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When adopting any technology for the first time, the starting point is always the same: Learn the basics. This is especially true for AI, because the technology itself is very new -- at least for the contact center.
While AI has been percolating for decades, recent breakthroughs have just now made artificial intelligence a viable option for business applications. To consider contact-center AI, decision-makers must first understand the relevant use cases and define clear objectives based on the value to the business.
AI is a broad umbrella term for many related technologies, such as machine learning, natural-language processing and cognitive computing. In terms of business applications, most forms of AI pertain to automating tasks or making processes more efficient.
With that in mind, your first move for contact-center AI should identify pain points in the contact center, either for internal operations or customer-facing engagement. Both use cases are well-suited to AI, and a fast-growing ecosystem of developers is working on applications.
Learning about this ecosystem can be overwhelming. If you cannot dedicate the necessary resources, you should engage with a consultant already immersed in the contact-center AI space.
When starting out, you can't look at AI as a broad technology -- it's too vast to apply as a "solution" to your overall contact center. You need to identify specific problems for AI developers to address.
Your first contact-center AI project shouldn't have a hard ROI, as it's so new. The scope should be modest so the project can be tested quickly for proof of concept. That learning curve will be invaluable, because it will give you the background to add more AI -- and that's a track you'll need to be on, as these technologies are set to become mainstream in 2018.
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