Written by Arttu Huhtiniemi, Senior Data Strategist at DAIN Studios.

Digital, Data and AI Strategies

Digitalization of products and services surrounding us begun in the mid-1990’s when computing started to become more affordable and financially sensible for more use cases. In the early days the transformation was slow but started to pick up first in the information heavy industries such as media, telecommunication and consumer finance. Fast forward to the current century and we find us surrounded by digital services that are continuously evolving and usually creating value both for the supplier and consumer.

When digitalization started to happen in scale, the term Digital Transformation emerged and a Digital Tranformation Strategy was demanded by the boards of many organizations. The purpose of the Digital Transformation Strategy is to define how the enterprise readjusts themselves to operate in the new digital operating environment.

Data

Digitalization of customer touchpoints have created an ability to record and collect accurate data on customer interaction with products, services and customer touchpoints. At the same time the cost of communication, data storage and computing infrastructure have become less costly, which has created a possibility to store all consumer interaction data into permanent storage.

In manufacturing, logistics and other industries with no direct consumer interaction, operational data has become easily available with the help of wireless sensory technology that can sense everything that happens in the operation and forward the data into permanent storage.

Similarly as with the Digital wave, the new data management capabilities have created new opportunities for corporations, which require new approach in how to store data. Formulating that approach into a Data Strategy, defines how an organization improves existing and creates new business from the data available from the different sources.

Artificial Intelligence

The third big technology shift in the last three centuries is the emergence of Artificial Intelligence (AI) from the university research chambers to the board rooms around the world. Again, behind this phenomenon is technology development that has made computing power and algorithms more easily available to organizations cost effectively and with high quality through cloud platforms.

Today we are seeing more and more organizations developing AI strategies that will address the issues and opportunities that come with this next shift in computing technology.

Learning to fly

While the use cases powered by AI are certainly exciting to many, the need to approach it systematically is essential in order to lower the risk of failures and managing expectations. While the AI algorithms available today are highly advanced and well tested, teaching the algorithms require vast amount of data, which is only available if the organization is systematically storing data, and the correct data is only available if the right digital touchpoints have been enabled.

In order to fly and keep yourself safely in the sky, you need to make sure you first have your Digital strategy in place so you can collect data and you need your Data strategy to know where and how to store the data. After that becomes the moment for an AI strategy that guides the organization in how to and where to apply AI.