Artificial intelligence has successfully taken over every conversation about automation and improving productivity in the last couple of years, and with good reason. In this article I will provide some reflections around both the incredible benefits of AI in data managements, but also when and why traditional data logic and good old fashion automations can solve your task in a better way.
Just to clarify, this post is not intended to talk down AI. It is actually co-written by AI as we do with most texts nowadays. It is intended to enlighten you about some of the areas where AI may be a misleading, less accurate, and/or resource heavy solution compared to the practices we have relied on for many years already.
AI as a leap in data management and analysis
For decades, automation has been strictly rule-based. This is fantastic for predictable, repetitive tasks, but it shatters the moment it encounters ambiguity.
This is where AI truly shines. Instead of just following explicit instructions, AI models can learn from your data, which opens up entirely new capabilities:
Understanding Unstructured Data: An AI can read an email, understand the sentiment, and categorize the topic, all...
