AI: How BlackRock is viewing the sector
The surge in artificial intelligence (AI) has intrigued investors seeking opportunities beyond established tech giants. However, AI's intricate landscape poses challenges in identifying winners and predicting trends. $Blackrock (BLK.US)$ 's Rick Rieder acknowledges the complexities in AI investments.
Comparing with the Internet Boom
Contrasting AI with the speculative internet era, Rieder notes the subtleties of AI investments. Unlike the internet's diverse avenues, AI presents unique challenges, making investment decisions intricate.
Predicting Winners and Mergers
Rieder anticipates mergers and acquisitions in AI. Selecting winners and assessing potential business disruptions are daunting tasks. The focus lies on companies closely tied to AI applications, while evaluating long-term cash flow potential from derivative sectors.
Gradual AI Revenue Growth
Examining companies like Synopsys, Rieder acknowledges AI's current modest revenue contribution (5-10%). Identifying the right time to invest in potential high-growth AI companies is crucial. Sectors adjacent to AI, like chip manufacturing, could experience significant growth in the next year.
Navigating Investment Complexity
Investing in AI's second or third derivatives is challenging due to delayed returns. Adjacent sectors offer more tangible opportunities due to their immediate connection with AI.
Role of Acquisitions in Growth
Rieder underscores acquisition strategies' effectiveness in rapidly integrating advanced technologies, particularly in enterprise software and cloud sectors.
Tech Industry's Inherent Strength
Rieder debunks the idea that AI alone drives tech success. Established tech giants thrive organically, capitalizing on diverse revenue streams.
AI's Market Impact
AI influences market sentiment, especially within tech. However, broader strengths, like diverse cash flows, contribute to tech companies' resilience.
Conclusion: Navigating the Unpredictable AI Terrain
Rieder's insights illuminate AI investment intricacies. The nuanced challenges, unpredictable winners, and potential disruptions underscore the need for cautious, informed investment decisions as the AI landscape evolves.
Contrasting AI with the speculative internet era, Rieder notes the subtleties of AI investments. Unlike the internet's diverse avenues, AI presents unique challenges, making investment decisions intricate.
Predicting Winners and Mergers
Rieder anticipates mergers and acquisitions in AI. Selecting winners and assessing potential business disruptions are daunting tasks. The focus lies on companies closely tied to AI applications, while evaluating long-term cash flow potential from derivative sectors.
Gradual AI Revenue Growth
Examining companies like Synopsys, Rieder acknowledges AI's current modest revenue contribution (5-10%). Identifying the right time to invest in potential high-growth AI companies is crucial. Sectors adjacent to AI, like chip manufacturing, could experience significant growth in the next year.
Navigating Investment Complexity
Investing in AI's second or third derivatives is challenging due to delayed returns. Adjacent sectors offer more tangible opportunities due to their immediate connection with AI.
Role of Acquisitions in Growth
Rieder underscores acquisition strategies' effectiveness in rapidly integrating advanced technologies, particularly in enterprise software and cloud sectors.
Tech Industry's Inherent Strength
Rieder debunks the idea that AI alone drives tech success. Established tech giants thrive organically, capitalizing on diverse revenue streams.
AI's Market Impact
AI influences market sentiment, especially within tech. However, broader strengths, like diverse cash flows, contribute to tech companies' resilience.
Conclusion: Navigating the Unpredictable AI Terrain
Rieder's insights illuminate AI investment intricacies. The nuanced challenges, unpredictable winners, and potential disruptions underscore the need for cautious, informed investment decisions as the AI landscape evolves.
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lightfoot : I think we are a long way from the true meaning of AI. So many tests, evaluations plus quantifying results Valid