AI set to add potential $15.7 trillion to global economy

Global GDP could be 14% higher in 2030 because of accelerating artificial development and take-up – adding a potential $15.7 trillion. Of this, $6.6 trillion is projected to come from increased productivity and $9.1 trillion from consumption-side effects, according to PwC’s Global Artificial Intelligence Study.

The productivity gains will come from automating processes (with robots, for example), and from augmenting the existing labor force with AI technologies. Increased consumer demand from more personalized and higher-quality AI-enhanced products and services, meanwhile, will drive the other side of the gains.

According to the PwC report, the gains from improved productivity will arrive in the near-term, as companies begin to automate routine tasks. Manufacturing and transport will likely see the largest productivity gains, as their processes are most susceptible to automation.

GDP uplift from product enhancement will arrive later, but deliver an even larger GDP boost than productivity gains in 2030 ($9.1 trillion), as consumers are attracted to the more personalized products and services unlocked by AI. Healthcare, automotive, and financial services have the greatest potential AI disruption/enhancement, according to the report.

Over the period between 2017 and 2030, labor productivity gains are projected to account for 55% of GDP gains from AI, while product enhancements are projected to account for 45%.

China and North America are expected to see the greatest GDP boosts from AI technology, gaining 26.1% of GDP ($7 trillion) and 14.5% of GDP ($3.7 trillion), respectively.

North America will see the fastest boost over the next few years, according to the report, and though the impact will be strong in the mid-2020s, exports of AI-enabled products from China will dampen gains.

China, with its expansive manufacturing sector, will see huge uplift from productive technologies. Though it will take time to build up a critical mass of tech, by 2030 productivity gains in China could begin to pull ahead of the US, according to PwC. A key part of the equation will be China’s higher relative rate of capital re-investment, pouring back more profits to feed increased AI capabilities and returns.

PwC also identified a number of major AI use cases and barriers for various industries. In the automotive industry, autonomous ride-sharing fleets are a high potential use case – as consumers take a shine to only paying for a car when they need it, and eschewing costly maintenance and insurance. The technology still needs to be fully-developed, however, and regulatory and consumer acceptance barriers still need to be overcome.

In the retail industry, personalized design and production means that consumables could be tailored on demand. Fashion, for example, could be designed and supplied through an AI-enabled interactive experience, and then automatically produced in small batches. This would, however, require the adaptation of the production supply chain to the much more agile approach.

In manufacturing, self-learning monitoring could make processes more controllable, reducing delays and defects. It would require all parties to have the necessary technology and be ready to collaborate, however.

In the energy sector, smart meters could help customers tailor their energy consumption and reduce costs, while opening up data to create customized tariffs and more efficient supply. The technology does require more development, though, as well as high levels investment.