ne word that perfectly encapsulates today’s global economic and political landscape is ‘uncertainty’: trade wars, geopolitical tensions and recurring economic shocks are destabilizing the old order. Thrown into this mix are AI–fueled technological transformations which are now disrupting on overdrive, bringing both fears and cheers.
It’s clear we need smart policies capable of balancing both the threats and opportunities that AI brings; comprehensive, future–oriented investment strategies that protect jobs while allowing AI to spur innovation and drive economic growth.
Policies also need to be context–specific, closely tailored to national conditions and trends and avoiding ‘one size fits all’ approaches. President of the World Bank Group Ajay Banga reinforced this at April’s spring meetings, arguing that the Global South should maximize ‘small AI’—AI solutions that are less dependent on massive datasets and computational or energy resources.
One key contextual factor is age structure—and we believe it is a consequential dynamic around which countries should orient their AI policies and strategies. Done right, countries striking the right balance in development and deployment of AI across generations can increase human capital, productivity, and spending—and ultimately—reap what we call a “digital demographic dividend.” Here’s how in three scenarios.
Scenario 1: Countries with a young population
Build AI skills and aim for a thriving AI research and start–up ecosystem. A large share of countries in the Global South have young populations. African countries, such as Nigeria, Mozambique, and Kenya are slated to double their youth population in the next 5 years. Supporting the labor force in this context requires investments in long–term talent and skills development—especially those oriented toward industries where AI–human interactions will become critical. It could also mean supporting young women in STEM fields and facilitating AI innovation and enterprise in order to broaden the AI labor force and increase the diversity of inputs at all stages of the AI lifecycle.
At the same time, efforts are also needed to address the brain drain. Many countries globally are investing in AI academic and professional programs without targeting talent retention. This leads to an imbalanced AI ecosystem where people may develop AI skills but have nowhere to utilize them. Supporting and developing AI startups, by providing government use cases, investment in infrastructure, avenues for business financing and venture capital, and partnerships between the private sector and universities are all critical components of a talent retention, job creation, and AI–enhanced growth strategy
Scenario 2: Countries with an older population
Focus on AI literacy and AI–enabled services. Conversely, most of the world’s wealthier economies have to consider the effects of an aging population. With the potential to tap into the ‘silver economy,’ these countries need AI investments that support engaged and active longevity and catalyze continuing employment, economic participation, and wealth utilization.
Countries such as Japan have invested in AI tools for healthcare provision and caretaking such as telemedicine, robotics, and diagnostic tools. Recent advances in AI might also be considered to advance the productivity of younger people who care for their elders, maintaining their income and freeing them to provide additional nursing care rather than having their care duties replaced by robots.
Additionally, governments may consider AI tools, notably optimization and predictive analytics tools, in public and financial services to streamline access to benefits such as pensions and social security. Finally, older workers will need AI literacy to adapt. Even those who are no longer working salaried jobs may also benefit from AI upskilling that helps them to start small businesses, increase their investment revenue, or return to the workforce as consultants.
Scenario 3: Transitioning countries
Upskill existing workers and facilitate women’s entry into the AI workforce. Countries transitioning from very young to older populations—many with middle–income status in either Latin America or the Middle East—will need to identify, incentivize and seize competitive economic and financial opportunities in the immediate and near-term while building wealth and planning ahead to support the working population as they age. In this scenario, AI should be applied to help workers stay in the workforce or run their businesses longer. This approach could also be paired with opportunities to engage in work that could see productivity gains from AI, rather than disruptions.
Additionally, many transitioning countries have lower female labor force participation, and would therefore benefit from a focus on digital literacy skills to reduce the digital gender gap and support the entry of more women into the workforce, alongside efforts to bring women into AI–related entrepreneurship.
Shaping a digital future
Microsoft co–founder and leading global philanthropist Bill Gates recently made a bold prediction on NBC’s ‘The Tonight Show.’ He predicted that within ten years “humans won’t be needed for most things.” The interview was a casual, tongue–in–cheek observation about the increasing sophistication of AI technologies. Yet for many workers around the world, particularly in the Global South, AI replacement is not a laughing matter; it is a serious, even existential threat to their livelihoods.
With proactive support to their labor force while guiding the strategic development of AI in a way that boosts economic growth equitably and sustainably between and across generations, governments can shape a future that delivers for all. A digital demographic dividend is there for the taking.
a global affairs media network
Adopt age–based approach to AI for equitable economic growth
Image via Adobe Stock.
May 29, 2025
To ensure equitable economic growth tomorrow, we need to take into consideration the contexts in which AI operates today. One of the most important contexts for AI and its impact on the economy are age—which should inform how we formulate AI policies and strategies.
O
ne word that perfectly encapsulates today’s global economic and political landscape is ‘uncertainty’: trade wars, geopolitical tensions and recurring economic shocks are destabilizing the old order. Thrown into this mix are AI–fueled technological transformations which are now disrupting on overdrive, bringing both fears and cheers.
It’s clear we need smart policies capable of balancing both the threats and opportunities that AI brings; comprehensive, future–oriented investment strategies that protect jobs while allowing AI to spur innovation and drive economic growth.
Policies also need to be context–specific, closely tailored to national conditions and trends and avoiding ‘one size fits all’ approaches. President of the World Bank Group Ajay Banga reinforced this at April’s spring meetings, arguing that the Global South should maximize ‘small AI’—AI solutions that are less dependent on massive datasets and computational or energy resources.
One key contextual factor is age structure—and we believe it is a consequential dynamic around which countries should orient their AI policies and strategies. Done right, countries striking the right balance in development and deployment of AI across generations can increase human capital, productivity, and spending—and ultimately—reap what we call a “digital demographic dividend.” Here’s how in three scenarios.
Scenario 1: Countries with a young population
Build AI skills and aim for a thriving AI research and start–up ecosystem. A large share of countries in the Global South have young populations. African countries, such as Nigeria, Mozambique, and Kenya are slated to double their youth population in the next 5 years. Supporting the labor force in this context requires investments in long–term talent and skills development—especially those oriented toward industries where AI–human interactions will become critical. It could also mean supporting young women in STEM fields and facilitating AI innovation and enterprise in order to broaden the AI labor force and increase the diversity of inputs at all stages of the AI lifecycle.
At the same time, efforts are also needed to address the brain drain. Many countries globally are investing in AI academic and professional programs without targeting talent retention. This leads to an imbalanced AI ecosystem where people may develop AI skills but have nowhere to utilize them. Supporting and developing AI startups, by providing government use cases, investment in infrastructure, avenues for business financing and venture capital, and partnerships between the private sector and universities are all critical components of a talent retention, job creation, and AI–enhanced growth strategy
Scenario 2: Countries with an older population
Focus on AI literacy and AI–enabled services. Conversely, most of the world’s wealthier economies have to consider the effects of an aging population. With the potential to tap into the ‘silver economy,’ these countries need AI investments that support engaged and active longevity and catalyze continuing employment, economic participation, and wealth utilization.
Countries such as Japan have invested in AI tools for healthcare provision and caretaking such as telemedicine, robotics, and diagnostic tools. Recent advances in AI might also be considered to advance the productivity of younger people who care for their elders, maintaining their income and freeing them to provide additional nursing care rather than having their care duties replaced by robots.
Additionally, governments may consider AI tools, notably optimization and predictive analytics tools, in public and financial services to streamline access to benefits such as pensions and social security. Finally, older workers will need AI literacy to adapt. Even those who are no longer working salaried jobs may also benefit from AI upskilling that helps them to start small businesses, increase their investment revenue, or return to the workforce as consultants.
Scenario 3: Transitioning countries
Upskill existing workers and facilitate women’s entry into the AI workforce. Countries transitioning from very young to older populations—many with middle–income status in either Latin America or the Middle East—will need to identify, incentivize and seize competitive economic and financial opportunities in the immediate and near-term while building wealth and planning ahead to support the working population as they age. In this scenario, AI should be applied to help workers stay in the workforce or run their businesses longer. This approach could also be paired with opportunities to engage in work that could see productivity gains from AI, rather than disruptions.
Additionally, many transitioning countries have lower female labor force participation, and would therefore benefit from a focus on digital literacy skills to reduce the digital gender gap and support the entry of more women into the workforce, alongside efforts to bring women into AI–related entrepreneurship.
Shaping a digital future
Microsoft co–founder and leading global philanthropist Bill Gates recently made a bold prediction on NBC’s ‘The Tonight Show.’ He predicted that within ten years “humans won’t be needed for most things.” The interview was a casual, tongue–in–cheek observation about the increasing sophistication of AI technologies. Yet for many workers around the world, particularly in the Global South, AI replacement is not a laughing matter; it is a serious, even existential threat to their livelihoods.
With proactive support to their labor force while guiding the strategic development of AI in a way that boosts economic growth equitably and sustainably between and across generations, governments can shape a future that delivers for all. A digital demographic dividend is there for the taking.
