As artificial intelligence (AI ) and machine learning (ML) solutions and technologies continue to evolve, more and more businesses are looking for ways to incorporate them into their operations to realize a greater business impact. But with so many potential applications, it can be difficult to know where to start. In this blog post, we’ll outline some tips for identifying AI / ML use cases. We’ll also provide a few examples of how AI & machine learning can be used in business settings. So if you’re thinking about adding AI or machine learning to your toolkit, read on! This blog post will be appropriate for product managers, business analysts, data science architects, data scientists, etc.
The following are some of the challenges you may face when trying to identify AI and machine learning use cases for your business:
When human thought process / intelligence becomes limited to take decisions based on several parameters, artificial intelligence comes to the rescue.
The following is a diagrammatic representation of different steps that can be taken to identify or arrive at the most appropriate analytics solutions including AI/machine learning use cases:
One of the biggest challenges in adopting AI is identifying potential use cases. In this blog post, we’ve outlined a process for how you can identify and validate AI/machine learning hypotheses. By following these steps, you’ll be able to establish the truth for certain business processes and adopt them into your organization’s workflow. Let us know if you have any questions about how to apply these principles in your own business!
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