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Applying AI in Business, Demystified

How to break down your AI project into comprehensible pieces that make economic sense

Asko Seeba
Towards Data Science
14 min readMar 22, 2020

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Image source: pexels.com

The fields of AI and data science have been going through an extreme hype cycle. The technology carries enormous promise, but all the noisy hype makes it daunting or intimidating to filter out where the value actually is, and, how to make use of the existing AI components that are already easily available and accessible.

While everyone is talking about AI as the next leap forward in business and people’s lives, the natural emotional questions for most business leaders at all levels are the following:

  1. How does my organization make sure we are not missing out on something important that continues to pick up speed?
  2. How can I embrace these new technologies so they bring high-value impact to my company without risking too much money or other valuable resources and energy in the process?

In this post, I am making an attempt to outline a real strategy for success in AI and data science by separating out the emotions of hype. I will attempt to lay this out in a simple to understand research and development process for a successful AI or data science project. It will be based on the hard lessons learned from many projects.

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Towards Data Science
Towards Data Science

Published in Towards Data Science

Your home for data science and AI. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

Asko Seeba
Asko Seeba

Written by Asko Seeba

Machine learning engineer, entrepreneur, nerd. Head of data science, co-founder, Mooncascade.

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