The rise of artificial intelligence in the business environment has brought with it fascinating advancements, but also a certain confusion. In a landscape where new tools, promises of total automation, and grandiloquent speeches emerge every week, many organizations are faced with a fundamental question: do we really need to apply AI in our business, or are we doing it simply because it’s trendy?
The responsible answer to that question should always be the same: technology only makes sense if it solves real problems. And in the case of AI, this becomes even more relevant. Artificial intelligence is powerful, yes, but it must also be precise, well-directed, and aligned with the strategic objectives of each company. Implementing it without a clear purpose is like using a cannon to kill mosquitoes.
A purpose for AI
Far from being a magic solution for everything, AI can be a profitable, efficient, and harmonious ally when used wisely. When directed towards specific tasks where it adds real value, it not only transforms processes but also frees up time, improves decision-making, and reduces error margins. At Devol, we verify this daily with projects in which artificial intelligence acts as a catalyst for change, rather than just a technological adornment.
Real applications to achieve tangible solutions
One of the common great challenges in many companies is the management of unstructured information. Thousands of documents circulate daily in sectors such as legal, healthcare, administration, or finance, and a large part of them contains key data that gets trapped in PDFs, scanned reports, contracts, or policies. Traditionally, extracting this information has been a manual process, slow and with a high risk of human error.
This is where AI can make a tangible difference. Through models specifically designed for natural language understanding and computer vision, it is now possible to accurately interpret documents and transform texts into useful data for decision-making.
For example, an insurance company that receives hundreds of medical reports can automate the reading of those documents, extracting dates, diagnoses, or coverage, and freeing teams from repetitive tasks. This capability not only improves operational efficiency but also speeds up response times and reduces costs.
Another common bottleneck in companies lies in access to databases. Although the information is there, it is often confined to those who are proficient in SQL or understand the technical structure of the systems. This limits the autonomy of business teams, slows down analysis, and creates a constant dependence on the IT department.
Thanks to advancements in natural language processing, it is now possible to interact with databases using just human language. Instead of writing complex queries, it’s enough to ask a question like “Which customers have purchased from us more than three times this year and still have pending orders?” to receive a clear and actionable response.
This type of solution does not eliminate the role of analysts, but it does expand the analytical capacity of other profiles within the company, allowing marketing, sales, or finance to work with data directly, immediately, and without intermediaries.
AI is what is needed… if it really brings advantages
The key is to understand that artificial intelligence should not be imposed as a generalized standard, but rather proposed as a response to specific problems. Each company has different needs, and applying AI indiscriminately can even be counterproductive.
In contrast, when a specific task is identified —such as interpreting documents, making data more accessible, or automating routine decisions— and a well-trained solution is implemented for it, the impact is immediate and measurable.
Artificial intelligence, when applied with common sense and clear objectives, becomes a profoundly human technology: it does not replace, but empowers. It does not complicate, but simplifies. And most importantly, it does not present itself as an end in itself, but as a means to help people and businesses work better.
