Responsible AI use in business: ethics and security

With the growing use of AI, there is a strong emphasis on what it can help us solve and how much easier it can make our lives, but we are forgetting that this goes far beyond simple process efficiency. One topic that has been widely discussed is job displacement brought about by AI. It does have a social impact, since fewer people are needed to carry out the same tasks, and those tasks get done faster. It is a widely debated subject, but it is not the focus I want to give this article.

The issue is that we are currently using AI indiscriminately, even irresponsibly. Some influencers use their channels to promote free versions, unaware that this can open the door to compromising security, copyright and creative work, among many other critical aspects involved in the responsible use of artificial intelligence.

And this is no minor matter: the global AI market is estimated to reach 826 billion by 2030, with marketing and sales among its most widespread business applications (Statista, 2025; McKinsey, 2024). We are adopting, at an unprecedented pace, a technology whose ground rules are only now being written.

What I heard at a talk and haven't been able to stop thinking about

• Using AI without licensing and integrating it into key business processes, overlooking the fact that the information shared through it is subject to usage restrictions. This can violate confidentiality laws, rights and data protection.
• Ownership of the rights to products generated with AI. Here it is essential to document and be clear about human involvement in the process, so that intellectual property rights over the work can be secured. On this point, the Andean Community, in its Common Regime on Copyright (Art. 3), establishes that the author is a natural person, which, as the rules stand today, excludes creations made entirely with AI. This is not an isolated position: both the World Intellectual Property Organization (WIPO) and the U.S. Copyright Office agree that AI-generated works without sufficient human involvement tend to fall into the public domain (Palma Peña, 2025).
• The security gaps we are exposed to when AI is used without clear organizational processes. We have the tools, but we don't give the team the right guidance, and they end up being used indiscriminately.

It's not about not using it. It's about using it well.

Unfortunately, we are seeing a proliferation of videos and information that indiscriminately teach people how to use AI while ignoring its responsible use. It's not about avoiding it, but it is important to focus on the vendors' usage policies, on the responsibility we take on when we use it, and on the emerging regulatory framework that is taking shape as a result.

Data protection laws are not left out here; quite the opposite, this is where we need to be most careful. Where is customer data ending up if we rely on free versions of AI tools? What information are we handing over that we shouldn't?

The academic literature confirms it: AI systems collect, process and analyze large amounts of personal data, and the associated privacy risks directly affect customer trust and satisfaction (Barari et al., 2024). The answer is not to react after an incident, but to adopt what researchers call "privacy by design": preventive strategies built in from the earliest stage of the process, not added later as a patch (Paredes, Robayo-Pinzón & Rojas-Berrío, 2025).

It's not just about generating content or products, or getting tasks done faster. It's about understanding that full responsibility lies with the human using it, and with whether or not they are handing total or partial control over to AI.

The five dimensions every company should review

When examined in detail, responsible AI use is not a single issue to keep an eye on. According to Paredes, Robayo-Pinzón & Rojas-Berrío, 2025, there are 5 aspects to consider:

• Privacy and data protection. Knowing what data is collected, how it is used and under which regulations it is handled.
• Trust and autonomy. Advanced personalization must not feel like manipulation; transparency is the foundation of trust.
• Governance and corporate responsibility. Companies must design their own usage policies.
• Value creation. Making the most of technology without losing the human element and authenticity in the customer relationship.
• Regulatory frameworks. Keeping up with legislation that moves more slowly than technology, but is already arriving.

These are not minor issues; on the contrary, they are what we should be talking about, not just the unchecked rollout of AI.

Emerging framework: what's coming

As for the regulatory framework, although it is still in its early stages, three legal references are worth mentioning because they are changing the rules of the game:

PL 043 / 2025 — Colombia

Colombia's AI bill

Law 2502 / 2025

Aggravating criminal circumstance for malicious use of AI

US Copyright 2025

Report Part 2 — Copyright & AI

Fortunately, at Arcetec we have already understood this

Fortunately for us, at Arcetec we understood long ago that unlicensed tools create security gaps for everyone. We firmly believe that a company that does not pay for the licenses it uses for its most important work is, without realizing it, mortgaging its customers' security, the ownership of its own work and its legal peace of mind.

That's why we work with licensed tools, and we are structuring our internal policies for AI use. Efficiency matters, yes. But trust, legality and responsibility matter more, because they are what sustain everything else.

The question, then, is not whether you are going to use AI. It's how you are going to use it.

Sources

Paredes, M. R., Robayo-Pinzón, O. & Rojas-Berrío, S. (2025). Dimensiones éticas en la implementación de inteligencia artificial (IA) para estrategias de marketing: un análisis sistemático de desafíos y oportunidades. Revista Académica ECO, 32, 1-20.

Palma Peña, J. M. (2025). Derechos de autor y licencias de la inteligencia artificial generativa: un análisis desde la ciencia abierta en América Latina. Revista Interamericana de Bibliotecología, 48(3).

Statista (2025); McKinsey (2024); European Commission (2025) — cited in the sources above.