Facilitating the adoption of Artificial Intelligence and Machine Learning
We are in a digital age increasingly led by data-driven companies. In the image below, you can see how the ranking of the largest companies by market capitalization has changed in the last three decades (source: Platform Patterns—Using Proven Principles to Develop Digital Platforms).
What currently characterizes the largest companies in the world, and also most of new entrants, is the intensive use they make of user data. They take advantage of the value that these data provide through techniques such as Artificial Intelligence (AI) or Machine Learning (ML).
No sector is safe from new entrants, who are 100% focused on creating value through technology and the optimal use of data, whether to make better decisions, to improve operating processes or to create much more customized products and services. And we have to be prepared to compete with them.
Faced with this situation, business leaders and CIOs wonder how they can turn their data into business value, and how they can transform their company into a data-driven one.
This is what we will try to solve in this series of articles, based on our own experience, in which we will address the following topics:
- The data challenge for Artificial Intelligence
- 4 types of data to apply Artificial Intelligence
- What team will you need for your Artificial Intelligence project
- The challenges of applying Artificial Intelligence