Who Governs AI and Who Lives With the Outcome?

Artificial intelligence is not just another technological wave. It is a structural force reshaping labour markets, education systems, political discourse, warfare, creativity, and even the epistemic foundations of truth. Yet the governance of AI today is overwhelmingly concentrated in the hands of political leaders, regulators, and institutional decision-makers who are neither its primary users nor those who will live longest with its consequences. This is a profound misalignment.

Illustration by The Geostrata

Technology governance cannot be led exclusively by those who are not first-order users of the technology. The generation that will build with AI, learn through AI, compete against AI in the labour market, and form social identities mediated by AI must have a direct and structured role in governing it. Otherwise, we risk repeating the mistakes made in the governance of the internet, mistakes rooted in misunderstanding, regulatory lag, and philosophical shallowness.

The internet was initially governed as a technical infrastructure rather than as a socio-political environment. Early policy discussions underestimated its capacity to shape cognition, democracy, social cohesion, and the concentration of power. Regulators failed to anticipate surveillance capitalism, algorithmic manipulation, platform monopolies, and information warfare. Governance frameworks emerged reactively, often after harms had already metastasised.

AI presents a similar inflection point but at a greater speed and scale. Unlike the early internet, AI is not merely connective; it is cognitive. It generates content, makes decisions, mediates knowledge, and increasingly acts as an autonomous agent within economic and institutional systems. The stakes today are higher, and the feedback loops are tighter.

The consequences of governance failure could be deeper and more irreversible. And yet, much of today’s AI governance debate is dominated by senior policymakers and executives who are not immersed in the lived reality of AI-native environments. Many decision-makers encounter AI as a policy abstraction through briefing notes and regulatory consultations rather than as a daily cognitive interface embedded in their education, work, and social interactions.

By contrast, younger generations experience AI as an operating layer of everyday life. Students use generative systems for research and drafting. Creators use AI for design and production. Young entrepreneurs build companies around AI APIs. Teenagers interact with AI companions and recommend systems that shape identity formation and worldview. This cohort understands intuitively how AI systems influence agency, creativity, attention, and trust. Governance that excludes this lived experience will inevitably be incomplete.

Youth participation in AI governance should not be symbolic or performative. It must be institutionalised. Youth councils attached to national AI strategies, advisory seats within regulatory bodies, structured representation in multilateral AI forums, particularly from the Global South, where demographic youth bulges intersect with rapid technological adoption. Participatory technology assessment mechanisms should become standard features of governance architecture. The goal is not generational replacement, but generational integration.

There are three core reasons why this is essential. First, epistemic competence. Those who are first users of AI systems understand their affordances and failure modes in ways that cannot be fully captured by expert testimony alone. They see how recommendation engines influence political discourse in student communities. They experience how AI tools reshape academic integrity norms. They witness how automated hiring systems alter entry-level job prospects. This experiential knowledge is not anecdotal rather it is diagnostic.

Second, legitimacy. AI governance will only be durable if it commands trust across generations. A framework perceived as imposed by distant elites, technologically detached and temporally insulated from long-term consequences, will struggle to maintain credibility. Involving younger leaders creates shared ownership of norms and responsibilities, strengthening compliance and societal buy-in.

Third, the moral horizon. AI’s most profound effects will unfold over decades. Those who will inhabit that future longest have a moral claim to shape its trajectory. Intergenerational justice is not only an environmental principle, but it is a technological one. Decisions about AI safety thresholds, surveillance norms, biometric integration, autonomous weapons, and labour automation will shape the opportunity structures of people who are currently students or early-career professionals.

The argument here is not that youth alone should govern AI. Experience, institutional memory, and geopolitical awareness matter deeply. But technological literacy, lived immersion, and long-horizon stakeholdership matter just as much.  Moreover, we must acknowledge that governance philosophies themselves need renewal. Much of current regulatory thinking is rooted in industrial-era models: compliance checklists, sectoral silos, and jurisdictional fragmentation.

AI, however, operates as a general-purpose technology embedded across domains. Governing it demands systems thinking, adaptive regulation, and iterative oversight mechanisms co-designed with users.

Younger leaders with their entrepreneurial bent of thinking are often more comfortable with open-source ecosystems, agile experimentation, and networked collaboration. These sensibilities align more naturally with the distributed architecture of AI innovation. They can help design governance frameworks that are dynamic rather than static, capable of evolving alongside technological capability.

If we fail to integrate youth meaningfully, we risk three familiar outcomes. Overregulation born of fear, stifling innovation and pushing development into opaque jurisdictions. Underregulation driven by capture or misunderstanding, allowing harms to scale unchecked. Or symbolic regulation that gestures at control while leaving structural incentives untouched. 

Thus, the question is not whether young leaders are ready to help govern AI. It is whether existing governance structures are ready to share power with those who will live longest with the consequences.

Disclaimer: The views and facts presented by the author are his own and do not necessarily reflect the views of the organisation.

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BY S YASH KALASH

SENIOR FELLOW AT CIGI

TEAM GEOSTRATA

info@thegeostrata.com