Stewardship Ensures AI Serves Human Flourishing
As AI generates more of the first drafts of code, content, financial projections, and strategic recommendations, stewardship becomes the most consequential human skill in the economy.
Stewardship is the capability of evaluating, correcting, and governing AI output before it reaches the world. To borrow a trucking analogy, it is the final mile delivery to the consumer. All of the complexity upstream becomes irrelevant if the wrong product, or damaged product, is what finally gets delivered.
Stewardship is the human who reads the AI-generated report and catches the error prior to that error getting to the customer. It is the difference between a successful delivery and an unsuccessful one. It can save the company money, preserve brand integrity, maintain trust, and ensure safe and secure operations. An organization that does not promote stewardship will not handle AI responsibly. One of the main tools of a steward is an audit.
When AI generates code, a human needs to review it for security vulnerabilities and inference errors the model may not catch. When AI drafts a response to a customer complaint, a human needs to read it for hallucinations, omissions or poor judgment (yeah that other pillar). When AI produces financial projections, a human needs to make sure that the assumptions are sound and that the model was trained on the right data. When AI recommends operational changes, a human needs to review and approve those changes as compared to what is happening on the ground.
Stewardship requires an outside perspective … two sets of eyes are better than one. It requires domain expertise. And in a corporate world where AI increasingly blurs functional lines, it also requires humility: a willingness to slow down, seek counsel, and involve people with different skills and experience. Borrowing from the world of safety - it sometimes requires a WORK STOP, even when stopping costs time and money.
And for those skeptical of AI, stewardship is precisely how trust is built. Every time a steward catches an error before it reaches customers the system becomes more reliable. Every time someone verifies that the output aligns with reality, confidence grows. Stewardship is how AI becomes useful without becoming dangerous or untrustworthy.
So, what does Stewardship look like in practice? YLCJ believes it looks like (1) reviewing AI-generated code or process changes before the changes go into a production / live environment; (2) auditing AI-drafted content for context the model missed and gaps that could expose the company; (3) reviewing financial projections and asking hard questions about the assumptions and data sources before they make their way to the board or outsiders; (4) checking strategic and tactical recommendations against macro- and micro-environment.
The common thread: you oversee the AI. And that act of stewardship, of exercising the Biblical call to “fill the earth and subdue it, and have dominion over” creation in service of human flourishing, is uniquely human.