The revolution of AI and the subsequent AI economy continue to leave their mark in the world of business serving as an indispensable part of most major enterprises. However, questions are being raised as to the actual value of AI’s impact on efficiency. The idea is that far from actually being an efficient part of the enterprise there is in reality little proven value. This is why enterprises are being advised to think more strategically about how to best make use of AI applications. It is also why AI must be taken into consideration when it comes to creating profitable business plans, even more so in the future. Originating from the 80's when AI mostly consisted of hard coding human intelligence, it evolved into useful applications. However, after the AI winter that succeeded in this development, a new way of using AI emerged. Now, instead of incorporating human knowledge into technology systems, machine learning uses data from the real world in order to train computers to predict outcomes and detect patterns. In short, the most apparent difference between AI of the past and that of the future, is that back in the days, predictions in business did not rely on AI as it does in contemporary settings. Business cases such as Amazon or Google is evident of this as suggests.

Efficient or not, that is the question

There is a general idea that if you want to run a successful and efficient enterprise it is vital to have AI as a part of your business strategy. This is not true. Of course it is beneficial to have AI applications but they need to be customized to your business in order to generate efficiency and the truth is that there is still little evidence of any clear business ROI. Often the AI applications in place are mere pilots and it is difficult to yet determined their value and in worst case scenarios they have been implemented for the wrong reasons, i.e. implementing AI applications for the simple reason of having AI applications. As most of the issues with adopting AI solutions are structural, it becomes apparent if there is no evident use for the technology once an attempt is made to incorporate it. It is also important to have members within the organisational structure that are able to handle working with the applications. However, despite the challenges mentioned, there are many useful areas as well. Business functions such as for instance cyber security and customer service as well as specific industries such as finance will benefit the most from using AI applications.

Structure is key

Will then implementing AI applications into your enterprise structure mean more or less efficiency? Well, the answer to such a complex question is actually rather straight forward. It all comes down to determining if there is enough structural balance to handle it and also if there is an actual need for the application. The truth is, speaking from an efficiency point of view, most companies are simply not there yet.