Hey Adopter,
By the end of this newsletter, you’ll have a clear playbook to position yourself as your team’s go-to AI expert, even without a technical background.
Your company has an AI adoption problem you can solve
87% of organizations believe AI will give them a competitive advantage. The same research shows 87% of machine learning projects never make it to production.
That gap between belief and execution is your career opportunity.
Across most companies right now, employees are quietly using ChatGPT, Gemini, and other tools without guidance. Leadership surveys suggest this “shadow AI” usage is far higher than executives realize. The result: fragmented experimentation, potential data leaks, and an “illusion of productivity” where high-volume output masks hidden rework costs.
Someone needs to bring order to this chaos. That person builds credibility, visibility, and career leverage. The role doesn’t require seniority or a technical degree. It requires curiosity and initiative.
Which raises the question: what does it take to become that person?
The AI champion profile
The AI champion role isn’t reserved for senior leadership or engineers. Many successful champions are mid-level employees: team leads, managers, executive assistants, SMB owners. What defines them is a specific combination of mindset and action.
Intellectual curiosity over credentials
Champions commit to learning the material themselves. One effective approach: use AI tools to accelerate your own AI education. ChatGPT with web plugins can summarize dense industry articles from sources like McKinsey or TechCrunch, letting you ask clarifying questions and internalize concepts faster than traditional reading allows.
Communication over technical depth
Strong champions translate complex concepts into clear, relatable terms. Your value isn’t in understanding every technical detail. It’s in helping colleagues see how AI applies to their specific work without jargon or hype.
Action over permission
Champions don’t wait for a mandate. They identify their team’s pain points, experiment with solutions, and share results openly. This proactive stance separates advocates who talk about AI from champions who demonstrate its value.
Good, but knowing the profile isn’t enough. You need to build the foundation that makes action effective.
Build AI literacy in three layers
AI literacy is the baseline capability for using AI effectively, ethically, and safely. It breaks into three components.
Technical understanding. You don’t need to code. You need a foundational grasp of how AI systems work: what machine learning is, why data quality matters, why AI produces confident-sounding errors called “hallucinations.” This understanding helps you explain to colleagues why certain outputs need verification.
Practical application. Learn prompt engineering, the skill of formulating requests that get useful results. Know what AI can and cannot do within your specific role. Understand when human judgment is non-negotiable. This practical knowledge separates smart AI users from those who copy and paste without thinking.
Ethical awareness. At Samsung, employees accidentally leaked sensitive source code and confidential meeting notes by pasting them into ChatGPT. AI champions know the risks: bias in algorithms, privacy concerns, the danger of feeding confidential data into public tools. This awareness protects both you and your organization.
With literacy established, the next question becomes: how do you prove value in a way that builds momentum?
The pilot playbook for career leverage
Action without measurement is invisible. Here’s how to make your AI work visible and valuable.
