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How AI Can Support Humans Get back to the Core of Business

Updated: Sep 11, 2019



Omnichannel strategies involve the quality of product data information as an important value for distributors and brands. 


A quality global product is based on plenty of information such as packaging, labels; warning pictograms, allergens; references, conservation methods; media, and marketing descriptions amongst other categories. 


There could be over 150 different attributes stored in a single product sheet.

Can a human distributor control this amount of information?


Absolutely not! It’s humanly impossible to verify the accuracy and completeness of the product’s information at such a high volume, especially if there are thousands to check. 


This is due to the complexity of the rules and regulations that govern how the tremendous amount of information checked. Also, at the age of omnichannel, checking product information must be done as soon as possible, even in real time. 


Supported by the efficiency of smart data, A.I. can provide consistent suggestions in order to achieve considerable gains in productivity for both distributors and brands.


A.I. technology is increasingly becoming more self-sufficient, but it still remains under human control.


A large amount of data allows machine learning algorithms to be self-sufficient enough to identify patterns. Algorithms are becoming increasingly more accurate and perform much better when they’re fed the correct data. 


However, it would be a mistake to consider AI as the only source of truth. It should be considered and viewed as a means of increasing productivity. 


Machine learning does not decide to apply something without a human’s approbation. That being said, they can make a task achievable when it seems impossible. Humans are still the owners and in charge of the data, but when an AI is fed poor data, it will only yield poor results.


Let’s look at an example between a distributor and a brand.


In the scope of incorrect or incomplete data, a distributor assisted by AI can notify the brand with smart suggestions which are instantaneously relayed. For instance, it could be for data product conformity, smart key words, product descriptions, or even pictures.


The brand would receive this AI assisted message suggesting something be filed or corrected. At the same time, the AI machine learning component suggests information related to consistency.


These accurate AI suggestions save an immense amount of time as humans aren’t able to review such information so quickly. The initial time needed for creating a product file with all the characteristics such as regulations and distributor’s expectations are significantly reduced while data quality is improved.


Attaching too much human interaction is costly, time consuming, and flawed. By saving time, reducing mistakes, and giving smart suggestions, AI can support both brands and distributors in the way they collaborate, but also focus on the core of their business.


aeho


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