Antonio Tejeda Encinas | CEO of META Channel Corporation <\/p>\n
Most companies believe they have not yet decided to adopt artificial intelligence. The truth is simpler: they are already using it. An employee summarises contracts with a generative tool. The sales team automates its replies. Marketing produces campaigns on external platforms. HR screens job applications. Senior management asks for reports prepared with the help of digital assistants. Nobody calls it an \u201cAI project\u201d, but in legal terms that is exactly what it is.<\/p>\n
That is the first mistake. Many organisations still assume that artificial intelligence enters the business on the day a major technology plan is approved, a contract is signed with a specialist provider or a digital transformation is announced. Reality is far less tidy. AI gets in earlier, quietly, through the side door: a free account, a browser extension, a tool bundled with the office suite, a marketing platform, a CRM, a customer service system, a data analytics application, or simply a prompt written by a well-meaning employee.<\/p>\n
And once that happens, the company is no longer facing a mere question of productivity. It is facing a question of governance.<\/p>\n
Artificial intelligence does not operate in a vacuum. It runs on data, instructions, documents, patterns, historical records, profiles, images, conversations, case files, emails, customer databases, internal information and, very often, personal data. That is why the business debate on AI cannot be confined to asking whether a tool saves time or improves results. The right question is a different one: what information goes into the system, what it is used for, who controls it, where it is processed, how long it is kept, which provider is involved, which rights may be affected, and what documentary evidence the company has to show that all of this is under control.<\/p>\n
For years, many companies have treated regulatory compliance as a layer of paperwork. A privacy policy, some terms and conditions, a contract with the provider, an internal clause: a document that is filed away and that nobody looks at again until there is an audit. That model no longer works for artificial intelligence. Not because documents have stopped mattering, but because on their own they are no longer enough. With AI, compliance has to be connected to the way the technology is actually used. It must be demonstrable in practice.<\/p>\n
This is a profound shift, because it moves the conversation away from technology and towards corporate responsibility. AI is not just a tool that performs tasks. It is an infrastructure for decision-making, analysis and the processing of information. It can affect customers, employees, suppliers, consumers, investors and public authorities. It can produce errors, bias, leaks, opaque decisions, incorrect attributions or unforeseen uses of data. And when that happens, the explanation that \u201cthe system did it\u201d does not exonerate the company. On the contrary, it raises a more uncomfortable question: who authorised that system, and under what controls?<\/p>\n
Moreover, the EU Artificial Intelligence Act does not remove the obligations that already existed. It adds to them. This point is essential. Some companies are starting to talk about the AI Act as if it were a new, self-contained piece of legislation, as if adapting to it were enough to be covered. It is not. If an AI system processes personal data, the General Data Protection Regulation (GDPR) continues to apply in full. If the system is built into employment processes, labour law and equality risks arise. If it relies on critical technology providers, contractual obligations, cybersecurity and operational continuity come into play. If it affects consumers, digital platforms or financial services, the web widens further still.<\/p>\n
That is why the phrase \u201cAI compliance\u201d is deceptively simple. You do not comply with a single piece of legislation. You comply with an architecture.<\/p>\n
Consider something that seems entirely routine: an SME that lets its staff use generative tools to prepare sales proposals, analyse contracts or summarise client documentation. There may be no bad faith. There may even be efficiency. But if confidential information, personal data, trade secrets or third-party documents are fed into systems the company does not control, the risk already exists. The fact that it cannot be seen does not mean it is not at work.<\/p>\n
That is the point many companies have yet to grasp: European digital compliance is no longer a collection of separate documents. It is a web of responsibility.<\/p>\n
That is why AI governance cannot be reduced to the IT department. Nor can it be locked away in the legal department. It requires leadership, business judgement, regulatory knowledge, sufficient technical understanding and the capacity to execute. The data protection officer will see one part of the problem. The systems team will see another. The technology provider will see another. The external lawyer will see yet another. But \u201csomeone\u201d has to look at the whole, set priorities, identify overlaps, decide what must be done first and keep a record showing that the company has acted diligently.<\/p>\n
That is the difference between using technology and governing it.<\/p>\n
On 3 June, at Smart Meeting Tenerife, I will address precisely this question: how the main European rules already affecting companies, directors and investors fit together, and why the real challenge is not knowing every acronym but understanding the web they form. We will talk about artificial intelligence, data protection, cybersecurity, crypto-assets, digital platforms, connected products, technology contracts and corporate liability. Not as isolated subjects, but as parts of a single regulatory architecture.<\/p>\n","protected":false},"excerpt":{"rendered":"
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