Companies claim AI is revolutionary for productivity, yet economic studies, including one by OpenAI itself, show no correlation between spending on AI and increased revenue per employee. The hype about transformative efficiency is not reflected in actual economic output.

Developers claiming 10x speedups from AI often aren't 10x faster on their core tasks. Instead, they're tackling new side projects that were previously impossible, creating a perception of "infinite" speedup. However, these new tasks are often less economically valuable, inflating the true productivity gain on business-critical work.

According to OpenAI co-founder Andrej Karpathy, the true impact of AI code generation is less about a linear speedup on existing tasks. Instead, it expands the scope of what's feasible, allowing engineers to attempt projects they would have previously deemed not worth the effort or beyond their skillset.

A critique from a SaaS entrepreneur outside the AI hype bubble suggests that current tools often just accelerate the creation of corporate fluff, like generating a 50-slide deck for a five-minute meeting. This raises questions about whether AI is creating true productivity gains or just more unnecessary work.

Human intuition is a poor gauge of AI's actual productivity benefits. A study found developers felt significantly sped up by AI coding tools even when objective measurements showed no speed increase. The real value may come from enabling tasks that otherwise wouldn't be attempted, rather than simply accelerating existing workflows.

Productivity models often wrongly assume time saved by AI is redeployed into other work. In reality, many employees use efficiency gains to finish early. This 'human slack' factor dampens macro-level productivity gains, except in highly driven fields like tech, where workers use it to work even more.

A growing gap exists between AI's performance in demos and its actual impact on productivity. As podcaster Dwarkesh Patel noted, AI models improve at the rapid rate short-term optimists predict, but only become useful at the slower rate long-term skeptics predict, explaining widespread disillusionment.

Instead of leading to less work, agentic AI tools are causing users to work longer hours. The core reason is psychological: the tools are so effective at generating output that the opportunity cost of not working feels immense. This creates a hybrid of exhilaration and anxiety where time itself is the bottleneck.

A significant disconnect exists between AI's market valuation, which prices in massive future GDP growth, and its current real-world economic impact. An NBER study shows 80% of US firms report no productivity gains from AI, highlighting that market hype is far ahead of actual economic integration and value creation.