The rise of artificial intelligence marks a pivotal moment in human history one with the potential to reshape economies, societies, and everyday life. As we stand at this crossroads, two stark scenarios emerge: on one side, an era of unleashed productivity, innovation, and prosperity; on the other, one of job displacement, deepening inequality, and societal dislocation. The task before us is not simply to manage these changes, but to decisively shape their trajectory so that AI becomes a catalyst for human flourishing.
1. The Transformation of the Workforce
Recent IMF analysis underscores that roughly 40% of global jobs are susceptible to AI’s reach, with advanced economies facing even higher exposure nearly 60%. Critical here is the recognition that AI doesn’t just threaten jobs it transforms them. According to IMF, half of these jobs could be enhanced by AI, enabling heightened productivity and capabilities. But the flip side is real: the other half may face diminished demand, wage pressure, and even job elimination.
Importantly, this isn’t a story one-and-done; it’s a generational journey. Younger and less experienced workers often adapt more swiftly to AI tools, while older workers may struggle to keep pace. Today’s global workforce will need to continuously learn, unlearn, and relearn—across industries and geographies.
2. Diverging Realities: Advanced vs Developing Economies
Global impact will be uneven. Advanced economies, with mature infrastructures and high-tech industries, are both the most exposed and the most capable of integrating AI. Emerging and low-income countries face lower immediate exposure, but great structural barriers including poor digital infrastructure, limited workforce training, and weaker governance frameworks could prevent them from sharing in AI’s productivity gains.
The upshot: AI stands to widen the gap between “haves” and “have-nots” not just between individuals, but between nations. Without deliberate global policy design, AI could turn into a tool that deepens economic polarization and entrenches inequality.
3. Building Inclusive Foundations: The AI Preparedness Index
To navigate this transformation, the IMF introduced the AI Preparedness Index, evaluating countries on four pillars: digital infrastructure, workforce readiness, innovation capacity, and ethical/regulatory frameworks.
- Digital Infrastructure: Stable broadband, data centers, cloud computing.
- Human Capital & Labor Policies: Classroom quality, lifelong learning, mobility.
- Innovation & Integration: R&D investment, startup ecosystems, partnerships.
- Regulation & Ethics: AI governance norms, transparency, safeguards.
This tool reveals a stark alignment: wealthier nations dominate but there are outliers. Singapore, the U.S., and Denmark rank highest. The message is clear: bridging the digital divide is essential for ensuring that developing nations can become active participants, not passive spectators, in the AI revolution.
4. Policy Pathways: How to Guide AI for Broad-based Benefits
To ensure that AI’s limitless promise is harnessed for social good, farsighted strategies are needed:
a) Invest in Lifelong Learning & Retraining
We must reinvent education. Workers will move between roles and industries more frequently than ever as AI redefines job definitions. Governments, academia, and corporates need to co-invest in reskilling platforms, apprenticeships, and portable credentials.
The IMF recommends tailored retraining aids pensioners, workers displaced by AI, and vulnerable communities.
b) Strengthen Social Safety Nets
Uneven transitions require safety nets-unemployment insurance, wage subsidies, healthcare access-that offer dignity, not dislocation. Expanding these systems can buffer short-term shocks and encourage upskilling.
c) Modernize Taxation & Capital Policy
AI may depress labor income while boosting capital profitability. To capture these gains for broader societal use, the IMF advises recalibrating taxation-reversing decades-long declines in capital gains tax, and removing AI-specific tax breaks that mainly benefit large firms.
d) Implement Ethical, People-Centric Governance
As AI systems automate decisions in finance, hiring, policing and more, ethical guardrails are non-negotiable. Nations should adopt transparent AI governance regimes, focus on data privacy, ensure redressability, and engage civil society mirroring frameworks like the EU’s AI Act.
e) Promote Global Cooperation and AI Equity
AI is global but benefits are not automatically distributed. Multilateral cooperation, tech sharing, capacity-building, and funding for digital infrastructure in low-income countries are critical. Wealthier countries and institutions like the IMF must lead on inclusive AI diplomacy.
5. Economic Potential: Growth, Inclusion, and Resilience
If thoughtfully deployed, AI could boost global GDP by 1.3% – 4% over the next decade depending on adoption speed and productivity growth Advanced economies would benefit most, but gains can be more widely shared through infrastructure support and skill development in emerging economies.
Importantly, such gains aren’t automatic. They require parallel investments in people and systems. With them, AI could reverse sluggish growth trends, narrow gaps, and reinforce global resilience.
6. Human-Centered Stewardship: AI as Our Ally
This isn’t a zero-sum battle. AI can heighten human creativity, elevate problem-solving, and tackle grand challenges from climate change to disease and inequality. But technocratic solutions alone will fail if they ignore the human context.
Empathy must shape the AI narrative. Companies need to commit to workforce transitions, rather than layoffs. Governments must partner with communities, educators, and labor advocates to build trust in part by making AI regulation visible, responsive, and rights-based.
Large tech firms hold enormous power and responsibility. We need commitments like the “Windfall Clause,” where firms pledge to share unprecedented profits for the public good.