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Experts question impact of AI on productivity amid global growth concerns

By Jessica Penny
4 minute read

Despite significant investments in AI, driven by expectations of substantial improvements in economic productivity, market experts remain uncertain about when and how these impacts will materialise.

Global growth, which has slowed steadily since the early 2000s, saw an even more pronounced decline following the Global Financial Crisis (GFC).

According to the Amundi Investment Institute, economists largely attribute this decline to a broad-based slowdown in total factor productivity growth (TFP), which measures how efficiently labour and capital inputs are used to produce output.

Mahmood Pradhan, head of global macroeconomics at Amundi, noted that if current trends continue, global growth over the next decade is likely to fall below 3 per cent, compared to just under 4 per cent in the two decades before the pandemic.


“And that’s before we consider some of the more recent adverse developments, such as global economic fragmentation, increasing security concerns, and the transition to net zero,” Pradhan said.

Despite this, Amundi expects the macroeconomic growth impact of AI to materialise beyond the medium term, with rapidly increasing investments in AI across sectors, from manufacturing to services, leaving many optimistic about the outlook for productivity and growth.

Pradhan outlined how the investment firm anticipates the adoption of AI to unfold: firstly, limited visibility (2024–33), then a broader diffusion (2034–43) and finally, a normalisation phase where the new technologies deliver “diminishing” returns (2044–53).

Nevertheless, considerable uncertainty remains about the speed of this adoption and its potential macroeconomic impact.

“The latter issue is closely associated with whether AI displaces workers or augments their productivity. This, too, might have a time dimension, with a stronger likelihood of displacing some workers in the short run and a potential to enable new tasks in the longer term,” Pradhan noted.

In line with this, the IMF has previously suggested that 60 per cent of jobs could be susceptible to AI in the medium term.

He added: “Acemoglu estimates the increase in productivity over the next 10 years could be about 0.06 per cent per year – largely because most AI applications are geared toward saving labour, estimated at about 25 per cent, yielding overall cost savings of about 15 per cent. AI investment that spans across many sectors may raise 10-year productivity to between 1 per cent and 1.5 per cent of GDP.”

As such, these “low” estimates of productivity gains over the next decade reflect an underlying view of what AI is poised to change.

“It is currently seen as being focused on automation and monetising data, rather than introducing new tasks. If, and when, AI extends to aiding the process of scientific discovery and coming up with new products, the gains will likely be larger.”

Pradhan further noted that many countries may struggle to meet the infrastructure, skilled labour, and investment requirements necessary to fully leverage AI.

“Moreover, the near-term threat of displacing workers will come up against many institutional and structural rigidities in many countries, with the likely effect that it will delay widespread adoption,” he concluded.

In October, amid AI investments having been underpinned by expectations of a marked tech-driven improvement in economic productivity, analysis from Oxford Economics’ lead economist, Adam Slater, suggested the touted boost to productivity may be overstated.

“Our historical evidence strikes a note of caution about extrapolating dramatic rises in economy-wide productivity growth from the adoption of AI,” Slater explained at the time.

Most notably, the productivity benefits of general-purpose technology (GPT) like AI, the group added, may “take decades to bear fruit”.

Citing principles outlined by economics professor Nicholas Crafts in a paper published in 2002, Slater said initial impacts of GPT technologies on growth “can be small or even negative”.

“It takes time to transform a capital stock given that annual investment is only a small fraction of the total.”