Identifying Occupations Transformed by AI: The Five Criteria

AI is rapidly reshaping jobs and work, displacing some, creating new roles, and transforming tasks through automation or augmentation. While uncertainty remains about AI’s overall workforce impact, our research identifies five key criteria indicating which occupations are most susceptible to AI-driven transformation:

1. Require College Education. 

Workers employed in the US with a bachelor’s degree or more, or some college education are more exposed to AI than those with less formal education. 

*Data and Graph from Pew Research Center

2. High Skill and High Paying. 

Occupations most vulnerable to AI, particularly GenAI (yelllow), tend to be higher paying than those impacted by previous waves of automation (blue). While the data connects high-paying jobs to greater vulnerability, this is likely tied to the nature of these roles as high skill or knowledge work jobs. Occupations such as Legal, Computer and Mathematics, and Architectural and Engineering require advanced expertise and credentials.

*Data and Graph from Burning Glass Institute: "Generative Artificial Intelligence and the Workforce"

3. Rely on Technology.

The AI – Enabled ICT Workforce Consortium (led by member Accenture) predicts that over 91.5% of Information and Communications Technology job roles they analyzed will experience either high (more than 70% of principal skills affected) or moderate (between 50% and 70% of principal skills affected) transformation due to advancements in AI. 

4. Use Analytical or Data Skills. 

AI, particularly Generative AI, can automate a wide range of tasks, especially those that are routine, repetitive, or data-related, such as data entry, processing, predictive analytics, and administrative functions. Examples include:

  • Marketing and Communications: AI can streamline marketing efforts by analyzing market trends, conducting research, collecting data, and even drafting communications.
  • Product Development: AI can evaluate data on user preferences and purchase history to recommend new product features or improvements.
  • Software Development: AI can efficiently analyze, clean, and label vast amounts of data, speeding up the development process.

5. Large or Fast-Growing Occupations. 

The occupations that have been the fastest-growing over the past decade have been data-intensive ones.  As AI is more likely to transform occupations that require data-related skills and tasks, AI is likely to transform/impact some of the fastest-growing occupations. 

*Data and Graph from Burning Glass Institute: "Data Science is for Everyone"

What occupations meet the criteria for AI transformation? 

It is no surprise that tech and engineering occupations meet the criteria for AI transformation as they require a college degree, are high skill and high paying, heavily use technology, require data skills and are fast growing. We’re also digging into front-line roles like sales and marketing and professional and financial services roles, as they also exhibit the factors that make them most susceptible to AI transformation––meaning that we need to be rethinking how we educate and train for these professions of the future.

More from Bridging Business and Education

Rewriting the Talent Compact: Four Takeaways Shaping Our Work Ahead

For decades, the relationship between higher education and employers rested on a primary handoff: colleges prepared students, employers hired them and taught them the job, and one launch carried a career. That model no longer holds. AI is reshaping work, and most people will need to reskill multiple times across their working lives. Read on for key themes and actions to move us forward coming out of the BHEF Fall Convening: A New Talent Compact for a Changing Economy.

Why Every College Needs a Partnership Pitch- And How to Build One

A partnership pitch isn’t a script that everyone at an institution needs to memorize. It’s a shared set of messages that answer a few fundamental questions. These messages can be adapted for nearly any business engagement setting or industry context: a one-on-one conversation, outreach email, introductory meeting, one-pager, slide deck, website, or even an unexpected conversation with a business partner at an event. Read on for tips and examples from Tech Talent Accelerator 3.0 participating institutions on creating a partner pitch.

Lost in Translation – Navigating the Work-Integrated Learning Landscape

In practice, there is limited agreement on the minimum characteristics that define work-integrated learning models, and without greater consistency in how these experiences are defined and communicated, it becomes more difficult for employers, higher education institutions, and learners to understand the value of these experiences. A shared common language is needed.

Five Reasons Businesses Are Partnering with Higher Education for AI Talent

What’s driving the investment of time, attention, and resources in business and higher education partnerships? These five reasons and actionable recommendations are grounded in insights gathered from our sixteen Pilot Grant Tech Talent Accelerator 3.0 industry partnerships in Connecticut, with far-reaching implications for other states, businesses, and higher education institutions across the country. 

How AI and Industry Demand Are Reshaping the Critical Minerals Workforce

AI and critical minerals are converging, and higher education is rising to meet the moment.

Seven Strategies to Become an Employer’s Partner of Choice

Fewer than 1 in 5 higher education leaders are fully executing on an industry partnership strategy. That gap is costing learners, employers, and regional economies. That's why BHEF developed Industry Partnerships that Last: A Playbook for Higher Education — a practical guide to building, structuring, and sustaining partnerships that actually work. Here are 7 actionable strategies.