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- 🤖 Deloitte's 2024 AI Predictions
Good morning and welcome to the latest edition of neonpulse!
Today, we’re talking about Deloitte's 2024 tech predictions, exploring the transformative impact of generative AI on the semiconductor market and the challenges of integrating AI into the business landscape 🤖
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Deloitte's 2024 Predictions: Generative AI's Pivotal Role in Reshaping the Tech Industry
Deloitte's 2024 Technology, Media, and Telecommunications Predictions report presents a comprehensive analysis of upcoming trends in the tech world, with a particular focus on the growing influence of generative AI in the semiconductor industry. The report predicts that by 2027, specialized generative AI chips could constitute half the value of all semiconductors sold, signaling a significant shift in the industry landscape.
The integration of generative AI into enterprise software is anticipated to be nearly universal in 2024. This widespread adoption is expected to boost AI chip sales to more than $50 billion globally, with software revenue potentially reaching a $10 billion run rate by the end of 2024. The surge in demand for specialized chips optimized for generative AI is notable, escalating from almost zero to a projected two-thirds of all AI chip sales in 2022. By 2024, AI chip sales are forecasted to represent 11% of the global chip market, which could be valued between $110 billion and $400 billion by 2027.
Deloitte’s findings reveal that over 70% of companies are experimenting with generative AI, but less than 20% are willing to increase their current spending on it. This suggests a cautious approach by businesses in investing heavily in generative AI technologies. The largest cloud players are predicted to allocate between 3% to 13% of their 2024 capital expenditures on generative AI, although managing the operating costs of these systems remains a challenge. The per-query cost of generative AI ranges from $0.01 to $0.36, indicating the need for companies to demonstrate a positive return on investment for these technologies.
A key challenge for software companies in 2024 will be finding a sustainable pricing model for generative AI services that captures its value, covers its costs, and is acceptable to customers. The trend towards private generative AI is emerging, with organizations like Adobe Systems and Getty Images launching privately trained models, which are seen as more reliable compared to publicly trained models that may generate incorrect answers or source data from inappropriate channels. This shift towards private models is expected to continue, with more companies either working with hyperscalers to host the models or purchasing hardware to support them.
The cost and availability of advanced chips for running generative AI present another significant factor. These chips, which can cost around $40,000 each, are mostly manufactured in Asia and are subject to geopolitical influences, including trade restrictions. The demand for these chips could also impact other markets, like liquid cooling and high-voltage power supplies. However, Deloitte cautions that if enterprise AI use cases do not materialize as expected, the current surge in AI chip sales could be a bubble on the verge of bursting.
The report characterizes 2024 as a transition year, with various enterprise software tools expected to include generative AI not launching until late 2023 or early 2024. The true impact of generative AI on financial performance and competitive advantage remains to be seen, posing a question of great interest to industry watchers and participants alike.
Do you think generative AI will dominate the semiconductor industry by 2027? |
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