It’s Not All About AI; Do I Really Need AI or Just Better Processes?

Some time ago, during a conference about Artificial Intelligence (AI) I attended—where the focus was on “all the possibilities and new horizons of AI”— One of the speakers asked questions that made me rethink everything I had heard about the benefits of AI.

Among those questions was the doubt of whether we truly need AI—or if what we actually need is to improve our processes: development, ideation, planning, execution, etc.

Hand in hand with this question comes our great responsibility as professionals: to guide our clients and users in understanding what their real needs are.

The decision to implement AI in a company is clearly an important and strategic step, since it can help solve many problems faster and more efficiently (in some cases). But on the other hand, considering what has been said, we should also start analyzing existing processes in detail and improving them—because in some cases, the implementation of AI is unnecessary and/or inefficient, and only leads to more expenses and training requirements. And that’s where the biggest problems often appear.

A key part of this reflection is understanding the true nature of the challenges we face. Companies are often drawn to the idea of AI as a “magic solution” that will fix everything, but it is essential to conduct a deep analysis of the specific needs and obstacles at hand.

For this reason, I invite you to think about the following questions:

• What are the company’s business goals and objectives? Is AI implementation aligned with them, or is it simply following a trend?
• Where are the bottlenecks in current processes? Can AI effectively and efficiently address these issues?
• Do we have the right resources—both trained personnel and the necessary technological infrastructure—to implement and maintain AI systems?

If we were to ask an AI about this topic, it would likely say something like:

“It’s important to understand that AI is not a one-size-fits-all solution. It can be a powerful tool in certain contexts, such as automating repetitive tasks, analyzing large volumes of data, or making complex data-driven decisions. However, it is not the answer for every situation.”

I’d like to use this response as a starting point for another powerful phrase that stayed with me: “Data is the gold of the future.”

We live in a constantly evolving digital age, where information has become one of the most valuable and transformative resources.

Today, data generates knowledge, innovation, and growth. It helps us understand where trends are heading, uncover patterns, and gain insights that drive decision-making.

This is why major companies like Google, Meta (formerly Facebook), and Amazon invest so heavily in data collection: because data itself is a significant source of revenue, whether through targeted advertising, personalized recommendations, or other business models.

But simply having a large volume of data does not guarantee success. It is crucial to filter, organize, and analyze it properly. At this point, AI can certainly help us—but we must never forget that the main actors in this equation are us, the professionals. It is our judgment, built through experience, that must take precedence over AI tools.

Artificial Intelligence will help us change the world, understand how we are evolving, and where we are heading. But we, as a society, will always remain the main drivers of these advances.