Which Jobs Will Be Most Impacted by ChatGPT?
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.
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 By||AI Exposure|
|Admin and legal assistants||AI||100%|
|Climate change policy analysts||AI||100%|
|Reporters & journalists||AI||100%|
|Mathematicians||Human & AI||100%|
|Writers & authors||Human||100%|
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|
|Large equipment operators||Barbers/hair stylists|
|Glass installers & repairers||Dredge operators|
|Automotive mechanics||Power-line installers/repairers|
|Masons, carpenters, roofers||Oil field maintenance workers|
|Plumbers, painters, pipefitters||Servers, 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 Parameter||AI Exposure Correlation|
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.
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.
The Future of Supply Chain Automation
As COVID-19 disrupts global supply chains, we take a look at how industries are investing in automation—and what this is tells us about the future.
The Future of Supply Chain Automation
As Amazon continues to set the bar for efficiency by integrating an astounding spectrum of automation technology, it’s becoming increasingly apparent that traditional supply chain models are ripe for disruption.
For this reason, companies around the world are now rethinking their warehouse and distribution systems, with automation taking center stage.
Today’s infographic from Raconteur highlights the state of automation across global supply chains, while also providing an outlook for future investment.
Long Time Coming
Let’s start by taking a look at what supply chain technologies are priorities for global industry investment in the first place:
|Rank||Technology||% of Companies* Investing in Tech|
|#3||Internet of things||41%|
|#14||Virtual reality and digital twins||6%|
*Based on survey of supply chain professionals in retail, manufacturing, and logistics fields
As seen above, warehouse automation has already received more investment (55%) than any other supply chain technology on the list, as companies aim to cut delivery times and improve overall margins.
Interestingly, other areas receiving significant investment—such as predictive analytics, internet of things, or artificial intelligence—are technologies that could integrate well into the optimization of supply chain automation as well.
Smoothing the Transition
While fully automated supply chains in most industries may still be a few years away, here is how companies are investing in an automated future today:
|Timeline For Acquiring New Automation Tech||% of Warehouse Managers Surveyed|
|Have, looking to upgrade||8%|
|Within 12 months||10%|
|One to three years||21%|
|Three to five years||8%|
|Over five years||3%|
According to the above data, over 70% have already integrated automation technology, or are planning to within the next five years. On the flip side, over a quarter of warehouse managers are not currently looking to integrate any new automation tech into their operations at all.
Adoption Rates and Growth
As supply chain automation gains momentum and industry acceptance, individual processes will have varying adoption rates.
Take order fulfillment, for instance. Here, only 4% of current operations are highly automated according to a recent survey from Peerless Research Group:
|Order Fulfillment Operations (Picking and Packaging)||Percentage of Respondents|
|A mix of automated and manual processes||42%|
|Mostly or all manual||49%|
Meanwhile, 49% of operations were primarily manual, illustrating potential for growth in this particular area.
It’s worth noting that other individual supply chain components, such as conveyor belts, storage, automated guided vehicles, and shuttle systems, will all have differing trajectories for automation and growth.
Post-COVID Supply Chains
The COVID-19 pandemic has shown us that complex supply chains can become fragile under the right circumstances.
As supply chains see increased rates of automation and data collection becomes more integrated into these processes, it’s possible that future risks embedded in these systems could be mitigated.
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