A provocative new report from Citrini Research paints a dystopian picture of AI's economic impact, projecting that autonomous AI agents could double unemployment rates and slash stock market valuations by over a third within just two years. The analysis, framed as a dispatch from 2028, challenges the tech industry's relentless push toward AI automation with a sobering question: what happens when the efficiency gains become economic catastrophe?
Citrini Research just dropped a bomb on the AI hype cycle. The firm's latest analysis imagines a report written in 2028, looking back at how the rapid deployment of AI agents triggered an economic meltdown that doubled unemployment and wiped out more than a third of stock market value. It's a stark counternarrative to the productivity paradise promised by OpenAI, Microsoft, and Google as they race to put autonomous AI systems in every workplace.
The timing couldn't be more pointed. Just as enterprises are scaling up AI agent deployments - systems that can autonomously handle customer service, write code, manage schedules, and execute complex workflows - Citrini Research is asking the uncomfortable question everyone's been avoiding: what happens when all those efficiency gains translate into massive job losses?
The report's framework is deliberately provocative, using a future-backward approach to trace how today's decisions could cascade into tomorrow's crisis. By imagining the aftermath rather than just modeling probabilities, Citrini Research forces readers to confront the human cost of automation in concrete terms. Doubled unemployment doesn't just mean statistics - it means millions of workers displaced faster than the economy can absorb them.
What makes this analysis particularly relevant right now is the breakneck pace of AI agent adoption. Microsoft has been aggressively pushing its Copilot agents across enterprise software. Google is embedding AI agents into workspace tools used by millions. recently showcased agents that can perform multi-step tasks with minimal human oversight. The technology has moved from research labs to production environments in months, not years.
