The global Generative AI Market size is anticipated to grow at a CAGR of 36.7% during the forecast period, from USD 20.9 billion in 2024 to USD 136.7 billion by 2030.
The Generative AI Market is poised for substantial growth, propelled by several key business drivers. Factors such as development of cloud storage solutions making data retrieval effortless, advancement in AI and deep learning technologies reshaping industries, and the surge in creative content production and diverse applications collectively steer the expansion of the Generative AI Market.
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Generative AI Market Dynamics:
Drivers:
- Innovation of cloud storage enabling easy access to data
- Evolution of AI and deep learning
- Rise in content creation and creative applications
Restraints:
- High costs associated with training data preparation
- Issues related to bias and inaccurately generated output
- Risks associated with data breaches and sensitive information leaks
Opportunities:
- Acceleration in deployment of Large Language Models (LLMs)
- Arousing interest of enterprises in commercializing synthetic images
- Robust improvement in generative ML leading to human baseline performance
List of Key Players in Generative AI Market:
- Microsoft (US)
- OpenAI (US)
- Google (US)
- AWS (US)
- Adobe (US)
- Anthropic (US)
- Paige.AI (US)
- Midjourney (US)
- Jasper (US)
- Synthesia (UK)
In the field of generative design, a rapid adoption of generative AI can be expected, particularly in the design of physical products and services. The preferred media format among younger generations is video, so it is not surprising that tools tapping into this trend have been quickly developed by AI toolmakers. Another trend which can be seen is towards multi-modal generative AI. It is anticipated that the forthcoming version of OpenAI’s ChatGPT will be capable of understanding and interpreting images, as well as being able to respond to voice commands. This capability is expected to become more common over the next year, making it normal to engage with an AI about a picture or a video in the same way as with text today. One prevalent regulatory change is The Artificial Intelligence Act (AI Act) of the European Union. Proposed by the European Commission on 21 April 2021 and passed on 13 March 2024, it aims to establish a common regulatory and legal framework for AI.
Based on application, the synthetic data management segment is projected to grow at the fastest rate during the forecast period due to its crucial role in addressing the challenges of data privacy and scarcity. With increasing concerns about data privacy regulations and the limitations in accessing real-world data for training AI models, synthetic data offers a compelling solution. It allows companies to generate vast amounts of diverse and realistic data without compromising privacy or dealing with data access hurdles. This capability is particularly valuable in industries like healthcare, finance, and autonomous vehicles, where large and diverse datasets are essential for effective AI development.
Based on verticals, Retail & e-commerce vertical is poised for rapid growth during the forecast period due to several key factors. One major driver is the increasing need for personalized customer experiences and enhanced product recommendations. Generative AI can analyze vast amounts of customer data to generate tailored product recommendations, create personalized marketing content, and even design custom products based on individual preferences. This level of customization and personalization not only improves customer satisfaction but also drives sales and customer loyalty. Additionally, generative AI enables retailers to optimize supply chain management, inventory forecasting, and pricing strategies through advanced data analysis and predictive modeling.
The Generative AI Market offers numerous opportunities for businesses to seize. One key avenue is the advancement of multi-modal generative AI, capable of comprehending diverse data types like text, images, and voice. This expansion enables companies to serve a wider array of industries, including healthcare, entertainment, and marketing. Another promising prospect involves integrating generative AI with existing software, bolstering their capabilities. Developing APIs and SDKs facilitates seamless integration into various products, empowering developers, and businesses to harness AI’s potential without extensive expertise. Additionally, a rising need exists for generative AI tailored to specific industry challenges, such as creating synthetic data for training AI models in data-scarce fields or generative design tools for streamlining product development. Focusing on niche markets and crafting specialized generative AI solutions allows companies to stand out and tap into lucrative segments.
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