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How to address the challenges of adopting AI in communications

How to address the challenges of adopting AI in communications

Today, is the Wild West of IT projects. It started with business intelligence, where data was collected across the enterprise and shipped into a big database.

SwissCognitiveToday, is the Wild West of IT projects. It started with business intelligence, where data was collected across the enterprise and shipped into a big database. Reports and dashboards were then built on top to help shape our daily decisions.

About a decade ago, the language shifted toward big data and analytics. More recently, the tune has changed to and . Marketers took it a step further by calling it .

Currently, enterprise adoption of includes looking at operational data hiding in every nook and cranny of the enterprise and making that data actionable. Organizations are now focused less on the technology and more on business outcomes and what can be derived from placing learning algorithms on top of the data we have.

People have also become skilled at computer vision and analytics to create best practices on converting to text and text to , as well as identifying objects and actions in images. These advancements, coupled with the idea that in business processes creates market advantages, have pushed companies toward .

When a colleague and I researched the use of in real-time communications , we interviewed companies working with — from -first startups to large enterprises that needed to start initiatives. The survey uncovered some challenges that organizations face when adopting and in communications.

1. Finding the right talent

One of the main challenges for adoption is finding talent conversant enough in . The talent pool is relatively small , and large cloud vendors, like Amazon, Google and Facebook, are attracting developers and data scientists with high salaries, bonuses and highly rewarding work.

Enterprises can attract talent in one of three ways:

  1. Open offices in smaller technology hubs around the globe. The further away from San Francisco you go, the less of a fight over talent you will face.
  2. Compete in the market by offering higher salaries and benefits to lure experienced developers.
  3. Train the existing workforce. One organization we interviewed said all developers were given the opportunity to take online courses, which led to 10% of their developers becoming more familiar with .

2. Making business sense

Adding to a healthcare use case is different from adding to a social network interaction. While both these examples may use similar algorithms and techniques, you’ll need some domain expertise in the market itself.

In contact centers, for example, the dynamics of a sales conversation are quite different than a partnership discussion. In these instances, could gauge who speaks when and for how long. Knowing these differences and nuances of the business is just as important as knowing statistics and .[…]

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