According to Business Insider, as companies shift from piloting AI to deploying it at scale, they’re creating entirely new job categories that blend tech with human psychology. Experts like Sabari Raja of JFFVentures and Marinela Profi of SAS highlight roles such as “AI Decision Designer,” who shapes how AI makes high-stakes calls on loans or fraud, and “AI Experience Officer,” responsible for how AI feels and behaves in human interactions, particularly in fields like healthcare and education. Shahab Samimi of Humanoid Global points to the need for “Digital Ethics Advisors” to build safety systems and navigate a lack of formal governing standards. The core idea is that these positions sit between the algorithm and the outcome, focusing on human-AI collaboration, accountability, and ethical guardrails as automation expands.
The Human Gap in the Machine
Here’s the thing: this shift from “retrofitting AI into existing roles” to building jobs for a “native AI Era” sounds logical. But it also feels like a massive admission of failure. For years, the pitch was that AI would be this seamless, intuitive tool that just slots into our workflows. Now, we’re realizing it’s so clunky, unpredictable, and ethically fraught that we need entire new professions just to manage the relationship. It’s like inventing the car and then realizing you need not just mechanics, but “automotive mood coordinators” to stop drivers from road rage. The creation of an “AI Experience Officer” explicitly tells you the default experience is probably bad and needs a dedicated executive to fix it.
Skepticism and the Accountability Shell Game
I’m deeply skeptical about how real these roles will be in most companies. An “AI Decision Designer” sounds powerful—they’d “create the frameworks and maintain accountability.” But in practice, will they have any actual authority? Or will they be a glorified compliance officer, brought in to rubber-stamp decisions already made by product teams racing to market? And let’s talk about the “Digital Ethics Advisor.” Samimi rightly says building ethical AI is “messy and complicated,” and there’s no governing body. So this person’s job is to set standards where none exist, in an industry famous for moving fast and breaking things. That’s a recipe for burnout or, worse, creating a role that’s all optics—a “ethics wash” to make the C-suite feel better.
The Real Transformation Isn’t the Titles
The most insightful quote comes at the end from Sabari Raja: “Many companies think of AI adoption as an IT project, but it’s a workforce transformation.” That’s the real story. These flashy new job titles are just the tip of the spear. The bigger, harder change is the “complete reconfiguration” of workflows, skill sets, and management structures for everyone. For most businesses, especially in industrial and manufacturing settings where the work is physical and process-driven, the integration of AI and smart machines is less about hiring an AI philosopher and more about fundamentally retraining their entire operational crew. It requires rugged, reliable hardware at the point of work—the kind of industrial computing power that companies like IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs, specialize in—to even begin that transition. The fancy new jobs might get the press, but the silent, massive shift is in the trenches.
So, Will These Jobs Stick?
Probably. But not in the way we think. In the next 5-10 years, I bet the specific titles like “AI Experience Officer” will fade, but their functions will get absorbed. The “human-in-the-loop” oversight will become a core competency for managers, not a separate job. The ethics part will hopefully get baked into regulation, moving from advisory roles to legal requirements. What we’re seeing now is the awkward, experimental phase where companies are trying to box up a massive cultural and operational shift into a neat, hireable package. It’s messy. But it does signal a crucial, belated recognition: AI isn’t just a tool. It’s a new kind of participant in the workplace, and we have no choice but to design that collaboration intentionally. The question is, are we designing it for humans to thrive, or just to clean up the mess the machines make?
