The landscape of the national workforce faces changing tides on multiple fronts, and perhaps no wave is stronger than the advent of AI in the workplace. According to a recent Heartland Forward poll conducted by Aaru, 74.4% of respondents report using AI at least occasionally in their professional and/or personal lives, and a 2025 research report from McKinsey & Company states that 92% of businesses plan to invest more in AI over the next three years. AI is quickly becoming a pillar of workplace productivity, and many fear its use in automation might displace a large portion of the workforce, as organizations such as Third Way estimate 12 million workers will need to shift career focuses due to AI by 2030. 

But AI is not the only arena where significant workforce changes are taking place.  The trades are growing, with the US Bureau of Labor Statistics estimating 4-60% growth in skilled trades by 2033. While the number of enrollees in degree-granting undergraduate institutions is projected to grow by 9% over the next five years, the total number of enrollees has decreased by 15% since 2010, placing the future of workforce preparation at a significant crossroads. More than 11,000 baby boomers reach retirement age daily, and the vast majority are expected to leave the workforce in the coming five years. As such, Gen X, Millennials and Gen Z need to be prepared to adapt to a rapidly changing and novel work landscape.

While it may seem intuitive for the remaining members of the workforce to run from jobs heavily impacted or displaced by AI toward jobs considered to be “safe” from AI automation (like trades and other non-degree requiring jobs), the conversation around the future of work is far more nuanced than this. 

To help heartlanders navigate the sea of uncertainty, Heartland Forward has created a tool highlighting the relationship between a job’s earning potential, resiliency to AI and expected job growth. 

Below is a key for understanding and interpreting the tool:

X-Axis: Median Wage for Job

• This axis indicates the median wage for jobs that do not require bachelor’s degrees. A reference line is added to indicate the median wage across all jobs.

Y-Axis: AI Resiliency (Share of Job Tasks Not Threatened by AI Automation)

• Using data from OpenAI, this visualization deems tasks as “effectively automated” if an AI tool, alone or in collaboration with other software, can cut the time needed to complete the task in half. This axis displays the percentage of job tasks that cannot be effectively automated by generative AI tools, a characteristic this article refers to as “AI resiliency”. On this visualization, higher on the y-axis means the job is more resilient to AI.

Dot size: Projected increase in employment for this job over the next 10 years

• A larger dot indicates a larger expected increase in the number of available jobs within the listed occupation over the next 10 years, per Chmura Economics’ projection. Importantly, this projection does not fully account for the incorporation of AI automation, and thus should be considered as a projection in the absence of AI automation. 

For example, dental hygienists make a median of $93,400 annually, placing them towards the right of the graph. Their AI resiliency score is 72%, meaning only 28% of their tasks can be effectively automated. Finally, the number of jobs can be expected to increase by 19,921 over the next 10 years. This mid-sized increase is represented by a mid-sized dot on the graph. 

Key Findings: 

The visualization demonstrates four key insights to guide consideration of AI’s impact on the workforce without a bachelor’s degree. Taken together, the four insights encourage members of the workforce to understand a job’s relationship to AI, so they can be better informed on how to engage with employment opportunities in an AI-driven world. Success in this new world means learning how AI will affect careers holistically and planning accordingly based on individual desired outcomes. No factor can offer clarity on its own, but multiple factors can point towards success when considered in conjunction. Consider the insights below: 

Insight #1: Supervisors’ workloads are being automated at higher rates than the workers they oversee. 

• Many highly AI-resilient jobs offer a diminished potential for advancement for workers lacking knowledge of AI. For example, construction laborers, painters and maintenance workers all find themselves with an AI resiliency above 90%, but construction managers are only 27% AI resilient, as businesses automate more managerial tasks such as accounting or communication. Job opportunities in skilled labor may offer relative stability from displacement, but career advancement opportunities may be limited for workers unfamiliar with AI tools. Should workers prefer stability, these jobs present great opportunities, but should they strive for career advancement, a strong understanding of how to leverage AI is required. 

Insight #2: AI upskilling can push back against AI displacement. 

• Popular jobs such as insurance sales agents, service sales representatives and distribution managers find themselves in the lower right section of the visualization, denoting higher-paying jobs with low AI resiliency. The jobs’ low AI resiliency may be a cause for concern, but when factoring in projected job growth (dot size), these jobs appear to be strong opportunities given the proper approach to securing them. Given the strong growth and risk of AI automation, success in these roles means building a strong digital skillset and fluency with AI tools, which may require AI upskilling efforts. As Nvidia CEO Jensen Huang puts it, “You’re not going to lose your job to AI, but you’re going to lose your job to someone who uses AI.”

Insight #3: High-paying jobs resilient to AI require hyper-specialization.

• The top-right section of the graph (including low-growth jobs such as professional athletes and commercial pilots) demonstrates the importance of a holistic understanding of AI’s impact on the workforce. AI cannot replace Patrick Mahomes, but neither can most Americans. That is to say, most high-paying and AI-resilient jobs are not a reality for the majority of the workforce, and in order to enter these fields, members of the workforce require tremendous planning and preparation. In this case, avoiding AI in the workplace involves years of training in other specialized skills.  

Insight #4: The most AI-resilient jobs are often the lowest-earning. 

• The densest section of the visualization is the top left. While jobs in the top-left section offer relative stability against AI automation, compensation can be volatile and dependent on market and governmental forces. Many of these positions are minimum-wage jobs and carry varying compensation across the country. Further, should AI displace other jobs, more members of the workforce will turn to these positions, potentially driving compensation down. A significant number of AI-resilient positions offer stability, but sacrifice earning potential, emphasizing the need to embrace AI in other opportunities. Embracing AI in the workplace does not limit earning potential or limit the workforce to specific sectors or functions in the same way that AI avoidance does. 

Conclusion:

The advent of AI has caused anxiety for many members of the workforce. According to the Heartland Forward poll, conducted by Aaru, 56% of respondents expressed anxiety about using AI in the workplace, but each member of the workforce’s relationship to AI is unique. The goal of studying the data above is not to rate jobs but to equip workers and students with the knowledge needed to make informed career decisions. 

AI upskilling opportunities and programs promoting access to alternative career pathways can help tailor careers to evolving AI needs. Heartland Forward organizes programs such as rootEd Arkansas, a partnership with Stemuli and the Connecting the Heartland Jobs Board to help members of the workforce find their path. Combining their guidance with holistic knowledge gleaned from this visualization can lead to successful careers.