“The AI revolution is not in its infancy, but most of its economic impact is yet to come.”

That’s the message from new research conducted by the McKinsey Global Institute (MGI).

Building out a model based on its understanding of company behaviour and industry dynamics – together with an appreciation of what “countries, companies, and workers are likely to experience as they transition to AI” – MGI has settled on a global view.

Of course there are many variables and thus potential outcomes, but MGI says that “at the global average level of adoption and absorption implied by our simulation, AI has the potential to deliver additional global economic activity of around $US13 trillion by 2030, or about 16 percent higher cumulative GDP compared with today.”

That’s 1.2% per year in additional GDP if MGI is correct, which, it says, “would compare well with that of other general-purpose technologies through history.”

Here’s how MGI came up with their numbers:

Our simulation examined seven possible channels of impact. The first three relate to the impact of AI adoption on the need for, and mix of, production factors that have direct impact on company productivity. The other four are externalities linked to the adoption of AI related to the broad economic environment and the transition to AI. We acknowledge that these seven channels are not definitive or necessarily comprehensive but rather a starting point based on our current understanding and trends currently under way.

The authors highlight the uncertainty surrounding their simulation and say the “impact of AI might not be linear.”

Rather, AI adoption and impact “could build up at an accelerating pace over time.”

As a result, by 2030 AI’s “contribution to growth might be three or more times higher… than it is over the next five years.”

MGI says that to extrapolate the current “slow burn” pattern of AI’s impact is a mistake, instead insisting “the size of benefits for those who move early into these technologies will build up in later years at the expense of firms with limited or no adoption.”

You can read the full report from MGI here.

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