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The Rapid Rise of Generative Artificial Intelligences Transforms Digital Communication, Demanding Specific Skills to Interpret and Interact with These Revolutionary Technologies that Redefine the Market, Work, and the Future of Digital Literacy at All Levels.
With the popularization of tools like ChatGPT and its competitors, many people have come to believe they would have instant answers to any question or challenge.
However, frustration grew when confronted with wrong, confusing, or even fabricated answers by generative artificial intelligences.
The problem, however, is not always with the technology — but rather with the way questions are asked.
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Understanding the correct language to interact with these tools is the secret to unlocking their real potential.
The Promise Was Simple and Seductive
Type any question and receive a clear, quick, and accurate answer.
But reality showed that this magic doesn’t always happen.
When answers disappoint, the blame is often placed on the AI.
Phrases like “the AI didn’t understand,” “it hallucinated,” or “it said nonsense” are common.
However, according to technology experts, the problem often lies in the way the user formulates the question, not in the artificial intelligence itself.
Generative AI Is Different from Common Search Engines and Chatbots
Generative artificial intelligence is not a common chatbot, nor a simple search engine like Google.
It operates with its own logic, based on statistical patterns of language.
Contrary to what many think, these tools do not possess consciousness or real understanding of the world.
They are systems that simulate understanding to produce texts, images, codes, or videos, using vast databases to recognize and replicate patterns.
Treating these AIs like traditional machines is a surefire path to frustration.
Specific Digital Literacy Is Essential
One of the biggest current challenges is the lack of specific digital literacy for interacting with AIs.
It’s not enough to just ask any question — one needs to know how to ask, detail what is expected, and understand the limitations of the answer.
The majority of people still do not understand that these models do not update their knowledge in real-time, unless they are connected to external sources.
Therefore, they can often generate incorrect information or even invent data — a phenomenon known as AI “hallucination.”
Blindly trusting this content can lead to serious misunderstandings, especially in corporate and academic environments.
Beware of the Credibility of Answers
Another growing risk is the belief that everything the AI produces is correct just because the answer seems well-written and convincing.
The persuasive style of these answers can be misleading.
Common phrases like “Here’s an example” or “Here’s a summary” give an impression of security.
However, using these texts directly in reports, papers, or posts without review and verification is irresponsible and dangerous.
The responsibility to validate and compare the generated information rests entirely with the user.
The New Essential Skill: Prompt Engineering
Thus emerges a fundamental skill for the effective use of artificial intelligence: prompt engineering.
This competence consists of learning to formulate clear, detailed, and strategic requests to achieve the best possible results from AI tools.
And contrary to what many think, this is not exclusive to programmers or technology specialists.
Anyone can learn, and should learn, if they want to make the most of these technologies.
Five Pillars to Master Command Engineering
Experts define five pillars to master command engineering:
First, technological literacy, which includes understanding how the models work, their limitations, and risks.
Second, choosing the right platform, since each model has specific advantages — some are better for creating text, others for programming or generating images.
Third, crafting the prompt, which should be specific regarding the objective, tone, context, and format of the desired answer.
Fourth, validating content, which requires reviewing, adjusting, and comparing information with other sources, in addition to refining commands to improve results.
Fifth, ethical responsibility, which involves reflecting on the social impact of using AI, its possible biases, and who is responsible for the generated information.
Mastering AI in the Job Market
In the job market, mastering these skills is not just a differential, but a growing requirement.
Companies value professionals who can extract quick, reliable, and high-quality answers using artificial intelligence tools.
This learning is not limited to memorizing preset commands — it involves developing critical thinking, creativity, and strategy.
AI Did Not Come to Replace, but to Challenge
Far from replacing people, models like ChatGPT, Gemini, and others are here to provoke a transformation in how we work and communicate.
They challenge us to be clearer, more careful, and more aware when interacting with technology.
And this change, more than any ready answer, can make us better users — and perhaps even better people.
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