Michael Ogbu

Conversations about AI governance have become increasingly common in recent years. Governments are developing regulatory frameworks, technology companies are publishing responsible AI principles, and experts continue to debate the merits of regulation versus deregulation.

Despite these efforts, one important question often receives less attention than it deserves: Who is AI governance ultimately for?

The answer may seem obvious – the people. Yet many of the discussions shaping the future of artificial intelligence are dominated by governments, regulators, technology companies, industry groups, and policy experts. While these stakeholders undoubtedly have important roles to play, the voices of ordinary citizens often remain underrepresented.

This creates a fundamental governance challenge. The individuals most affected by AI systems frequently have the least influence over how those systems are designed, deployed, and governed.

As artificial intelligence becomes increasingly embedded in our social, economic, and political institutions, governance must be taken to where it belongs – the people.

The Growing Gap Between Governance and Society

Artificial intelligence is no longer a technology confined to research laboratories or technology firms. It influences hiring decisions, credit assessments, educational tools, healthcare systems, online experiences, customer service interactions, and countless other aspects of everyday life.

In many cases, people interact with AI systems without fully understanding how decisions are made, what data is being used, or how outcomes are generated.

Yet when governance discussions occur, they often focus on regulatory obligations, industry competitiveness, national interests, technological innovation, or economic growth. And while these are important considerations, they do not fully address a critical reality: AI governance is ultimately about people.

Because every governance framework, regardless of its complexity, should answer a simple question:

How does this improve the lives, rights, opportunities, and protections of the people affected by the technology?

When this question becomes secondary, governance risks becoming an exercise in control rather than a mechanism for public benefit.

Lessons From Access and Inclusion

I often reflect on the early days of mobile telecommunications in Nigeria.

When GSM services were first introduced, owning a mobile phone was a privilege reserved for a relatively small segment of society. SIM cards were expensive, mobile devices were costly, and call tariffs placed communication beyond the reach of many ordinary citizens.

The technology existed, but access remained limited.

Over time, policy decisions, market competition, and broader reforms transformed the telecommunications landscape. Mobile communication eventually became accessible to millions of people who had previously been excluded.

The most important lesson from that experience is not whether regulation or deregulation was responsible for the outcome. And I understand that reasonable people may disagree on that point.

But the lesson is that successful governance should ultimately be measured by its impact on people.

Technology achieves its greatest value when its benefits become accessible, meaningful, and responsive to the needs of society.

The same principle should guide AI governance.

Beyond Regulation Versus Deregulation

Much of today’s AI governance debate has become polarized around regulation and deregulation.

One side argues that stronger regulation is necessary to protect society from potential harms. The other warns that excessive regulation may hinder innovation and reduce competitiveness.

While both perspectives contain valid concerns, focusing exclusively on this divide risks overlooking a more important issue.

Governance is not merely about determining how much control should exist. It is about determining who benefits from that control and whether the interests of affected communities are adequately represented.

A governance framework can be highly regulated and still fail to address public concerns. Likewise, a more flexible regulatory approach does not automatically guarantee fairness, accountability, or inclusion.

The real question is not whether governance should be stricter or lighter. The real question is whether governance is sufficiently people-centered.

What People-Centered AI Governance Looks Like

Taking governance to the people does not mean transferring complex regulatory decisions entirely to the public. Governments, technical experts, researchers, and industry leaders all have essential roles to play.

However, it does mean ensuring that public interests are not treated as an afterthought.

A people-centered approach to AI governance should include several principles.

Meaningful Public Participation

Communities affected by AI systems should have opportunities to contribute to discussions about how those systems are deployed and governed.

Public consultation should be more than a procedural requirement. It should be a genuine mechanism for understanding societal concerns, expectations, and priorities.

Transparency and Understandability

People cannot meaningfully engage with systems they do not understand. Organizations deploying AI should strive to communicate how systems function, what data they rely upon, and how important decisions are made.

Transparency is not merely a technical requirement. It is a foundation for trust.

AI Literacy as a Governance Tool

Governance does not begin with regulation alone. It begins with understanding.

A society that lacks the knowledge necessary to evaluate AI technologies will struggle to participate meaningfully in governance conversations. This is why AI literacy should be viewed not only as an educational priority but also as a governance priority.

The more informed people are, the more effectively they can advocate for their interests and hold institutions accountable.

Accountability to Those Most Affected

Organizations should be accountable not only to regulators and shareholders but also to the individuals and communities affected by their AI systems.

This requires mechanisms for feedback, redress, oversight, and continuous evaluation.

People should not simply experience the consequences of AI systems. They should have avenues through which concerns can be raised and addressed.

The Future of Governance

The future of AI governance will not be determined solely by laws, policies, or technological breakthroughs.

It will also be shaped by whether governance frameworks remain connected to the people they are intended to serve.

Technology continues to evolve rapidly. Governance must evolve alongside it. But as governments, organizations, and technology companies work to shape the future of artificial intelligence, they should remember a simple principle:

The ultimate purpose of governance is not to govern technology.

It is to ensure that technology serves people. The more closely AI governance aligns with that objective, the more likely it is to earn the trust, legitimacy, and public confidence necessary for long-term success.