Which Jobs Will Be Most Impacted by ChatGPT?
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Which Jobs Will Be Most Impacted by ChatGPT?

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Visualizing the impact of artificial intelligence on the labor market

Jobs Most Impacted by ChatGPT and Similar AI Models

On November 30, 2022, OpenAI heralded a new era of artificial intelligence (AI) by introducing ChatGPT to the world.

The AI chatbot stunned users with its human-like and thorough responses. ChatGPT could comprehend and answer a variety of different questions, make suggestions, research and write essays and briefs, and even tell jokes (amongst other tasks).

Many of these skills are used by workers in their jobs across the world, which begs the question: which jobs will be transformed, or even replaced, by generative AI in the coming future?

This infographic from Harrison Schell visualizes the March 2023 findings of OpenAI on the potential labor market impact of large language models (LLMs) and various applications of generative AI, including ChatGPT.

Methodology

The OpenAI working paper specifically examined the U.S. industries and jobs most “exposed” to large language models like GPT, which the chatbot ChatGPT operates on.

Key to the paper is the definition of what “exposed” actually means:

“A proxy for potential economic impact without distinguishing between labor-augmenting or labor-displacing effects.” – OpenAI

Thus, the results include both jobs where humans could possibly use AI to optimize their work, along with jobs that could potentially be automated altogether.

OpenAI found that 80% of the American workforce belonged to an occupation where at least 10% of their tasks can be done (or aided) by AI. One-fifth of the workforce belonged to an occupation where 50% of work tasks would be impacted by artificial intelligence.

The Jobs Most and Least at Risk of AI Disruption

Here is a list of jobs highlighted in the paper as likely to see (or already seeing) AI disruption, where AI can reduce the time to do tasks associated with the occupation by at least 50%.

Analysis was provided by a variety of human-made models as well as ChatGPT-4 models, with results from both showing below:

Jobs Categorized ByAI Exposure
AccountantsAI100%
Admin and legal assistantsAI100%
Climate change policy analystsAI100%
Reporters & journalistsAI100%
MathematiciansHuman & AI100%
Tax preparersHuman 100%
Financial analystsHuman100%
Writers & authorsHuman100%
Web designersHuman100%
Blockchain engineersAI97.1%
Court reportersAI96.4%
ProofreadersAI95.5%
Correspondence clerksAI95.2%
Survey researchersHuman84.0%
Interpreters/translatorsHuman82.4%
PR specialistsHuman80.6%
Animal scientistsHuman77.8%

Editor’s note: The paper only highlights some jobs impacted. One AI model found a list of 84 additional jobs that were “fully exposed”, but not all were listed. One human model found 15 additional “fully exposed” jobs that were not listed.

Generally, jobs that require repetitive tasks, some level of data analysis, and routine decision-making were found to face the highest risk of exposure.

Perhaps unsurprisingly, “information processing industries” that involve writing, calculating, and high-level analysis have a higher exposure to LLM-based artificial intelligence. However, science and critical-thinking jobs within those industries negatively correlate with AI exposure.

On the flipside, not every job is likely to be affected. Here’s a list of jobs that are likely least exposed to large language model AI disruption.

Jobs Least Exposed to AI
AthletesShort-order cooks
Large equipment operatorsBarbers/hair stylists
Glass installers & repairersDredge operators
Automotive mechanicsPower-line installers/repairers
Masons, carpenters, roofersOil field maintenance workers
Plumbers, painters, pipefittersServers, dishwashers, bartenders

Naturally, hands-on industries like manufacturing, mining, and agriculture were more protected, but still include information processing roles at risk.

Likewise, the in-person service industry is also expected to see minimal impact from these kinds of AI models. But, patterns are beginning to emerge for job-seekers and industries that may have to contend with artificial intelligence soon.

Artificial Intelligence Impacts on Different Levels of Jobs

OpenAI analyzed correlations between AI exposure in the labor market against a job’s requisite education level, wages, and job-training.

The paper found that jobs with higher wages have a higher exposure to LLM-based AI (though there were numerous low-wage jobs with high exposure as well).

Job ParameterAI Exposure Correlation
WagesDirect
EducationDirect
TrainingInverse

Professionals with higher education degrees also appeared to be more greatly exposed to AI impact, compared to those without.

However, occupations with a greater level of on-the-job training had the least amount of work tasks exposed, compared to those jobs with little-to-no training.

Will AI’s Impact on the Job Market Be Good or Bad?

The potential impact of ChatGPT and similar AI-driven models on individual job titles depends on several factors, including the nature of the job, the level of automation that is possible, and the exact tasks required.

However, while certain repetitive and predictable tasks can be automated, others that require intangibles like creative input, understanding cultural nuance, reading social cues, or executing good judgement cannot be fully hands-off yet.

And keep in mind that AI exposure isn’t limited to job replacement. Job transformation, with workers utilizing the AI to speed up or improve tasks output, is extremely likely in many of these scenarios. Already, there are employment ads for “AI Whisperers” who can effectively optimize automated responses from generalist AI.

As the AI arms race moves forward at a rapid pace rarely seen before in the history of technology, it likely won’t take long for us to see the full impact of ChatGPT and other LLMs on both jobs and the economy.

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This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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AI Week Wrap Report: See All the Visuals in One Place

AI Week, sponsored by Terzo, is Visual Capitalist’s in-depth exploration of the latest insights in the world of artificial intelligence.

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AI Week was our first-of-its-kind editorial event. In it, we examined the latest AI insights, including the amount each nation is spending on AI, how people utilize AI today, the skills required for a career in AI, and much more.

All these insights were drawn from the 2025 Stanford AI Index and other cutting-edge sources. All of these are available at Visual Capitalist’s AI content hub–brought to you by our partners at Terzo.

Tap Into AI Week

This week, we examined several key areas of the AI landscape in 2025.

First, we examined the state of global AI investment, discovering that the U.S. has raised nearly half a trillion dollars in private AI investment since 2013—the most of any nation. 

Following the U.S. were China and the U.K., which invested $120 billion and $30 billion, respectively, during the same period.

Patent filings serve as a means to measure innovation and leadership in the technology sector while also providing legal protection for novel ideas and inventions.

In our second post, we examined AI leadership by analyzing the number of AI patents filed by major nations. We found that China has accumulated 70% of all global AI patents, the most in recent years.

However, evidence does suggest that many of these patents were applied for and protected within China alone.

AI can be found in nearly every digital product today. So, in the third post, we explored how people utilize AI today

Here, we found that the primary reason people use AI today is for both professional and personal support. Showing that AI can assist humans in managing both their emotions and life.

However, AI continues to find many uses in content creation, learning, and creativity.

A significant aspect of the conversation surrounding AI models is the substantial amount of money tech giants are investing in their training.

We examined corporate investment in various AI models, finding that in recent years, Google has spent the most. Although data is limited, it’s believed that the company spent $192 million in training Gemini 1.0 Ultra—the highest amount across all leading models.  

Bar chart showing the estimated training cost of training AI models in 2023 and 2024.

The conversation around AI has also raised the question of whether humans or machines are faster at technical tasks.

While AI systems have historically fallen short compared to humans, the gap has narrowed considerably over the past year. Now, AI surpasses humans in specific technical skills, including advanced mathematics and visual reasoning.

A line chart showing AI vs human performance in various technical tasks

The advent of AI has also created the need for AI-based jobs. Stanford University’s 2025 AI Index examined AI job postings throughout the U.S. and found that the most sought-after skill is the programming language Python.

Computer science, data analysis, and an understanding of the Agile working methodology were also identified as valuable AI skills.

Bar chart showing the most wanted skills in AI jobs in 2024.

For our final AI Week graphic, we pit American AIs against their Chinese counterparts in a test of performance.

The graphic charts the performance of the top U.S. and Chinese AI models on LMSYS’s Chatbot Arena. It shows that while U.S. models have consistently outperformed Chinese models, the performance gap has closed dramatically in recent years.

A line chart showing U.S vs. China AI performance

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At Visual Capitalist, we craft campaigns like AI Week that tackle our client’s key challenges.

Whether by making your data more discoverable, leveraging our brand and audience of 12 million people per month, or consulting and educating around data discovery, our goal is to help you isolate the signal from the noise.

If you want to learn how companies like Terzo, BlackRock, MSCI, and Morningstar grew their brands by partnering with Visual Capitalist, contact us today.Use This Visualization

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