Leveraging AI and Machine Learning Within Enterprise Infrastructure

Posted on Posted in Tech Talk

AI can be broadly defined as a series of computers carrying out their own, autonomous tasks, and utilizing machine learning to obtain foresight and make better choices towards their tasks.

The majority of early investments in AI were concentrated on optimizing customer discussion workflows. Some increasingly-common examples of AI in practice are its applications towards streamlining order processing flows; another example is using smart robots to recognize a possible topic of a client query, in order to react quickly with the necessary information. In the realm of UC, we are still in the early stages of building AI capabilities into realtime collaborations. But over the last few years there have been numerous joint venture announcements which have served to advance AI services into the area of collaboration.

Optimizing customer support interactions

One possible UC scenario that can be streamlined using AI: Client A receives a telephone or text message from Customer B. The AI engine automatically pulls the the log of their previous written communications, any files that they may have exchanged, and comments from a client relationship management or ERP platform. This empowers the client to get the information that they want at the ready, streamlining the interaction with the customer.

With AI-integrated solutions, it becomes possible for customer service representatives to have important information/documents at the ready to service customers based on previous interactions. Taking it a step further, we can see a future where employees utilize language-based robots - think in the realm of Siri or Amazon Echo - to gather the information they want prior to attending calls or performing specific tasks.

At its Ignite summit in September 2016, Microsoft emphasized the ways it is seeking to utilize its Cortana voice portal to handle inter-personnel communications. Comparable to the Cisco-IBM strategy, Cortana could serve as a digital helper for client engagements, managing scheduled jobs and bringing appropriate data into customer engagements.

It is imperative that IT leaders discuss within their organization and with business software vendors to strategize road maps towards integrating AI into their business practices. While AI services are still being developed in the realm collaboration, executives should anticipate these trends and incorporate them into their road maps. Businesses that leverage AI to enhance internal and external collaboration and communications are going to have a distinct advantage over companies which delay in executing these steps.

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