The Quiet Risks of Agentic AI, and Our Responsibility to Act Now

I have spent much of my professional life observing how technology reshapes institutions, work, and human behavior. Few developments, however, rival the speed and subtlety with which agentic artificial intelligence is embedding itself into our daily lives. While much of the public discourse focuses on AI’s promise, efficiency, scale, and innovation, we have been far less rigorous in confronting its risks. That imbalance should concern us. The danger is not that AI will arrive suddenly and overwhelm us, but that it will integrate so seamlessly that we stop questioning its influence altogether.

One of the most underestimated risks of agentic AI is overdependency. Once AI systems become part of everyday workflows, complacency follows. We have already seen this pattern with simpler technologies. Most of us no longer navigate unfamiliar places without digital maps, even though we know these tools can be wrong. In the workplace, spelling, grammar, and even basic reasoning are increasingly delegated to automated systems. When outputs appear polished, we assume they are correct. Over time, this erodes our capacity for independent judgment. The issue is not that AI assists us, but that it quietly replaces cognitive vigilance. When humans stop checking, validating, and questioning, errors become systemic rather than incidental.

At the other end of the spectrum lies the malicious use of AI, particularly in media and information ecosystems. We are entering an era in which images, audio, and video can no longer be trusted by default. Deepfakes and AI-generated content have already been used to mislead audiences, influence political discourse, and damage reputations. What makes this especially troubling is not merely the sophistication of the technology, but the speed at which false content spreads before it can be debunked. Even when forgeries are exposed, the harm is often already done. Public trust, once lost, is difficult to restore. In this environment, skepticism becomes the norm, and genuine evidence risks being dismissed alongside fabricated material.

A third, and perhaps most consequential, challenge is the absence of comprehensive legal and regulatory frameworks governing AI use. Existing privacy, cybersecurity, and copyright laws were written for a pre-AI era. They do not adequately address scenarios in which AI systems generate content that violates privacy, enables fraud, or infringes on intellectual property. When abuse occurs, victims are often left without clear avenues for redress. Law enforcement agencies may lack both the technical expertise and the legal mandate to respond effectively. While recent legislative efforts suggest that governments are beginning to take AI seriously, these initiatives remain nascent. For now, we are operating in a legal gray zone, where accountability is unclear and enforcement mechanisms are underdeveloped.

This regulatory gap has practical consequences for organizations and individuals alike. Companies may unknowingly violate privacy or copyright by deploying AI-generated content trained on proprietary or protected material. Individuals may publish AI-assisted work without realizing it exposes them, or their employers, to legal and reputational risk. In the absence of clear laws, responsibility defaults to the user, whether or not they fully understand the implications of the tools they are using. This asymmetry is unsustainable.

What, then, can be done in the immediate term? Waiting for regulation to catch up is neither prudent nor ethical. Organizations must take proactive responsibility by establishing internal codes of conduct governing AI use. Ethical guidelines should not be treated as optional or symbolic; they must be operationalized through training, oversight, and accountability mechanisms. Employees should be taught not only how to use AI tools, but when not to use them, and how to critically evaluate their outputs.

Individuals, too, have a role to play. While AI use in private experimentation may feel like a free-for-all, the moment AI-generated content enters the public domain, through publication, professional work, or client-facing materials, it carries consequences. Reputational damage can be swift and severe. No organization wants to be accused of deceptive practices, privacy violations, or intellectual property theft, even if those outcomes were unintentional.

Finally, education and workforce development must evolve alongside AI adoption. Training future professionals to work responsibly with AI is as important as teaching them technical proficiency. Ethical literacy, critical thinking, and an understanding of AI’s limitations must become core competencies, not afterthoughts.

Agentic AI is not inherently dangerous, but unexamined reliance on it is. The choices we make now, before comprehensive regulation is in place, will shape public trust, institutional integrity, and the long-term legitimacy of AI itself. Responsibility cannot be deferred. If we fail to act thoughtfully today, we may find tomorrow that the risks we ignored have quietly become the norms we regret.

 

About Me:

Dominic “Doc” Ligot is one of the leading voices in AI in the Philippines. Doc has been extensively cited in local and global media outlets including The Economist, South China Morning Post, Washington Post, and Agence France Presse. His award-winning work has been recognized and published by prestigious organizations such as NASA, Data.org, Digital Public Goods Alliance, the Group on Earth Observations (GEO), the United Nations Development Programme (UNDP), the World Health Organization (WHO), and UNICEF.

If you need guidance or training in maximizing AI for your career or business, reach out to Doc via https://docligot.com.

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