AI comes in many different shapes and sizes. That applies to the use cases, the underlying technologies as well as the approaches to adopting AI in your organization. As many organizations are looking to adopt AI, an increasing need for tangible frameworks to understand the technology in a business perspective is requested by leaders in all industries.
Some of the key questions asked by leaders are simple. How much time and money is required to adopt AI and solve business problems via AI and what returns do we get for those efforts? That is more than reasonable questions but answering these questions have been an issue in two parts. Firstly the answers have been a moving target with the technology being in an exponential development and as a result the answers of yesterday seem antique today. Secondly the intangible and explorative nature of AI has made it hard to provide such answers at all.
But as AI has matured as a technology, and been packaged into products and ready-to-use solutions, these questions are ready to be answered. The products and solutions might come in different levels of abstractions but they are nevertheless ready for being applied to business problems without much hassle.
The three main AI approaches
To make it easy to understand the efforts and the outcomes of AI it can be divided into three core approaches; Off-the-shelf-AI, AutoAI and Custom AI. The idea is simple. AI has reached a point where some solutions are ready to use out of the box and others need a lot of work before being applied. All approaches come with their own benefits and drawbacks so the trick is to understand these properties and know when to apply what kind. These core AI adoption strategies provide a more concrete foundation for predicting costs, risks and returns when applying AI.
