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How To Cut Through The Hype And Get Value From AI

Nov 14, 2024 - forbes.com
The article discusses the financial impact of artificial intelligence (AI) and the debate surrounding its profitability. While some business leaders, like Baidu CEO Robin Li, believe we are in an AI bubble, others, like OurCrowd CEO Jon Medved, see real financial promise in AI. The AI market in 2024 is valued at $214 billion and projected to reach $1,339 billion by 2030. AI companies generate revenue through AI-as-a-service offerings and AI-enabled applications. However, the high operational costs of AI technology and the need to demonstrate real value quickly present challenges to sustainable profitability.

The article further explores the return on investment (ROI) for AI, citing Nvidia's success with hardware and infrastructure. AI-as-a-service offerings, like OpenAI's AIaaS and Google Cloud AI, and AI-enabled applications, like ChatGPT and Notion AI, are highlighted as significant revenue drivers. However, the costs of running these platforms are substantial, and companies need to balance affordability for customers with high AI processing and data management costs. The path to sustainable profitability may depend on efficient cost and pricing control and prioritizing human capital.

Key takeaways:

  • The AI market in 2024 is valued at an estimated $214 billion in revenue and is expected to grow to $1,339 billion by 2030, driven by expanding enterprise budgets for AI tools, rising investments in AI startups and the increasing number of AI-powered applications.
  • AI companies generate revenue through hardware and infrastructure, AI-as-a-service offerings, and AI-enabled applications. For instance, OpenAI's AIaaS offering and ChatGPT application are significant revenue streams for the company.
  • Despite the promising revenue figures, the costs of running AI platforms are substantial, with the need for advanced processors, high research and development costs, and data management expenses.
  • For AI companies to achieve sustainable profitability, they need to navigate the high operational costs of the technology and the pressure to demonstrate real value quickly. This could involve efficient cost and pricing control, prioritizing human capital, and following global regulatory frameworks like the ISO/IEC AI standards.
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