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Home Artificial Intelligence

Understanding The Economic Impact Of Artificial Intelligence

Contributor by Contributor
September 14, 2021
in Artificial Intelligence
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In Brief
  • The advent of artificial intelligence will substantially impact the economy in both the short and long term.
  • This article hopes to provide insight into some of the various economic impacts that AI is already having or will soon have on society.
  • AI can be defined as “intelligence exhibited by machines.” It includes cognitive technologies like machine learning (ML)–which extracts information from data sets without relying on explicit...

The advent of artificial intelligence will substantially impact the economy in both the short and long term. This article hopes to provide insight into some of the various economic impacts that AI is already having or will soon have on society.

AI can be defined as “intelligence exhibited by machines.” It includes cognitive technologies like machine learning (ML)–which extracts information from data sets without relying on explicit programming–and natural language processing (NLP), which enables computers to understand human speech.

Industry 4.0 is considered to be the organization of manufacturing activities using cyber-physical systems, industrial internet of things, and cloud computing with networked production lines. These concepts are often grouped under the label of Industry 4.0. They are based on the idea that smart production systems can yield an economic benefit if all of the physical elements in the value chain are intelligently interconnected via information technology.

 

What is smart factory?

Industry 4.0 has been described as a “smart factory.” It is a term used within manufacturing engineering to integrate cyber-physical systems into industrial processes: It is defined by integrating discrete manufacturing technologies (robotics, machine tools, computer numerical control) through cyber-physical systems, which enables better decision-making capabilities using real-time streaming data from sensors throughout a smart factory. You can use the data gathered from such devices to make intelligent decisions about optimizing productivity and efficiency or for automatic control of quality management feedback loops; this also allows for a more flexible and quick reaction to change.

Although Industry 4.0 is not reliant on artificial intelligence, it does benefit from the availability of high-speed (broadband) connectivity within production facilities, which can be used in conjunction with other technologies, such as cloud computing and big data analysis, thereby building competitive advantage at a time when international competition for manufacturing industry is increasing.

Industry 4.0 has been branded by Gartner Inc as “the fourth industrial revolution.” According to Jürgen Cerwinka, head of Digital Factory at Siemens AG: “Industry 4.0 enables companies to take fast decisions through predictive maintenance thanks to early fault detection.” Industry 4.0 also enhances productivity by connecting intelligent devices such as smartphones, drones, and self-driving cars to the network.

Industry 4.0 is expected to have a global economic impact of $4.6 trillion by 2025, according to a Gartner’s report from 2017. This figure represents an average annual growth rate of just under 9%. Know more at RemoteDBA.com

 

Offshoring, onshoring and reshoring

The offshoring trend, driven by manufacturing firms in developed economies seeking lower production costs through outsourcing activities overseas, has been going on for decades; however it now the potential of AI technology may be acting as a forcing function that will see this trend reversed over time with onshoring becoming more common due to AI’s ability to enhance productivity in manufacturing through various means (i.e., predictive maintenance & optimization). This phenomenon could also result in the reshoring or repatriation of jobs which the theory is already holding true to some extent.

Data from OECD shows that there has been a steady increase in manufacturing FDI outflows (investments made by firms located in one economy into another economy) over the last decade, reaching about USD 300 billion per year worldwide by 2015 (up from USD 150 billion ten years ago). According to an analysis done by Mckinsey & Company for Forbes, it was estimated that between 20-25% of companies would use AI and ML as part of their global workforce strategy by 2020.

Advanced Analytics Partners opened a 1 million square foot facility at South Carolina Boeing 787 final assembly site after the state promised $240 million in tax incentives. There are already some 300 jobs listed for the facility, which does digital engineering work for FedEx and Airbus Group parcel delivery companies.

 

Manufacturing and AI

The future manufacturers will be those who put artificial intelligence (AI) to use, integrating all aspects of their value chains, including manufacturing and management functions. The rise of Industry 4.0 is expected to provide a major stimulus for employment growth in technologically advanced economies by boosting demand for human labour as AI-based smart machines take on increasingly complex tasks that require dexterity and problem-solving abilities, such as picking parts from a pile or assembling them into sub-systems.

This would represent an evolution within the workforce rather than an overnight replacement; indeed, certain physical jobs will remain beyond AI’s capabilities for the foreseeable future.

Artificial intelligence and other digital technologies in manufacturing are expected to increase productivity by 10% in OECD countries by 2025. This will lead to a 1.3% gain in GDP in these countries at current prices, an increase equivalent to about USD 320 billion. The impact on individual sectors may vary significantly; however, all economic activities benefit from AI-based technologies as they raise total factor productivity (TFP).

Not only does AI help produce better quality goods with greater precision (including increased consumer safety), it also helps save time – up to 25% less through improved processes and reduced errors. For example, Amazon’s Kiva robots have allowed them to reduce their order processing time from 60 minutes to just 15 minutes.

The impact on jobs will depend on the extent and speed of adoption of AI technologies and the development of complementary innovations in other fields (robots, automation systems), which may amplify or partially substitute it. While the OECD employment outlook report shows that a 1% increase in TFP would typically lead to a 0.05% decrease in overall labor demand, this estimate varies across countries and sectors. Likewise, some occupations might be complemented while others could see their tasks reassigned to either humans or machines [or perhaps completely automated?]. Other factors such as worker mobility are also important for determining how quickly AI-based technologies can substitute labour.

Industrial robotics should provide global GDP by USD 7 trillion over the period 2016-2025. According to a new report from IDC Manufacturing Insights, by 2025, industrial robotics and artificial intelligence will automate an estimated 56 percent of the world’s manufacturing labour requirements. In addition, according to McKinsey & Company, recent advances in AI will have a major impact on both product innovation and service innovation.

Tractica forecasts that global revenue from the sale of AI hardware, software, and services will grow from USD 949 million in 2015 to nearly USD 38 billion by 2025. However, this might understate the role that AI technology is expected to play within industries such as transportation. For example, Goldman Sachs estimates that Waymo (formerly Google Car) could disrupt the global automotive with a fleet of self-driving cars that could be ten times cheaper to own and operate than regular cars.

According to PwC, the advent of AI technologies could increase total factor productivity growth by 0.8% in 2035-2045 for OECD countries, representing an additional USD 1.9 trillion. This implies a cumulative change in real GDP of about USD 24 trillion by 2030 and USD 35 trillion by 2040 [So, we are talking a long-term, ~10-year impact here.] thus, it is estimated that AI-led TFP growth would accelerate global GDP growth from 3.3% over 2000-2015 (mean annual growth) to 4.6 % from 2020-2030 and 5.0% from 2030-2040.

The bulk of the productivity gains are expected to be driven by the so-called “digital economy,” which is estimated to account for about 30% of GDP and 50% or more of employment in OECD countries.

Besides these direct impacts on GDP growth through increased productivity, AI-based technologies should have a positive spillover on investment and capital as they may induce companies to invest more in technology.

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