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Sorry guys, Ai does not stand for Adobe Illustrator. Even if we love this product today we are looking into A.I., Artificial Intelligence (AI). Time comes where SkyNet and Co are getting reality, more and more companies are investing into AI, read how you can tackle the topic for yourself and when it makes sense to invest into it. 

Digital Marketing is not anymore like traditional marketing. In the era of digital transformation happening everywhere, marketers want a proof of their investment.

Dieter Hovorka

CTO, Co-founder, Skillz Middle East

The use of artificial intelligence applications in all fields including business is growing, but AI and machine-learning aren’t yet there for every business task, according to an infographic by Lantent View.

The big blue-chip companies like Microsoft, Adobe and IBM, for example, are investing more and more into this emerging technologies.

Published by LatentView, a marketing automation and digital analytics platform, the infographic details what criteria make a task a good candidate for AI, and goes on to explain how to use AI in your business.

Just one example, in marketing, decisions about personalized offers to customers may work well with AI, but decisions about marketing strategy are best left to the humans (at this point, anyway), as we learned.

Find repetetive tasks which can be automated and increase the quality of delivering the tasks an an automated decison making process. 

A valid question stays and asked by many. How do we get started? Well, the Infographics highlights a checklist what we shall do to get into the topic. To implement AI proper we shall look into, low patterns, volume, low cost of mistake and if something is repetitive.  

In customer service, AI can learn to improve responses based on historical chat data, but decisions that are based on empathy still require human intervention.

See the infographic below and learn more about when AI can and should be used in business:

Is Artificial Intelligence Right for Your Business? Implementing AI and Machine Learning
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