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View all search resultsWhy business leaders are souring on AI
Despite record investment, investors, executives and corporate boards are growing increasingly skeptical that AI will deliver significant productivity gains anytime soon.
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A man walks past signage for the World Artificial Intelligence Conference (WAIC) on July 16 in Shanghai, China. (AFP/Hector Retamal)
A
fter years of soaring expectations, the artificial intelligence industry is approaching a moment of reckoning. Despite record investment, investors, executives and corporate boards are growing increasingly skeptical that AI will deliver significant productivity gains anytime soon.
AI skepticism is driven by several factors. For starters, the cost of using large language models (LLMs) continues to climb, often with few measurable benefits. According to the Silicon Data Token Expenditure Index, LLM spending has doubled since 2025, even though the cost per token has fallen by more than 90 percent over the past three years.
In other words, AI usage has grown so rapidly that lower token prices have failed to reduce overall spending, leaving companies paying more than ever. Economy-wide, the Federal Reserve Bank of Atlanta estimates that firms will increase AI spending by 50 percent in 2026, to US$280 billion.
This spending surge has exposed a fundamental asymmetry. As companies come under growing pressure to justify rising AI costs, LLM providers have become increasingly dependent on token consumption to sustain revenue growth and support lofty market valuations.
The obvious question is when - and if - these investments will begin generating meaningful productivity increases or cost savings. A 2025 MIT report found that 95 percent of generative AI pilot programs, including many intended to accelerate revenue growth, have failed to achieve their stated objectives.
Another source of concern is the growing risk that companies deploying AI tools may inadvertently hand over their proprietary intellectual property, data and business know-how, accumulated over decades, to major model providers like OpenAI and Anthropic. While licensing agreements and contractual safeguards limit exposure, LLM providers may nevertheless gain access to information that reveals how companies create, price and capture value.
The dispute between Anthropic and Figma illustrates this tension. Figma partnered with Anthropic to develop AI-powered design assistants, but the relationship came under strain when reports emerged that Anthropic was developing a competing tool, which it subsequently launched as Claude Design.
