In just nine months, Citadel CEO Ken Griffin went from publicly dismissing AI as overhyped “garbage” to being “fairly depressed” by its power to automate high-skilled finance jobs. His rapid change of heart exemplifies the swift journey from skepticism to the "doom desperation" phase of the AI adoption cycle.

Convincing users to adopt AI agents hinges on building trust through flawless execution. The key is creating a "lightbulb moment" where the agent works so perfectly it feels life-changing. This is more effective than any incentive, and advances in coding agents are now making such moments possible for general knowledge work.

The perceived timeline for AI agents to build and run sustainable businesses has radically compressed. A host who dismissed the idea as impossible three months ago now considers it a real possibility. This drastic shift in expert opinion highlights the dizzying, exponential pace of advancement in agentic AI capabilities.

Investor Brent Beshore's experience demonstrates a step-function change, not a gradual evolution. His firm's agentic AI projects, which failed after months of effort, were completed in minutes using Claude Cowork just weeks later. This highlights the surprisingly rapid transition of agentic AI from a theoretical concept to a practical, value-creating tool.

Citadel CEO Ken Griffin posits that the narrative of AI causing mass white-collar job loss is primarily a hype cycle created by AI labs. He argues they need this powerful story to justify raising the hundreds of billions of dollars required for data center capital expenditures, rather than it being an imminent economic reality.

Contrary to the view that useful AI agents are a decade away, Andrew Ng asserts that agentic workflows are already solving complex business problems. He cites examples from his portfolio in tariff compliance and legal document processing that would be impossible without current agentic AI systems.

When Ken Griffin saw AI replicate the work of his PhDs, his "depression" may have been less about job loss and more about strategy. He realized Citadel's core asset—an army of elite human analysts—could be commoditized by AI, eroding a key competitive advantage.

The rapid change in perception about AI's impact wasn't caused by new models alone, but by a critical mass of technical users experiencing agentic tools firsthand. This shift from "talking" about AI's potential to "doing" real work with it, like building a website in an hour, created a cascade of recognition that abstract understanding could not achieve.

The future of financial analysis isn't job replacement but radical augmentation. An analyst's role will shift to managing dozens of AI agents that perform research and modeling around the clock, dramatically increasing the scope and speed of idea generation and validation.