The job of an individual contributor is no longer about direct execution but about allocation. ICs now act like managers, directing AI agents to perform tasks and using their judgment to prioritize, review, and integrate the output. This represents a fundamental shift in the nature of knowledge work.
AI's ability to generate ideas and initial drafts for a few dollars removes the high cost of entry for new projects. This "ideation" phase, once proven successful, often justifies hiring human experts for full execution, creating net-new work that was previously unaffordable.
AI makes tasks cheaper and faster. This increased efficiency doesn't reduce the need for workers; instead, it increases the demand for their work, as companies can now afford to do more of it. This creates a positive feedback loop that may lead to more hiring, not less.
Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.
AI models lack access to the rich, contextual signals from physical, real-world interactions. Humans will remain essential because their job is to participate in this world, gather unique context from experiences like customer conversations, and feed it into AI systems, which cannot glean it on their own.
When transitioning Box to be "AI first," CEO Aaron Levie explicitly communicated that the goal was not to reduce headcount or cut costs. Instead, he framed AI as a tool to increase company output, speed, and customer service, which successfully aligned employees with the new strategy by removing fear.
Box CEO Aaron Levie advises against building complex workarounds for the limitations of cheaper, older AI models. This "scaffolding" becomes obsolete with each new model release. To stay competitive, companies must absorb the cost of using the best available model, as competitors will certainly do so.
Unlike the cloud-era "digital transformation," which often didn't change core employee workflows, the AI transformation is universal. It changes how every knowledge worker operates daily, making the shift more profound and akin to the move from paper to computers, fundamentally altering the nature of work itself.