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How to choose the right pattern to infuse AI into your business

Updated: Feb 13, 2020

Organizations are looking to AI models to bring out digital change in business. However, understanding which sort of models are generally fit to the business needs is crucial.

As enterprises are discovering the benefits of artificial intelligence (AI), they realize the journey to AI is long and bumpy. Many CIOs (chief information officers) want AI to quickly transform their business without identifying which processes will perform better with AI.



In an ideal world, one can pick any procedure, infuse it with AI and afterward find the advantages & disadvantages during the journey. The most ideal approach to learn is on ventures instead of investigating through theoretical case studies.

But there needs to be some order to the madness. Can we generalize some patterns that could make it easy for business owners to apply AI? Let’s discuss some scalable, enterprise-relevant AI patterns.

Discover new processes: This is about finding new opportunities afforded by AI. Consider the example of a defect in a machine, degrading over time. An experienced AI engineer can deduct the condition of the machine from the sound generated.

Reinvigorate old processes: This pattern improves existing processes by introducing AI. For instance, almost every organization collects data from the employees’ badges, which provides information on access control and employee movement. Reinvigorating this process by adding occupancy sensors and then adding AI will help derive deeper insights such as the number of people per floor.

Unlock data: Organisations can derive value from their data by applying AI. For example, machine learning algorithms can be used to detect fraud in financial transactions or even an asset defect, which would otherwise go unnoticed by humans.

Opening new channels: This is another area where we have seen several businesses apply AI successfully. This essentially means starting a new channel of interaction with customers or employees using AI-based virtual assistants with natural language processing technologies.

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