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Global AI Report

AI will add $13 trillion economic output by 2030, boosting economic growth by 1.2% per year

 

AI is a family of technologies; five broad categories are:

  • Computer vision
  • Natural language
  • Virtual assistants
  • Advanced machine learning
  • Robotic process automation

By 2030, 70% of companies will adopt at least one and less than half will adopt all 5. Seen this before? Steam engines in 1800 boosted output by 0.3%, robots in 1990s 0.4% and spread of IT in 2000s 0.6%.

 

7 channels for AI impact

1. Augmentation

Changing the balance of labour capital for jobs. AI will augment existing jobs may altering human capabilities and improve productivity.

 

2. Substitution

More productive and cheaper technologies will replace other factors of production (labour, older technologies).

 

3. Product and service innovation and extension

Innovation beyond the bare minimum creates a surplus for companies in terms of portfolios, channels and business models. Companies are motivated to not only improve efficiency in what they currently do but want to stay ahead in terms of what goods and services they offer.

 

4. Economic gains from increased global flows

Digital and data flows could account for 7% of GDP growth between now and 2030, AI will contribute 20% towards this.

 

5. Wealth creation and reinvestment

Productivity gains from AI translate into higher profits for entrepreneurs and higher wages for employees. The result is a multiplier effect as more money is reinvested into businesses and more money is spent within the economy or paid in taxes.

 

6. Transition and implementation costs

Firms will encounter a range of costs as a result of adjusting to AI, with examples including:

  • Paying severance for displaced workers
  • Fees for AI software
  • Consulting and project fees paid to successfully onboard new software
  • Increasing the skills of their workforces

 

7. Negative externalities

  • Government support costs for displaced workers who need retraining or economic support
  • While workers are unemployed and perhaps retraining, they will not be contributing to economic growth and further problems could arise
  • Engels pause: during the first half of the 19th century, output per worker and profit share of national income increased but wage growth was stagnant.

 

Geographical Trends

China and US lead the race:

  • Scale and network effects enable more investment and a better talent pool
  • External investment: US 66%, China 17% and then the rest in 2016 but China’s share is growing fast

 

Canada, France, South Korea, Sweden, Germany, Japan and UK:

  • Well-positioned to capture AI benefits due to slowing productivity growth
  • Higher labour costs create the incentive to switch to automation
  • A strong foundation of enablers

 

India, Italy and Malaysia have moderate foundations:

  • Weaker starting position than the above but have some comparative strengths
  • India: generates 1.7 million STEM graduates (more than G7 combined) and has a high share of ICT-related exports

 

Economies with weak foundations:

  • Priority is for these countries to alleviate poverty and the ROI may be more certain for catching up technologies to best practices rather than innovation
  • These economies will focus on transforming the economy away from agriculture towards basic and advanced manufacturing
  • Lack of digital infrastructure, capital markets (venture capital, reliable financial institutions), isolated from global trade and data flows

 

Will AI replace jobs?

  • 375 million workers, 14% of the global workforce, may need to change jobs
  • Virtually all will need to adapt their jobs

 

Jobs that have the highest potential for automation (60-80%):

  1. Performing physical activity and operating machinery in predictable environments
  2. Collecting data
  3. Processing data

 

Jobs that have a 10-25% potential for automation:

  1. Performing physical activity and operating machinery in unpredictable environments
  2. Interfacing with stakeholders
  3. Applying expertise to decision making
  4. Planning
  5. Creative tasks

 

Trends in employment:

  1. Shift towards jobs requiring high digital skills and nonrepetitive tasks
  2. More wage inequality as wages go up for digital-based jobs and down for repetitive jobs
  3. Depends on the company: top-percentile companies have seen wages increasing fast whereas lower-percentile companies have had stagnated wages

 

Sources:

https://www.mckinsey.com/featured-insights/artificial-intelligence

 

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