The new AI jobs are here, and driving it is the fastest-growing company of all time. Mercor hires experts to train specialized AI models. When Chatgpt was introduced to the world, we discovered how powerful general AI could be, but time would tell that one-size-fits-all AI doesn’t meet every need. As companies like Mercor hire experts, entry-level jobs are reducing. When entry-level jobs disappear, we risk losing the proving ground where future managers, and leaders get their start.
Federal Reserve Chair Jerome Powell shared recent remarks citing that they have some evidence that AI is likely affecting the job market for recent college graduates but job creation in general has slowed down. Providing a glimpse of what the future of the workforce pipelines may look like. Entry level positions being augmented with senior level employees and specialized AI tools tailored to specific jobs supercharging what they’re able to accomplish.
It’s not all great for employers adopting, according to the State of AI in Business 2025 report 95% of AI pilots fail. The study revealed recurring causes behind these failures: static AI applications, misalignment, workers using AI under the radar, and lack of strategic integration. The employers who successfully integrate AI but consolidate entry level positions may receive short-term benefits but face long-term unintended consequences. The fragmentation of workforce pipelines through consolidating entry level positions creates a barrier for the workforce in developing new talent. The successful employers will redesign entry level positions but smaller employers won’t have the capacity or resources.
In workforce policy, our job is to fill gaps in the talent pipeline. The greatest challenge AI disruption presents to workforce professionals is the change of client demographics and the loss of entry level positions. Workers seeking support may no longer be first-time job seekers or individuals with low formal education, workforce boards have to prepare for this change. We’ll be serving a different type of client in the future, and the way we serve them will also change, meaning new tools, partnerships, and training models.
In Rhode Island, the Governor’s Workforce Board brought together our Labor Market Information team and graduate students from Brown University to examine the potential impact of AI on the state’s workforce. Using Felten’s study on AI occupation exposure scores, we identified which occupational groups were most vulnerable particularly those with high exposure in image and language tasks and compared these findings against our occupational employment and wage data to get a big-picture view of potential risks and pressure points. Workforce professionals need to keep an eye on highly exposed occupations that make up a considerable amount of your workforce. Talking with these employers is a great way to gauge if they are considering AI adoption.
Utilizing that quantitative and qualitative data will be essential in informing funding decisions. Job training programs that are in highly exposed occupations should incorporate AI literacy curriculum. Job training programs in occupations with less exposure present an opportunity to scale. New jobs like AI evaluators and the increase in datacenter’s should also be prioritized as new pathways for workers transitioning from traditional industries. Innovation always brings disruption and today, career progression itself is at risk. If we act quickly, we can scale our existing systems to meet this moment. Move fast, and we can strengthen the system. Move slow, and we’ll train workers for yesterday’s jobs.
