Using AI to generate content without adding human context simply transfers the intellectual effort to the recipient. This creates rework, confusion, and can damage professional relationships, explaining the low ROI seen in many AI initiatives.

Leaders should anticipate active sabotage, not just passive resistance, when implementing AI. A significant percentage of employees, fearing replacement or feeling inferior to the technology, will actively undermine AI projects, leading to an estimated 80% failure rate for these initiatives.

Despite proven cost efficiencies from deploying fine-tuned AI models, companies report the primary barrier to adoption is human, not technical. The core challenge is overcoming employee inertia and successfully integrating new tools into existing workflows—a classic change management problem.

Using generative AI to produce work bypasses the reflection and effort required to build strong knowledge networks. This outsourcing of thinking leads to poor retention and a diminished ability to evaluate the quality of AI-generated output, mirroring historical data on how calculators impacted math skills.

To overcome employee fear of AI, don't provide a general-purpose tool. Instead, identify the tasks your team dislikes most—like writing performance reviews—and demonstrate a specific AI workflow to solve that pain point. This approach frames AI as a helpful assistant rather than a replacement.

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.

Instead of policing AI use, a novel strategy is for teachers to show students what AI produces on an assignment and grade it as a 'B-'. This sets a clear baseline, reframing AI as a starting point and challenging students to use human creativity and critical thinking to achieve a higher grade.

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.

Employees hesitate to use new AI tools for fear of looking foolish or getting fired for misuse. Successful adoption depends less on training courses and more on creating a safe environment with clear guardrails that encourages experimentation without penalty.