Providing access to AI education isn't enough. For training to succeed, a specific person or team must own the program's goals—like time saved or new projects launched—not just course completion rates.
Hiring an AI change management consultant creates value based on organizational readiness, not the project phase. Many companies are not prepared for strategic change, instead focusing only on immediate tool adoption like ChatGPT licenses.
The most compelling way to demonstrate AI skills to an employer is to build something. Creating custom GPTs for personal productivity or simple apps proves practical problem-solving ability far more effectively than a list of certifications on a resume.
Using AI to save time on content can backfire if the audience expects authenticity. The value in human-created art, writing, or presentations often lies in the invested energy and personal story, which AI shortcuts can devalue in the customer's eyes.
Anthropic's AI constitution was largely built by a philosopher, not an AI researcher. This highlights the growing importance of generalists with diverse, human-centric knowledge who can connect dots in ways pure technologists cannot.
If an AI pilot fails, it's likely a cultural issue if the technology was personalized for specific teams with clear use cases. When tools are made easy to adopt but usage remains low, the barrier isn't the tech; it's the team's mindset.
To assess a candidate's ability to use AI as a thinking partner, have them solve a problem with an LLM. The key is observing their follow-up prompts and their ability to guide the AI step-by-step, rather than just accepting the initial output.
When one employee leverages AI to generate massive value (e.g., a new million-dollar revenue stream), standard compensation is inadequate. Companies need new models, like significant one-time bonuses, to reward and retain these high-impact individuals.
The opportunity cost of building custom internal AI can be massive. By the time a multi-million dollar project is complete, off-the-shelf tools like ChatGPT are often far more capable, dynamic, and cost-effective, rendering the custom solution outdated on arrival.
The most effective chatbot users are those with deep domain expertise who can ask the right questions, guide the AI, and critically assess its output. This dynamic creates a significant hiring and development challenge for entry-level workers who lack this contextual knowledge.