Report Format:  
| Pages: 110+
Type: Niche Industry Monitor
| ID: AI4215
| Publication: June 2024
|
US$925 |
Currently, Generative AI in Brazil has appeared to have moved beyond the peak of inflated expectations and is transitioning towards the trough of disillusionment in the Hype Cycle. The most valuable applications of generative AI tend to focus on solving specific problems within particular domains, enhancing human productivity rather than replacing it entirely. Entrepreneurs have prioritized building products with a clear focus and establishing a competitive advantage. This is anticipated to involve developing a strong brand, implementing robust security features, leveraging network effects, or securing proprietary intellectual property. For Brazilian start-ups, the most promising opportunities lie in application layers, capitalizing on factors such as The Home-Field Advantage (addressing local needs effectively) and Affordable Agility (developing tech solutions in Brazil at a lower cost compared to the developed countries).
Brazilian companies have recognized the potential benefits of generative AI in streamlining operations, improving user experience, and staying competitive in the market. By embracing GAI technology, they position themselves as innovators and leaders in the industry, potentially gaining a competitive edge over their global counterparts. This trend also underscores the growing importance of GAI technologies especially in the financial services sector, highlighting the need for continued investment and integration of AI solutions to drive growth and efficiency. For instance,
Major companies in the generative AI space primarily offer infrastructure services through model APIs and open-source libraries, contributing significantly to the industry's foundational development. Emerging startups making notable strides in this field include:
Analysis Period |
2019 – 2032 |
Actual Data |
2019 – 2023 |
Base Year |
2023 |
Estimated Year |
2024 |
CAGR Period |
2024 – 2032 |
Research Scope |
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Component |
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Deployment Model |
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Business Function |
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Technique |
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End User |
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