NEW YORK — What happened: For the past two years, tech companies have marketed AI writing and coding assistants as magical multipliers for individual output. However, a comprehensive multi-industry benchmark study published this month shows that while lines of code and document counts have skyrocketed, actual product delivery timelines have barely budged.
Why it matters: For everyday knowledge workers and managers, this gap between perceived productivity and business impact is causing severe burnout. Workers feel busier generating and reviewing AI drafts, yet executive leadership wonders why top-line revenue growth per employee remains flat.
Deep dive: The trap lies in confusing artifact generation with value creation. Writing ten thousand lines of AI-generated code takes minutes, but debugging, reviewing, and integrating that code takes human experts just as long as writing it from scratch—sometimes longer because the code lacks architectural context. The bottleneck has simply shifted from creation to verification.
Report check (claims vs what is verified vs still rumor): Software tools claim a 55% boost in developer velocity; verified data shows a modest 10% speedup in greenfield projects, with zero net gain in complex legacy codebases; rumor has it that some HR departments are abandoning automated productivity tracking entirely.
Open questions: What new metrics will companies adopt when traditional measures like lines of code or pages written become entirely decoupled from business success?