AI could impact up to 40% of global jobs
We’re looking at one of the most significant shifts in work since the Industrial Revolution. It’s real, and it’s happening now. According to the United Nations Conference on Trade and Development (UNCTAD), up to 40% of all jobs could be affected by AI.
What’s driving this shift is automation. AI is now capable of performing tasks that were once limited to people, analysis, decision-making, even customer interaction. As that expands, the nature of work changes. Repetitive jobs go first. Low-skill or mid-skill roles where tasks follow predictable patterns are already being replaced by learning algorithms. But it doesn’t stop there. High-skill work is also being reshaped, legal research, financial analysis, diagnostics.
This might sound alarming, but it’s not bad news for everyone, unless you do nothing. The same technology that automates roles also creates new industries. Entire evolution cycles are occurring, not just replacing humans, but augmenting them. That means demand is rising for people who can work with AI: data analysts, AI system designers, prompt engineers, platform managers, automation strategists. These weren’t even recognized positions just a few years ago.
For C-suite leaders, the key move is investment in people. Targeted reskilling built around what AI can’t (yet) replicate: creativity, judgment, ethics, communication, and unique problem-solving. Ignore talent adaptation at your own risk. Keeping your workforce relevant means embedding learning into the business strategy, not handling it as an HR side-project.
This is also about risk management. If you’re not evolving your workforce at pace with automation, you’re actively moving toward operational fragility. Companies that can’t adapt get outrun.
The future is already here; the workforce just needs to catch up. It starts at the top. Make automation work for you by leading with intention, not reaction.
AI may exacerbate global inequality
There’s a real imbalance forming in the global distribution of AI’s benefits. The UNCTAD report makes it clear, nations that already hold the technological infrastructure, data access, and financial capital are positioned to dominate. While advanced economies accelerate through AI adoption, most developing countries are either excluded or stuck competing with fewer tools and lower leverage.
AI rewards scale and data. If your country or company controls large data pools, has access to cloud infrastructure, and owns AI development platforms, you’re ahead. For countries without those advantages, there’s a loss of leverage, especially if their competitive edge was historically based on providing low-cost labor. AI reduces dependency on that labor, immediately undercutting one of the few advantages developing economies rely on.
That creates a feedback loop. More AI-generated value flows to nations that already build and integrate the technology. Companies in these countries gain efficiency and profit faster. That growth then allows them to reinvest, build more technology, and hire higher-skilled domestic talent, locking others out even further. If nothing shifts, this won’t even be a race, it’ll be a global sorting mechanism where most of the emerging economies fall behind.
Business leaders should take a broader view. Supply chains rely on balanced global growth. So does innovation. If only a few players capture most of the tech value, you limit the diversity the global economy depends on. That eventually feeds back into reduced opportunity, economic stagnation, and socio-political risk.
The UN’s recommendation is clear: developing countries must have a seat at the table when AI rules are being shaped, ethics, trade frameworks, accountability systems. Without participation in these formative discussions, their future role in AI ecosystems will be limited to consumption, not creation. That’s not sustainable for them, or for the rest of the world’s businesses.
Build partnerships. Share capability. Support standards that are inclusive.
The global AI market is projected to grow to $4.8 trillion by 2033
Let’s talk scale. The UNCTAD report estimates the global AI market could reach $4.8 trillion by 2033. That’s a decade-out projection based on sustained enterprise adoption, expansion of consumer applications, and national-level tech investments. The trajectory is clear: AI is moving from experimental pilots to critical infrastructure.
This level of growth concentrates power. Right now, value creation in AI is not evenly distributed. It’s led by a small group of dominant players, companies and countries with massive compute power, proprietary models, full-stack integration, and multi-layer monetization. They’re setting standards, collecting data, refining use cases, and capturing market share faster than any regulatory frameworks can catch up.
This poses a challenge for emerging players. Break-in costs are rising. You need capital, access to skilled engineers, and permissionless innovation space to keep pace. That applies equally to nations and to companies trying to scale. If you’re not already positioned in the AI value chain, hardware, foundation models, cloud infrastructure, vertical-specific solutions, you’re buying from those who are. That pricing power creates dependence.
Growth at this scale opens room for focused specialization. Enterprises that move fast, especially in operational AI use cases, industry-specific platforms, or ethically embedded systems, can capture value. C-suite leaders should stop treating AI as a support tool and start treating it as a lead product line. The opportunity is in tech development, and in business model transformation, service automation, market prediction, and operational acceleration.
There’s also a responsibility piece. If large-scale AI expansion continues without aligned accountability, misuse gets entrenched. That’s bad for business. Lack of transparency, data privacy violations, biased outputs, these erode user trust and attract regulation. Expect governments to intervene when foundational models begin displacing democratic safeguards. That risk should be factored into your planning.
If you’re thinking long term, act short term. Start now. Build internal capabilities. Establish data governance. Audit use cases. Don’t wait for regulators or market forces to correct for you, because they react, and by the time they do, you could already be priced out.
Key executive takeaways
- Prepare for large-scale job disruption: AI advancements could impact up to 40% of jobs globally. Leaders should prioritize strategic retraining and workforce transitions to maintain productivity and minimize operational risk.
- Address growing global inequality risks: AI is expected to widen the economic gap between developed and developing countries. Executives should support inclusive AI governance frameworks and explore partnerships that extend capability-building beyond high-capital markets.
- Act early on AI market positioning: With the AI market projected to reach $4.8 trillion by 2033, companies that embed AI deeply into core operations now will have a significant competitive edge. Failing to invest in internal capabilities and responsible AI practices may lead to strategic and regulatory setbacks.
