Why Marketing Can No Longer Treat AI Ethics as a Side Role

For years, AI ethics has lived comfortably at the level of principles. Fairness. Transparency. Accountability. Trust. They appear in policy documents, keynote slides, and brand manifestos, reassuring well-intentioned and often disconnected from day-to-day decision-making.

For marketing, this gap matters more than in most other functions. AI systems do not just optimize operations; they shape attention, visibility, persuasion, and choice.

A recent academic paper, Who Is an AI Ethicist?, quietly disrupts that comfort zone. Instead of asking what ethical AI should look like, it asks a far more operational question: who is actually responsible for making ethics work inside organizations?

For marketing leaders working with AI-driven targeting, personalization, optimization, and automation, this question is no longer academic. It goes straight to the heart of how value is created and where risk accumulates.

The myth of shared responsibility

In many organizations, AI ethics is treated as a diffuse responsibility. Legal teams handle compliance. Product teams worry about bias. Communication manages reputational fallout. Leadership talks about values.

Ethics becomes everyone’s job, which in practice means it belongs to no one in particular.

The study shows why this model fails. Through an empirical analysis of LinkedIn profiles and job postings across Europe, the UK, and the US, the authors reveal a fast-growing but deeply fragmented profession. “AI ethicist” can mean a data scientist, a policy advisor, a governance specialist, a researcher – or, at times, a rebranded compliance role.

This lack of clarity is not just an HR problem. It creates ethical blind spots precisely where AI systems interact with human behavior, persuasion, and choice.

In other words: marketing.

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