Why Accountants Still Choose Excel Over AI

When I read the news that, despite the unstoppable advance of Artificial Intelligence, a decades-old program continues to be the preferred choice for accounting professionals, I must admit a smile of astonishment appeared on my face. In an era obsessed with automation and innovation, this resistance—almost a form of loyalty—immediately prompted me to reflect. In my role as Editor-in-Chief of Cortex News, I am always on the lookout for trends that defy expectations, and this is definitely one of them. What makes such an “old” tool still so powerful and indispensable? It is a question that, in my view, deserves deep analysis.

The Enduring Appeal of a Silent Giant

My first reflection, when thinking about a program like the famous spreadsheet, is its universality and almost intrinsic malleability. It is not just a tool; it is a blank canvas for numbers, an extension of the accountant’s logical thought process. From an engineering perspective, its familiar interface, the ability to manipulate data at a granular level, and the transparency of every calculation are, in my opinion, the pillars of this loyalty. Professionals have spent years mastering these tools, building complex models and established workflows. Trusting a “black box” AI algorithm for critical compliance and reporting tasks, where every cent counts, is a leap many are not yet ready to take without direct, verifiable control.

Complementarity, Not Replacement

This does not mean accountants are averse to innovation. Quite the contrary. I have observed an exciting openness toward AI to automate repetitive tasks like data entry, transaction reconciliation, or anomaly detection. AI excels at processing immense volumes of information and spotting patterns that would escape the human eye. However, for strategic analysis, complex scenario planning, or creating custom reports requiring subtle data interpretation, the decades-old tool offers unmatched flexibility. That is where the human, with their experience and judgment, interacts directly with the numbers. AI, in this context, becomes a powerful co-pilot, not an autopilot that eliminates the need for manual navigation.

Lessons for AI Development

From my perspective, this trend offers a crucial lesson for Artificial Intelligence developers. The success of software is not measured solely by computational power or cutting-edge algorithms, but also—and above all—by its ability to integrate seamlessly into human workflows while respecting the need for control, transparency, and customization. The AI solutions that prevail will be those that act as intuitive extensions of human capabilities rather than complete replacements. Building trust also means allowing users to understand and, if necessary, intervene in processes. Usability and familiarity remain non-negotiable requirements, especially in such critical sectors.

In my opinion, this persistence is not a sign of backwardness, but rather a powerful lesson on the importance of usability, control, and trust in the tools we use daily. It shows us that for AI to be truly transformative, it must learn to integrate fluidly and transparently into existing workflows, offering enhancement without stripping away control or understanding. It is not a matter of replacement, but of elevation. But what do you think, readers? Do you believe AI will ever completely supplant traditional tools, or will coexistence remain the norm for decades to come?