Why Better AI Models Don't Always Lead to Better Business Outcomes
Introduction Every few months, a new AI model emerges that can do what the previous generation could not. It can handle longer documents, answer more complex questions, write better code, or process information faster. Technology executives operate under the assumption that better models lead to better business outcomes. It is not always the case. An organization might be equipped with such a highly skilled model but still not manage to extract value from it. And it may not even be about the model itself. It may be related to the fact that data is disperse d among different systems. Th e employees may find it difficult to use the model's output. Some critical business processes may still be carried out using Excel and manual approvals. That is how many enterprise AI implementations fail to deliver results. A Better Model Doesn't Fix a Broken Process Consider a customer service team handling a growing number of requests. The team uses a CRM, a billing ...