The future of AI: Determining its impact on the economy




Economists are known for their mixed track record when it comes to predicting the future, and the tech industry often oscillates between enthusiasm and disillusionment with emerging technologies. Therefore, a degree of scepticism regarding pronouncements about the transformative power of artificial intelligence (AI) on the economy is warranted. However, recent technological advancements have fuelled speculation about AI's potential to reshape various aspects of society, including the economy.

AI's Influence Beyond the Economy

AI's influence extends beyond the economy, affecting national security, politics, and culture. This article, however, focuses on AI's implications for three critical areas of macroeconomic interest: productivity growth, the labour market, and industrial concentration. The future of AI is not predetermined, and it depends on various factors, including technological developments and policy decisions made today. For each of these areas, we present two potential futures and the policies needed to steer AI towards a more favourable outcome.

First Fork: Productivity Growth

The future of economic growth hinges largely on productivity growth, a challenge that has plagued the US and other advanced economies for decades. Boosting productivity is crucial for addressing budget deficits, poverty reduction, healthcare, and environmental issues. AI could either exacerbate or alleviate this problem.

Low-Productivity Future

In one scenario, AI's impact on productivity remains limited. Despite technical advancements, AI adoption by businesses remains sluggish and concentrated in large corporations. AI's role may be limited to routine tasks, failing to enable workers to engage in novel or powerful endeavours. This path could lead to a lacklustre contribution to long-term productivity growth, akin to the "productivity paradox" observed in the computer age.

Numerous challenges, such as legal and regulatory obstacles, could impede AI's development. Intellectual property issues, stringent regulations, and outright bans may hinder AI progress. Inadequate organizational and managerial adjustments by businesses may further undermine AI's economic benefits.

High-Productivity Future

Alternatively, AI could lead to a higher-productivity-growth future by significantly enhancing productivity across a broad range of tasks. AI might complement workers, freeing them from routine tasks and allowing them to focus on creative and innovative endeavours. AI's ability to harness vast amounts of data can empower workers to tackle novel problems, potentially leading to a society of innovators and researchers.

This future could usher in a permanently higher economic growth rate, with AI-backed research driving breakthroughs in fields like medicine and science. AI's recursive self-improvement could become a reality, enhancing creativity and scientific discovery.

Second Fork: Income Inequality

Income inequality has been a growing concern over the past few decades, partially attributed to automation and technological advancements. AI's impact on income distribution can either exacerbate or alleviate this issue.

Higher-Inequality Future

In one scenario, AI leads to higher income inequality. AI may replace various high-paying jobs, driving down wages for many workers. Generative AI may even create content and interact with customers, further broadening the range of jobs threatened by automation. In this scenario, income inequality could increase as a polarized labour market emerges, with a small, highly-skilled elite and a large underclass of poorly paid service workers.

Lower-Inequality Future

Conversely, AI may lead to lower income inequality by empowering less experienced or knowledgeable workers to excel in their roles. AI can support workers, making them more productive, and if the gains are shared with workers, income distribution may become more equal. AI could also improve the quality of work by eliminating routine tasks, leading to higher job satisfaction and reduced turnover.

Third Fork: Industrial Concentration

Industrial concentration, marked by the dominance of large corporations, has been on the rise in many advanced economies since the 1980s. AI can either exacerbate this trend or open up opportunities for smaller businesses.

Higher-Concentration Future

One scenario envisions AI contributing to increased industrial concentration. Large firms with substantial resources may be the only ones capable of fully integrating AI into their core operations. Developing AI models could become prohibitively expensive, favouring only the largest companies. AI may also facilitate complex coordination within large firms, challenging the advantages of small firms in decentralized markets.

Lower-Concentration Future

Alternatively, a lower-industrial-concentration future may emerge, where open-source AI models become widely accessible. A diverse ecosystem of for-profit and non-profit entities, academics, and individual developers could create an environment where small businesses gain access to advanced AI technologies.

This scenario is supported by recent observations that suggest open-source AI models may outperform proprietary ones in terms of customization, privacy, and cost-effectiveness. AI could foster decentralized innovation, benefiting small firms and potentially reducing industrial concentration.

Toward a Policy Agenda

In each of these scenarios, the path leading to a worse outcome is the one of least resistance, characterized by low productivity growth, higher income inequality, and increased industrial concentration. Achieving more favourable outcomes requires diligent policy interventions that shape the future of AI and the economy.

Furthermore, it's essential to understand that AI's development is not fixed; it can evolve in various directions. Policymakers should focus on encouraging AI that complements human labour, broadens access to AI technologies, and fosters open-source ecosystems. Many stakeholders, including major corporations, academic institutions, legislators, regulators, voters, and labour unions, have the power to influence AI's future direction.

As AI's impact on society grows, there is a need for more research on the economic and social consequences of AI. By reorienting research priorities and developing a smart policy agenda, society can move toward a future of sustained and inclusive economic growth, where the potential of AI is harnessed for the benefit of all.


Name Peter Milios

Peter Milios is a recent graduate from the University of Technology - majoring in Finance and Accounting. Peter is currently working under equity research analyst Di Brookman for Corporate Connect Research.