Bridging the AI Technology Gap Before It Becomes a Chasm

By Dr K.M. George — Secretary-General, Global Millets Foundation & CEO, Sustainable Development Forum

The world is living through a paradox. Never before have we witnessed such extraordinary leaps in technology, particularly in artificial intelligence (AI). Yet never before has the risk of exclusion been so stark. While AI transforms health, education, commerce and governance in advanced economies, large parts of the globe remain on the margins — struggling with basic digital infrastructure, skills shortages, and limited say in shaping the rules of the game.

This is not just a “digital divide” anymore. It is an AI divide, growing faster than many policymakers realize. Left unchecked, it will deepen inequality between nations and within societies. The United Nations’ recent Governing AI for Humanity report makes it clear: without urgent, coordinated action, the very technology that could help us solve global challenges may instead amplify them.

From Access to Capability: How the Divide Evolved

The digital divide of the 1990s and 2000s was about simple access: who had internet, who had devices. Over time, mobile phones and cheaper data services narrowed that gap. But the story didn’t end there.

The new divide is about capability. Can teachers use AI to prepare students for tomorrow’s jobs? Can hospitals in low-resource settings deploy AI diagnostics to catch diseases early? Can small farmers use satellite-fed AI tools to boost yields?

For many, the answer is still no — not because they lack imagination, but because they lack infrastructure, skills, data, and investment. The AI revolution, concentrated in a few labs and companies in a handful of countries, risks leaving billions of people as passive consumers of systems they had no part in shaping.

The Reality Check: Uneven AI Adoption

Recent reports from the World Bank, OECD, and UN agencies paint a sobering picture:

• Adoption is lopsided. Firms in wealthy countries are adopting AI at lightning speed. In some regions, adoption doubled in a year. Meanwhile, many developing countries lag far behind.
• Wages are at risk. OECD economists warn that AI could widen wage inequality if workers are not reskilled. Some tasks will be automated, while others will demand higher skills and pay premiums.
• Basic infrastructure is missing. Billions remain offline or dependent on unreliable internet. Without reliable electricity, broadband, and data centers, AI remains a distant dream.
• Literacy is low. UNESCO stresses that “AI literacy” is now essential. Without it, communities risk becoming an “AI underclass” — unable to interpret, evaluate, or benefit from the tools shaping daily life.
• Women are especially vulnerable. Gender gaps in digital access and employment mean women could be disproportionately displaced by AI-driven disruption.

These realities mean AI isn’t just an innovation story. It’s a development story. And development gaps, if ignored, have a way of hardening into permanent divides.

The Challenges We Cannot Ignore

1. Concentration of power. A handful of corporations control the compute, data, and models that underpin modern AI. This centralization risks embedding their priorities into systems used globally.
2. Job dislocation. AI will not just replace jobs — it will reshape them. Without proactive policy, entire communities may find themselves locked out of the AI economy.
3. Governance vacuum. Many countries lack even the most basic AI policies or data protection laws. Without them, they risk becoming “rule takers” in a game set by others.
4. Exclusion by design. If AI systems don’t recognize local languages, cultural contexts, or social needs, they effectively exclude those communities.
5. Gendered impact. Without deliberate empowerment, women risk falling even further behind. Already underrepresented in STEM and leadership, women face greater displacement risks in routine sectors — from clerical work to retail.

📦 BOX COLUMN: AI Through a Gender Lens

The Concern
Technology gaps are never gender-neutral. Women — especially in low- and middle-income countries — often have less access to devices, weaker digital skills, and fewer opportunities in high-paying tech sectors.

The Opportunity
AI can empower women:

• Entrepreneurship: Market access, financial planning, e-commerce support.
• Education: AI tutors and translation tools for girls in rural areas.
• Health: AI-driven diagnostics for maternal care where female doctors are scarce.
• Safety: Platforms that strengthen reporting and prevention of gender-based violence.

The Call to Action

• Scholarships for women in STEM.
• Quotas in AI policy committees.
• Investment in women-led AI startups.

A gender lens is not optional. It is essential for inclusive AI.

What Must Be Done: A Seven-Point Agenda

The answer is not to slow down AI. The answer is to speed up inclusion:

1. Invest in digital foundations. Last-mile broadband, affordable devices, reliable electricity, and public data platforms.
2. Launch national AI programs. Labs, sandboxes, fellowships — AI solutions tailored to local realities: agriculture, health, disaster response.
3. Reskill and protect workers. Wage inequality is not inevitable. Targeted reskilling, apprenticeships, and social safety nets are essential.
4. Democratize data and models. Open repositories and regional “AI clouds” give universities, SMEs, and governments affordable access.
5. Adopt inclusive governance. Algorithmic audits, transparent procurement, and global standards.
6. Make AI literacy universal — with a gender lens. From classrooms to community centers, training in local languages ensures no one is left behind.
7. Pool global financing. A global AI capacity fund — much like climate finance — can support infrastructure, skills, and governance in the Global South, with earmarked resources for gender empowerment.

📦 BOX COLUMN: AI and Education — Double-Edged Sword

The Concern
AI is transforming learning — but not always positively. Students may rely on AI shortcuts, bypassing critical thinking and research skills.

Risks for Formal Education

• Over-reliance on AI reduces original thinking.
• Erosion of critical analysis, problem-solving, and reasoning skills.
• Equity gaps: Students without AI access fall behind.
• Teacher challenges: Need to adapt assessment and pedagogy.

The Opportunity
AI can enhance learning if guided properly:

• Personalized tutoring for individual learning pace.
• Assistance in research, simulations, and language translation.
• Tools for teachers to provide targeted feedback.

Call to Action

• Integrate AI literacy into curricula.
• Train teachers to supervise AI usage responsibly.
• Design assignments that encourage original thinking.
• Ensure equitable access, especially in under-resourced schools.

Bottom Line
AI is not anti-educational — but without careful guidance, it risks undermining formal learning foundations.

Proof That It Works: Early Success Stories

Inclusive AI is already showing impact:

• Health: AI-assisted radiology tools help under-staffed hospitals triage cases faster.
• Agriculture: Satellite-driven advisory systems support small farmers, including women.
• Languages: Localized AI models make government services accessible in minority languages.
• Women in leadership: Programs in Africa and South Asia train women entrepreneurs in AI, with measurable success.

These pilots, if scaled, can provide replicable models for broader deployment.

What to Measure: Tracking Progress

Governments and donors should track:

• Broadband access with real usability.
• AI adoption among SMEs, not just tech giants.
• Wage gaps in AI-intensive industries.
• AI literacy levels among public professionals.
• Gender parity in digital access, AI training, and leadership roles.

These metrics ensure that AI advances shared opportunity, not entrenched inequality.

The Political Economy of AI: Who Wins, Who Resists

Countries and companies with a head start will protect their advantages. They may resist open models, global standards, or redistributive funds.

Coalitions matter. Governments, donors, civil society, and responsible businesses must act together. Incentives (funding, partnerships) and obligations (audits, licensing, standards) can align cooperation. The UN’s call for multilateral AI governance — including a global capacity-building fund — is a starting point, but urgent operationalization is critical.

A Turning Point, Not a Foregone Conclusion

AI is not destiny. It is a set of choices.

We can let the divide widen, leaving billions behind. Or we can invest in digital infrastructure, reskill workers, empower women, safeguard education, and democratize access. Done right, AI can be an engine of shared prosperity. Done wrong, it will entrench inequality.

The technology is moving fast. Our response must move faster.

Dr K.M. George
Secretary-General, Global Millets Foundation
CEO, Sustainable Development Forum