As employees shift from typing to speaking to their AI assistants, their work-related commands become audible to colleagues and managers. This creates a passive form of monitoring, making it easier to discern whether an employee is focused on productive tasks or distracted by non-work activities like social media.

To determine if an employee critically engaged with AI-generated content, bypass reading the lengthy document. Instead, directly question them on its substance. Their ability to confidently defend, elaborate on, and explain the material is the true test of their understanding and ownership of the work.

A gap is growing between employees who master AI tools and those who don't, creating productivity disparities. Leaders must formally integrate AI competency into job expectations and performance reviews to motivate adoption and manage talent effectively.

The CEO of Superhuman argues that the threshold for acceptable AI use in writing is situational. AI detection tools should be used not to enforce a universal ban, but to assess if the level of AI generation aligns with the context and the audience's expectations, much like calculator use varies by exam.

Senior leaders find AI accelerates work but encourages low-quality, uncritical outputs—a phenomenon called 'AI sloth'. To maintain standards, some build AI personas embodying their own perspective, which teams use to vet work before submission, counteracting the deluge of 'junk'.

CEO Luis von Ahn walked back his policy of evaluating employees on AI usage. He found it encouraged performative adoption—"using AI for AI's sake"—rather than genuine impact. The key lesson is to evaluate an employee's overall contribution, not their mandatory use of a specific tool.

Recognizing that providing tools is insufficient, LinkedIn is making "AI agency and fluency" a core part of its performance evaluation and calibration process. This formalizes the expectation that employees must actively use AI tools to succeed, moving adoption from voluntary to a career necessity.

Research highlights "work slop": AI output that appears polished but lacks human context. This forces coworkers to spend significant time fixing it, effectively offloading cognitive labor and damaging perceptions of the sender's capability and trustworthiness.

To accelerate its internal AI transformation, Meta is now grading employees on their use of company-provided AI tools as part of their performance reviews. This tactic moves AI from an optional productivity enhancer to a mandatory part of the job, creating powerful incentives for adoption and cultural change across the organization.