AI stands for Artificial Intelligence and is generally regarded as a General Purpose Technology (GPT). Other GPTs are the steam engine, electricity and Information and Communication Technology. The impact of a GPT on society as a whole is enormous. Everything and everyone has to deal with it. Now imagine a world without electricity.
Just as with the rise of electricity, computers and the internet, people always first ask themselves: what is it and what can I do with it? This also applies to AI at this time. For many, this is still unknown territory. The awareness has not yet penetrated everywhere that AI has since moved from the research environment to the world of application. You probably already use applications developed by Google, Apple, Amazon, Alibaba, Netflix, Facebook, etc. almost every day. They already use AI in all sorts of ways.
For example, on 1 October 2016, Google translate switched to Deep Learing, a form of AI, overnight. The quality has risen. The first wave of AI applications is in the internet domain. The following tsunami of applications will take place within the walls of the business: Business AI. In particular, the business in Western countries now has a large amount of structured and labeled data available.
This offers enormous opportunities for AI to maximize the value of the data. However, AI does not stand alone. Data is fuel for AI. To fully utilize the opportunities of AI, it is necessary to prepare the organization for the deployment of AI. The ability to deliver data quickly must be in order, knowledge and expertise must be available internally to be able to perform the analyzes and use AI effectively.
Data must be considered and managed as an asset. It is strategically important to integrate the data driven and AI driven aspects into the vision, strategy and culture of the organization. That is no small challenge. For many people, AI is new and unknown territory. This must be overcome by starting with good and practical information. To be able to get more and more added value from data, organizations must further develop themselves (digitally). This results in a change process that benefits from a step by step approach.