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GenAI Reflections

Generative AI: Reflections at the End of 2025

As 2025 comes to an end, I’d like to share some thoughts on Generative AI, a key technology in my work this year.

I highlight that, although its consumption continues to grow among users, the pace is not the same when it comes to automation.

I comment on the MIT report which indicates that 95% of Generative AI pilots have failed, leading me to consider the role of AI departments within organizations.

Finally, I review why Generative AI has mostly been applied in a few departments and share where I expect to see its evolution in 2026 … Continue readingGenerative AI: Reflections at the End of 2025

Artificial Intelligence in RPA

There is a tendency in many communications about RPA to add the words “Artificial Intelligence” to the message, in such a way that one might think a certain RPA technology provider includes Artificial Intelligence in their products.

It’s true that both technologies complement each other well, and from any RPA product you can easily call an external Artificial Intelligence service. But what really piqued my curiosity was whether RPA products actually include AI capabilities themselves.

In this article, I’ve tried to separate the wheat from the chaff and identify what the main RPA vendors actually include in their products. … Continue readingArtificial Intelligence in RPA

Don’t Be Misled by the OCR Percentage

I still see projects where the success of a data capture system is measured based on the OCR accuracy percentage. Even in some proof-of-concept tests, clients still tend to compare different solutions according to the extraction percentages achieved.

However, this figure is not a fundamental business parameter. What decision can an executive make if we tell them that one solution has a capture rate of 80% and another has 70%? Most likely, none—unless other factors that affect the calculation of a potential return on investment are also considered.
Continue readingDon’t Be Misled by the OCR Percentage