Find employers where the bottom of the ladder is still open

You are choosing a first job, not just a title. The question that matters is whether the company has a level above the one you are applying for. Ramp Economics Lab published a study on June 30, 2026 finding that firms making significant AI investments expanded workforces faster than comparable firms.

A promotion case depends on the org chart. If there is no next level, no amount of polish saves the conversation. Early-career workers should screen for the same thing before they apply: a company where the bottom of the ladder is still open.

The bottom of the ladder is visible before you apply

Use this screen in order. It separates employers that are buying AI from employers that are building work around it.

• Check spend intensity. High AI adopters spent about $33 per employee per month in the first three months after adoption, while low adopters spent about $3 per employee per month. Public job descriptions often reveal the tool stack. If the same AI platform appears in multiple roles, the spend is likely real. Stop when the budget looks large enough to create new roles, new teams, and new managers.
• Rule out token spending. Companies making modest AI investments did not show significant workforce growth. A token budget may cover a few seats, a conference talk, and a demo. It will not support a new team. Look for a budget that survives an audit and a hiring cycle.
• Count entry-level openings. Entry-level employment increased by 12% among high-intensity AI adopters. Look for repeated junior roles: associate, analyst, engineer, coordinator, or a named entry title that appears across teams. Titles that mention a new team or a foundational role are stronger than generic entry-level labels. Stop when the pattern looks like a hiring plan rather than a lone posting.
• Reject one-off pilots. A pilot can look impressive on a careers page, but it does not create a promotion case. If the only junior role is tied to a temporary project, the case may end after a short assignment. A temporary project may need a junior worker, but it may not need one next year. You can stop when you can name the reason a role is recurring, not temporary.
• Trace integration. High-intensity AI adopters added about 10% to headcount over the first two years after deploying AI. Check whether AI shows up in job descriptions, team structures, and internal mobility. Ask interviewers how the tool changes the work, not just what it does. You are done when you can point to a workflow, a new team, or a manager who owns the tool.
• Wait for slow evidence. The employment effects developed gradually, because firms needed time to embed AI, find productive uses, and expand hiring. That timing is good news for early-career candidates. Watch for repeated postings, new team names, and managers who speak about the tool in operational terms. Repeated hiring after the rollout confirms it.

The study gives the screen its numbers

Ramp Economics Lab connected Ramp corporate card and bill-pay AI spending data with Revelio Labs workforce records for 21,599 U.S. firms. The connection is what makes the screen practical. It turns a vague AI claim into a hiring signal.

A shortlist becomes a promotion case

Build a shortlist of a few firms where you can name the entry title, the team, and the manager who would own your first project. Then write the first promotion case before you apply: state the outcome you expect, the evidence you would collect, and the next level you would ask for. Aim for a short paragraph that a manager could read without asking what you mean. If the next level is unclear, ask who would approve it and what the role looks like after the first project. Do this before you spend effort on one application. A kind manager can explain the path, but the path still has to exist.