Most business problems are really about making good decisions. When you’re deciding which project to prioritize next, how much inventory to hold or which ingredients to use in a new product, you’re constantly trading off goals with constraints.

Does the general public systematically and repeatedly misunderstand the nature of the value AI actually creates?

Language models have dominated the current AI wave and hype cycle. Interacting with them creates an illusion of human-likeness. This thinking is monolithic, and there are far more interesting scenarios for driving real value from AI.

The concept of agency in artificial intelligence has become a focal point in both technical and public discourse. At Renessai, we have strongly argued that AI does not have agency at all, but, a closer look at both research and practical experience reveals a more nuanced reality. One could ponder even what is even the thinking we humans do.

Everyone has their own mental models about what AI means. To add to that, the meanings of words change over time. For example, in relation to AI, many have recently started to talk about “agents”. Not too long ago, AI was synonymous with the Large Language Model (LLM). And a few years back, the synonym was machine learning. But do not worry, this article is not here to provide a new, definitive definition of AI.