OpenAI’s CFO Sarah Friar recently made a straightforward point that every worker and job-seeker should take seriously: AI is already reducing the need for certain roles, but mostly the repetitive, low-value ones. In her own finance team, procurement used to run about 2,800 credit checks a year. Those checks were “pretty mundane.” Now an AI model handles them. Cost per check dropped from roughly $200 to 17 cents. The company needs fewer people doing that specific work—and the work that remains is higher-value.
What this means for your career
Friar’s view is pragmatic rather than alarmist. AI is excellent at scale, consistency, and rote processes. Tasks that follow clear rules, involve heavy data checking, form-filling, basic verification, or repetitive analysis are the first to shrink. Credit checks are just one example; similar patterns are appearing in accounting, basic research, routine reporting, simple compliance reviews, and many entry-level data or administrative roles.
At the same time, she notes that this frees people for “work at the edge”—the judgment calls, complex problem-solving, relationship-building, strategy, and creative decisions that still require human intelligence. The model does the volume work more accurately and cheaply; people do the thinking that creates real advantage.
Other AI leaders are more pessimistic. Anthropic’s Dario Amodei has warned that AI could eliminate a large share of entry-level white-collar jobs. Geoffrey Hinton has said those predictions are “probably right” and that the technology is improving fast. Both perspectives can be true at once: many routine jobs will shrink or disappear, while demand grows for people who can use AI well and add the judgment, creativity, and interpersonal skills machines still lack.
Practical steps to stay valuable
1. **Audit your current work.** List the parts of your job that are repetitive, rules-based, or purely data-processing. Those are the tasks most likely to be automated or heavily assisted. Identify the parts that require judgment, context, client relationships, creative problem-solving, or ethical decisions—those are your leverage points.
2. **Become the person who uses the AI, not the person competing with it.** Learn the tools relevant to your field (whether OpenAI’s products, industry-specific platforms, or internal systems). The workers who thrive will be those who can prompt effectively, check outputs critically, and combine model speed with human insight.
3. **Move toward “edge” skills.**
- Analytical and strategic thinking
- Complex communication and stakeholder management
- Domain expertise that lets you interpret AI results correctly
- Creativity, original problem framing, and ethical judgment
- Cross-functional collaboration and leadership
4. **If you’re early in your career, be selective about pure entry-level rote roles.** Positions that exist mainly to process volume (basic credit checks, simple data entry, formulaic reporting) are shrinking. Look for roles that already mix process work with analysis, client contact, or project ownership so you can grow into the higher-value parts.
5. **Treat continuous learning as non-negotiable.** The technology is improving quickly. The people who stay relevant will keep updating both their technical fluency with AI and their deeper professional expertise.
AI is not eliminating all work—it is reallocating it. The mundane volume tasks are becoming cheaper and faster for machines. That creates pressure on roles built around those tasks and opportunity for people who can operate at a higher level of judgment and creativity. Use the tools, protect and develop the uniquely human parts of your contribution, and position yourself where intelligence (not just processing) is the scarce resource.
If your current role is heavy on repetitive processes, start shifting the balance now. The CFOs and AI researchers are already describing the direction of travel. The workers who adapt will be the ones still in demand.