Let us get clarity on this million-dollar question. Today you can’t sell anything without associating with AI. Implementing AI is a mandate that I agree. After all, if we are not taking advantage of the technology, then what is the point in having one? 

AI is nothing, but algorithms have existed for decades (and ongoing basis, a new algos may get invented). The algos are time-tested and proven it is working.

BUT where do businesses fail to recognize the facts and realize them? What is critical here is the DATA. Quality data is needed to train the AI model. The model is trained in two phases, they are forward propagation (initial training) and backward propagation (reinforcement), and on the top bias, which adds more weightage to the preferred outcome. The ‘bias’ plays a significant role in the overall AI outcome. 

You can’t train dog features to the AI model and expect to identify a Tiger. This is where the real challenge for business would come. AI model would expect variety and veracity of data to identify all the edge cases. Unfortunately, most companies have failed to record their past data. Latecomers are still in the process of capturing it, and so lack of quality data leads to failure. Or the one with volumes of data has unstructured and unpredictable data, again a lack of data. Lastly, the amount of interest shown to do initial training (forward propagation) is not given to backward propagation. Businesses complain about the model’s failure but are not concerned about backward propagating and strengthening the model. 

Some of you might think I am mixing machine learning and AI. Machine learning would mature as AI or at least lead to it. So, let us not fight over there rather, help the organizations to get their data right 😉 

#AI #AIAdoption #MachineLearning #BusinessFailure