Slicing Artificial Intelligence — Introduction
In one of the last articles we defined A.I. as
a non-natural, adaptable system that has the ability to solve problems, or to create products, that are valued within one or more cultural settings
So A.I. systems solve problems or creates products by learning. This learning is triggered by new data being fed into the system. But Gartner also added that the problems the intelligence solves or that the products the intelligence creates need to be valued within a cultural setting. This addition to mostly found A.I. definitions adds the component of value. What does that mean for using A.I. systems within our businesses?
For our businesses it means that they generally create “value” for the company. Value for a company, however, can have three characteristics or forms:
- It can be valuable for the customer (e.g. better service). This is also known as Voice of Customer (VOC).
- It can be valuable for the employee (support of their work). This is also known as Voice of Employee (VOE).
- It can be valuable for the business itself (support of strategy, increase of revenue, decrease of costs). This is known as Voice of Business (VOB).
In summary, A.I. systems have to increase either the VOC, VOE or VOB. If they are not, they are not considered A.I. systems. This extended definition of A.I. puts well-meant pressure on us to firstly define a true business case before we start A.I. projects.
Now that we have talked about the definition of A.I., we want to look at the three big value-adding groups of A.I. systems within a business setting. This will give you good framework to work with while trying to approach the topic of A.I.
- Group 1: Machine learning
- Group 2: Natural language processing (NLP)
- Group 3: Robotics
The first group is something you might have heard about. And many people use it sometimes synonymously with A.I. The second group deals with translating and understanding spoken or written human language. The last group contains the world of robotics and what advances A.I. has done to this field within the last decade.
Tomorrow we will start looking at machine learning.
—
If you are interested in A.I. leadership education or want to start your A.I. journey, just contact me at ansgar_linkedin@goldblum-consulting.com
