The role of artificial intelligence (AI) tools and techniques in business and the global economy is in the spotlight. This is not surprising, given that AI has the potential to bring about fundamental and perhaps unprecedented changes in the way people live and work. The AI ​​revolution is still in its infancy, but much of its economic impact is yet to come.
A new study from the McKinsey Global Institute seeks to simulate the impact of AI on the global economy. First, we build a bottom-up perspective on how to adopt and absorb AI technologies, based on an understanding of corporate behavior and the dynamics of different sectors. Second, we consider the disruption that countries, businesses, and workers will experience as they transition to AI. Costs are very likely to be incurred during this transition period and should be factored into your estimates. This analysis examines how economic gains and losses are likely to be distributed among companies, employees, and countries, and how this distribution may hinder the reaping of the benefits of AI. We will investigate. Third, this study examines the dynamics of AI in a wide range of countries categorized into groups with similar characteristics, with the aim of providing a more global perspective.
This analysis should be seen as a guide to the potential economic impact of AI, based on the best knowledge available at this stage. The main findings are:
AI has great potential to contribute to global economic activity. The main challenge is that its introduction could widen disparities between countries, companies, and workers.
There is great potential for AI to contribute to global economic activity
McKinsey Global Institute examined five broad categories of AI: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. Companies will use these tools to varying degrees. Some companies will take an opportunistic approach, testing just one technology and piloting it with a specific feature (an approach we call adoption in our modeling). Some might be more bold and adopt all five and absorb them throughout the organization (an approach we call complete absorption). Between these two poles are many companies at various stages of implementation. The model also captures this partial effect.
Average simulations suggest that by 2030, approximately 70% of companies will have adopted at least one type of AI technology, but fewer than half will have fully absorbed all five categories. It won't be enough. The pattern of adoption and complete absorption is likely to be relatively rapid and on the higher end than that observed for other technologies.
Several barriers can impede rapid adoption and uptake (see video “One Minute with McKinsey Global Institute: Challenges of Automation Technology Adoption''). For example, a late adopter may find it difficult for him to generate impact from AI. This is because frontrunners have already captured the AI ​​opportunity, and late adopters have lagged behind in capability development and talent acquisition.
Nevertheless, at the global average level of adoption and uptake our simulations suggest, AI could generate approximately $13 trillion in additional global economic activity by 2030, compared to today. cumulative GDP could increase by approximately 16 percent. This equates to an additional GDP growth of 1.2% per year. If realized, this impact would be comparable to any other general-purpose technology in history.
Many factors, such as labor automation, innovation, and new competition, will impact productivity gains with AI. Both micro factors, such as the pace of AI adoption, and macro factors, such as global connectivity and a country's labor market structure, will contribute to the magnitude of the impact.
In our simulations, we investigated seven possible impact pathways. The first three relate to the impact of AI implementation on the need for and combination of production factors that directly impact a company's productivity. The remaining four are externalities related to AI adoption related to the broader economic environment and the transition to AI. We recognize that these seven channels are not definitive or necessarily comprehensive, but are a starting point based on our current understanding and ongoing trends (Exhibit 1) .
The impact of AI is not linear and is likely to increase at an accelerating rate over time. His contribution to growth could more than triple over the next five years by 2030. The S-curve pattern of AI adoption and absorption will begin slowly due to the significant costs and investments associated with learning and deploying these technologies, followed by the cumulative effects of competition and improvements in complementary capabilities along the way. It may accelerate. Innovation.
It would be a misjudgment to interpret the effects of this “slow burn” pattern as evidence that AI's effectiveness is limited. The magnitude of the benefits for companies that adopt these technologies early will accumulate later in life at the expense of companies with limited or no adoption.
Section 2
A key challenge is that the introduction of AI has the potential to widen disparities between countries, companies, and workers.
Al can boost economic activity, but the benefits are likely to be uneven.
Impact of AI on countries
Potentially, AI could widen the divide between countries and strengthen the current digital divide. Different countries may require different strategies and responses due to different rates of AI adoption.
Leaders in AI adoption (mostly developed countries) have the potential to widen their lead over developing countries. AI Developed countries could reap an additional 20-25% net economic benefit compared to today, while developing countries could only gain around 5-15%. Many developed countries have no choice but to advance AI to achieve higher productivity growth as GDP growth momentum slows and in many cases reflects, in part, the challenges posed by aging populations. Maybe. Furthermore, higher wage rates in these economies mean that there is a greater incentive to replace labor with machines than in developing countries with lower wages.
In contrast, developing countries tend to have other ways to improve productivity, such as catching up on best practices or restructuring their industries. Therefore, there may be less incentive to promote AI (in any case, the economic benefits from AI may be relatively small compared to developed countries). Some developing countries may be exceptions to this rule. For example, China has developed a national strategy to become a world leader in her AI supply chain and is making significant investments.
How AI will impact your business
AI technology is creating a gap between frontrunners (companies that fully absorb AI tools across their companies over the next 5-7 years) and non-adopters (companies that have not adopted any AI technology or have not fully adopted it). There may be a performance gap between. (to be absorbed into the company by 2030).
On one end of the spectrum, front runners may benefit disproportionately. By 2030, cash flows (economic benefits earned minus associated investment and transition costs) could double. This means an additional approximately 6% increase in annual net cash flow over the next 10 years. Frontrunners tend to have a strong initial IT base, a higher propensity to invest in AI, and a positive view of the business case for AI.
Non-adopters, on the other hand, could see cash flow decline by about 20% from current levels, assuming the same cost and revenue models as today. One of the key drivers of this profit pressure is the existence of strong competitive dynamics between companies, which can shift market share from the laggards to the frontiers, leading to an unequal distribution of the benefits of AI. (Exhibit 2).
Impact of AI on workers
Increasing inequality can play out at the individual employee level (see video “One Minute with McKinsey Global Institute: What AI Can Do and What It Can't Do”) [yet] “). Job demands are likely to shift from repetitive tasks to those that are socially and cognitively driven and require more digital skills. Characterized by repetitive activities Occupations and occupations that require low-level digital skills are likely to see the largest decline in their share of total employment, from about 40 percent to about 30 percent by 2030. is expected to rise from about 40 percent to more than 50 percent for non-repetitive activities and activities that require advanced digital skills.
These changes will affect wages. We expect that around 13% of total wages will shift to categories that require non-repetitive, high-level digital skills, potentially increasing their earnings, while workers in the repetitive, low-digital skill categories will simulates the possibility of experiencing wage stagnation or reductions. . The latter group's share of total wages could fall from 33% to 20%.
A direct result of this widening gap in employment and wages will be an escalation of warfare for people, especially those skilled in developing and using AI tools. On the other hand, there is the potential for structural oversupply for a still relatively large proportion of people who lack the necessary digital and cognitive skills to work with machines.
Overall, AI adoption and absorption may not have a significant impact on net employment. Demand for full-time employment is likely to come under considerable pressure, but the overall net impact may be more limited than many fear. Our average global scenario suggests that aggregate demand for full-time equivalent employment may remain flat or even have a modest negative impact on employment by 2030.
While the opportunities for AI are significant, there is no doubt that its widespread adoption has the potential to cause disruption. The productivity benefits of AI probably won't be realized anytime soon. The impact can increase exponentially over time. Therefore, the benefits of the initial investment may not be realized in the short term. It requires patience and long-term strategic thinking.
Policymakers will need to show bold leadership to overcome the public's understandable discomfort with the threat to jobs as automation takes hold. Businesses will also be key actors in finding solutions to the huge challenge of skilling and reskilling their workforce to take advantage of AI. Individuals will need to adapt to a new world where job turnover may become more frequent, transitions to new types of employment may be necessary, and individuals will need to adapt to the needs of a dynamically changing job market. You may need to continually update and refresh your skills.
Capitalizing on the historical trend of new jobs being created for old jobs and adjusting for low labor-to-output ratios to account for the labor-saving potential of AI technologies through smart automation will be facilitated by investments in AI. New job in 2030. The total productivity effect could have a positive contribution of about 10 percent to employment.
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