These days, in any discussion about enterprise computing, the action is at the front end -- delivering superior user or customer experiences and user interfaces. Artificial intelligence-based technologies are providing developers and IT teams the power they need to deliver, while reducing the repetitive, manual tasks that have characterized UX, CX and UI.
Not only does enhanced automaton help deliver the right information on demand, but also incorporates natural language processing to get smarter about questions being asked, relates Chris McNabb, CEO of Boomi, a Dell Technologies Business. I recently had the opportunity to chat with McNabb, who talked about the urgency of focusing on UX as a key part of enterprise computing initiatives. "You can't increase productivity without ease of use, without being smarter, and getting pervasive intelligence into your user experience," he says.
In today's digital era, the challenge has extended well beyond the data and application integration challenges enterprises have been wrestling with over the past two decades. "It's the engagement side as well that matters, he points out. "How do I engage customers, partners, prospects, and employees in a way that gives them world-class services that can make a difference in my business? Successful transformation lives both in data and in engagement."
AI, in all its forms, is taking on the UX experience for enterprises. "I think AI holds tremendous potential," McNabb says. "AI allows computer systems for instance to read human X-rays at a much higher or more granular read than humans can. That's a great use for AI." .The potential is also seen in re-orienting work within enterprises, "predicting and dynamically creating information for people on the fly, based on knowledge that's in your platform," he continues. "How you align that user experience to make it faster and easier for people to get their jobs done? Not, 'what is this component? What is this object? What is all the software engineering terminology?'"
While there has been a lot of concern about the looming AI skills shortage, McNabb believes the inherent automated nature of AI will help mitigate this. The skills are most needed for creating and training data models, he explains. "It is a complicated deal to train models, you need experts to establish the model, to establish the training method for that model. But it you look at how the training occurs, you don't need a tremendous amount of knowledge and experience to do that." With natural language processing, for instance, "if I just keep feeding it phrases, and keep asking it questions, the model will train itself."
In Boomi's own employment of the technology, "what ends up happening for us in our use of machine learning is that the training does occur by our 9,000 customers," McNabb explains. "Every time somebody asks it a question, and we validate whether the response came back good or bad, and that model gets smarter and smarter and smarter."