Responsible AI

Who’s in Control:

The Board or the Code?

A Call for Responsible AI Governance

Artificial Intelligence is no longer a futuristic concept. It is already reshaping business models, decision-making processes, and competitive strategies across industries. From predictive analytics to automated operations and customer interaction, AI is becoming a strategic asset. But as its power grows, so does a pressing question:

Who is truly in control, the board or the code?

The Illusion of Control

Boards of directors are responsible for overseeing strategy, managing risk, and ensuring long-term value for stakeholders. Yet in the case of AI, many are unknowingly giving up influence to complex systems they do not fully understand. Algorithms trained on massive datasets are making decisions that affect hiring, healthcare, finance, and national infrastructure.

While the board approves AI projects, the actual decisions made by these systems may unfold independently of human judgment. This creates a critical governance dilemma: how can you govern something you do not fully grasp?

Beyond the Checkbox

AI governance is often treated as a compliance formality. A policy document here, an ethics committee there. But surface-level oversight is no longer enough. Boards must confront the deeper and more difficult questions:

• Are we allowing AI to make strategic decisions without clear accountability?

• Do we understand the biases hidden in our data and algorithms?

• Who is responsible when something goes wrong, the vendor, the developer, or the board?

These are not theoretical concerns. In many sectors, AI already plays a central role in core operations. The risks, from reputational damage to regulatory violations and ethical failures, are growing.

From Oversight to Stewardship

Boards must move from passive oversight to active stewardship. Traditional governance models are not designed for self-learning, adaptive systems. Directors need to become AI-literate leaders who can ask the right questions and set boundaries that protect people, organizations, and society.

This includes:

✅ Demanding transparency in AI model logic ✅ Ensuring responsible data management and bias monitoring ✅ Reviewing ethical implications regularly ✅ Planning for errors and unintended outcomes ✅ Aligning AI use with company values and stakeholder interests

Responsibility Before the Point of No Return

AI is not inherently harmful. But unmanaged or misunderstood AI can create real damage. As organizations move faster into automation, there is a greater need for thoughtful leadership that takes responsibility for its use.

The real question is not whether AI can be controlled. It is whether boardrooms are prepared to act before the technology outpaces human judgment.

Boards that take this responsibility seriously will help build a future where AI supports human values. Those that delay may find themselves governed by systems they neither question nor control.

Author's Note: I help boards and executive teams build responsible AI strategies, assess governance frameworks, and ask the right questions. If you are ready to bring this discussion to your boardroom, I would be glad to support.