AI stagnation: The gap between AI investment and AI adoption

A recent survey conducted by Censuswide on behalf of Red Hat polled 609 IT managers across the United Kingdom and other major markets. More than 80% of IT managers reported an urgent AI skills shortage, mainly in areas such as generative AI, large language models (LLMs), and data science. This is up from 72% last year.

The need to sell AI, the need to consume AI, and the inability to do so lead to what I’m calling “AI stagnation,” a complex issue that is confounding many in the AI space, including yours truly.

AI at a near standstill

Technology providers continue to pour resources into AI development, creating advanced tools, platforms, and infrastructure. Tech giants’ and startups’ investments in AI are reaching unprecedented heights, with industry watchers predicting more than $120 billion in funding for AI startups in 2024 alone. The contributions of major players, such as Nvidia, OpenAI, and Anthropic, to a thriving AI market are reminiscent of the dot-com era. This type of capital influx is typically a positive indicator, signaling robust interest and faith in the potential for future returns.