Generative AI will likely affect a wide range of professions and create new occupations. Morgan Stanley economists break down the revolutionary technology’s near-term impacts on labour and the economy.
One of the most pressing questions for employers and employees alike is how and to what degree the emergence of generative artificial intelligence will change the way people work.
Revolutionary technologies have the power to create new economic activity and entirely new professions, and natural-language chatbots that use AI to create text, images, code and audio with human-like fluency are expected to be especially transformative.
Generative AI—hailed as one of the most disruptive technologies since the smartphone—is expected to have wide-ranging effects on labour and the broader economy. In a recent report, Morgan Stanley Research economists gauged the ground-breaking technology’s near-term reverberations. Their conclusion: More than 40% of occupations might be affected by generative AI in the next three years.
“It is impossible to know for sure, but current generative AI technologies could affect as much as a quarter of the occupations that exist today, meaning that AI has the potential to augment them now or in the future, with associated labour costs that could reach at most US$2.1 trillion,” says Seth Carpenter, Global Chief Economist for Morgan Stanley. “Within three years, this might rise to 44% of occupations affected and US$4.1 trillion of associated labour costs.”
Here’s where Morgan Stanley Research thinks generative AI for work could make the biggest ripples:
Balancing Disruption
Generative AI will increasingly augment or automate job roles and tasks, but accurately forecasting any resulting labour displacement remains a challenge. It has the potential for positive disruption—for example, the creation of completely new roles, or increased demand for specific jobs as costs fall and efficiencies rise. However, Generative AI could also cause negative disruption, such as AI replacing humans in certain functions. “As with any period of technological innovation, predictions of related job losses have generally proven unfounded amid increased productivity, lower prices and new products and services,” says Carpenter.
It is too soon to predict how rapidly these technologies will be adopted, analysts caution, with a recent AlphaWise survey of CIOs finding that companies are in the early stages of dealing with the legal, regulatory and implementation issues of generative AI. Of the survey respondents who said they plan to use generative AI in the future, most said they expected initial projects to be implemented in 2024 or 2025.
On the policy front, meanwhile, the White House has recently weighed in, with labour issues featuring in an executive order signed by President Joe Biden on Oct. 30, 2023, aimed at "seizing the promise and managing the risks of artificial intelligence." It calls for a report on AI’s potential labour-market impacts, as well as "best practices to mitigate the harms and maximize the benefits of AI for workers" in terms of job displacement and labour standards.
Productivity’s Macro Impacts
The adoption of new technologies generally boosts productivity, affecting not just labour markets but inflation, interest rates globally when new technologies diffuse around the World.
In the short term, increased labour productivity could spur faster GDP growth and lower inflation. In the U.S., for example, the Federal Reserve could cut interest rates in the short run either because it decides to boost economic activity to a new higher production capacity, or inflation slows due to faster productivity growth. However, in the long-run, interest rates might rise amid sustained productivity growth and higher investment demand.
“Over the long term, labour disruptions could herald an unprecedented demand for reskilling displaced workers and require a significant increase in capacity for retraining that may depend on public-private partnerships to address,” Carpenter says.
To that end, he thinks some combination of corporate investment in reskilling and retraining programs together with government social-insurance programs are more likely to emerge as support mechanisms for workers impacted or displaced by generative AI, rather than more sweeping reforms such as universal basic income.
Indeed, the recent executive order calls for the US Labor Department to identify and study options for strengthening federal support for workers facing labour disruptions, including from AI.
In terms of hiring, a shift to prioritising skills—especially those that are more difficult to replace with AI models—over credentials or occupation seems likely in areas most affected by job displacement.
| Top Skills Likely Difficult to Automate | Top Skills Likely Easier to Automate |
|---|---|
| Management of Personnel Resources | Information Gathering/Factual Search |
| Complex Problem Solving | Content Creation |
| Negotiation | Data Analysis |
| Social Perceptiveness | Scheduling/Administrative Tasks |
| Assisting and Caring for Others | Project Management-Monitoring Tasks |
| Management of Material Resources | Instruction/Teaching and Training |
| Technology Design | Evaluating Information for Compliance |
| Active Listening | Organizing Work/Prioritizing Tasks |
| Service Orientation | Written Expression |
| Persuasion | Using Technology to Sell and Influence Others |
New Era for Side Hustles
Generative AI is already proving a significant differentiator for the 5% of the population who work more than one job or have multiple earnings streams. A recent Morgan Stanley Research survey shows that multi-earners who use generative AI tools to enhance productivity or efficiency make US$8.50 per hour, or 21%, more than those who don't.
Multi-earning in the U.S. has risen 11% in the past year, the survey shows, with the figures for content creation and ecommerce up 7%.
“The multi-earner era is an evolution of the gig economy,” says Ed Stanley, Morgan Stanley’s head of thematic research in Europe. “It centres on platforms from social media and gaming to shared mobility and vacation rentals that offer avenues to earn money outside of traditional employment streams.”
In the most optimistic scenario, income from multi-earning could top US$1.4 trillion globally with generative AI adding US$300 billion of that, by 2030.
For full analysis on the impact of generative artificial intelligence on the future of work, labour markets and the broader economy ask your Morgan Stanley representative or Financial Advisor for the full reports, “How GenAI May Shape Labor and the Economy,” (Oct 12. 2023) and “Multi-Earning in a GPT Era,” (Sept. 18, 2023).
