Key Takeaways
- The boom in artificial intelligence is creating many new tech jobs but also widespread confusion over job titles.
- Companies use numerous different titles (up to 40, according to LinkedIn) for very similar AI-focused roles.
- This ambiguity makes it difficult for job seekers to understand positions and for employers to attract the right talent.
- Nearly a quarter of new U.S. tech jobs this year require AI skills, based on research from the University of Maryland and LinkUp.
- Despite the confusion, demand for professionals with AI expertise is high, and they tend to find jobs faster.
The tech job market is bustling with opportunities, especially in artificial intelligence, but finding the right fit has become tricky.
As companies race to adopt AI, they’re creating a flurry of new job titles. However, there’s little consistency, leading to confusion for those looking for work.
Roles like “AI engineer,” “machine learning developer,” and “data architect” might sound different but often describe similar responsibilities. This lack of clear definitions is a growing challenge.
Karin Kimbrough, LinkedIn’s chief global economist, highlighted this issue in an interview with the Wall Street Journal, noting the sheer number of titles used for comparable positions.
Research confirms the surge in AI demand. The UMD-LinkUp AI Maps project found that nearly 25% of new tech jobs posted in the U.S. this year seek candidates skilled in artificial intelligence.
Job seekers like Jack McVickar find the landscape baffling. He told the Wall Street Journal that “the titles are all over the place,” forcing him to scrutinize keywords and contact companies directly to understand what a role actually involves.
Employers are also grappling with this. They want specific yet flexible titles for roles that are still evolving rapidly alongside the technology.
Don Vu, chief data and analytics officer at New York Life, mentioned that defining these new roles is uncharted territory. “Is this an AI manager? Is it an AI coding agent?… There’s a lot of new titles that didn’t exist before,” he explained.
Many companies look to tech giants for guidance on naming conventions, hoping familiar titles will attract candidates.
Even established roles are changing. Vu noted the traditional data scientist job is increasingly blending with AI engineering, demanding stronger software development skills.
Despite the naming chaos, the demand for people with AI skills is undeniable. LinkedIn data shows these professionals get hired about 30 percent faster than others.
While job titles in tech have always evolved, Kimbrough told the Wall Street Journal the current pace is “pretty stunning,” with LinkedIn finding that roughly 20% of Americans starting new jobs in the past year have titles that didn’t exist at the turn of the century.
