense competition exists among major players to gain market share and adapt new business models in a rapidly evolving landscape.
North America region accounts for the largest share in the generative AI market in terms value due to presence of major tech companies and huge investments in AI research. The Asia Pacific region is expected to witness the fastest growth during the forecast period supported by increasing digitization initiatives by governments and growing tech startup culture.
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About Author:
Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc. (https://www.linkedin.com/in/money-singh-590844163)