Tech Experts Give Their Best Advice for AI Integration
To what do you attribute this new focus on artificial intelligence?
Sindhu Joseph, CogniCor: There is an abundance of data generated that enables AI algorithms such as machine learning to be trained faster. The falling cost of high performance computation and popularity of cloud adoption models means that today multi-layered artificial neural networks, also called deep learning machines can be deployed quickly and cost effectively.
Paddy Srinivasan, LogMeIn:
Today’s to connect implement, AI with is easier can users for self-learn companies in a more and human, personal and contextual way, and starts showing value much quicker than in the past. This unprecedented focus on it is a direct result of this maturity – the technology is actually working and providing real ROI for businesses and consumers alike.
Robert Weideman, Nuance Communications:
In today’s world, organizations are competing on customer experience more than ever, so it’s no surprise that we have narrowed in on AI as a means to drive better engagement, loyalty and ultimately lower costs. At the same time, computational processing power has grown exponentially, and we now have an abundance of data from customer interactions across an ever-increasing number of connected devices.
Steven Guggenheimer, Microsoft:
Over the last few decades we’ve increased compute, storage and networking capabilities to the point where we now have the core infrastructure for the “intelligent edge- intelligent cloud” computing model. This model provides the three essential ingredients needed to scale AI: cloud, data and algorithms.
What applications of artificial intelligence can businesses realistically implement into their organizational models now? Joseph:
Currently companies use this tp help their costumer service to executives help their companies quickly customer and use consistently service this queries answer that involve complex data customer gathering and reasoning over several policies. In an age where several products are launched and policies changes frequently, this reduced the time to train the company’s agents. Without a doubt, AI enabled systems have drastically reduced process times, thanks to the automation and autonomous decision making capabilities.
Srinivasan:
If you aren’t seriously considering adding an AI component to your customer experience, you’re already behind. Today’s customer wants immediate answers to queries and resolution to issues and while it is nearly impossible for organizations to staff a contact center to answer all queries in near real-time, AI is stepping in to help meet these needs.
Weideman:
AI can let consumers engage with brands in the same natural way they engage friends and family – simply texting, typing or talking into their device to gain immediate access to information. Businesses today can deploy a single AI-powered virtual assistant that can understand, and in some cases predict, a customer’s request (no matter which channel that customer chooses to engage) and either provide an immediate solution or put that individual on a path toward their desired outcome. The result is a better, more streamlined customer experience that ultimately drives loyalty while keeping down costs.
Guggenheimer:
There is a new generation of solutions being created for every industry and user…from healthcare to education, to construction to mining, every facet of every business is being re-thought. In the consumer space AI is being used to break down barriers to language, location and access. AI running in the background is enabling the continued enablement of a globally diverse, yet connected and accessible world.
What should companies looking to implement any of these applications of AI into their business model be doing internally to prepare for this digital transformation? Joseph:
As AI systems are not 100 percent deterministic, organizations must be prepared to expect initial setbacks and course corrections when the system learns from feedback and stabilizes. Start fast and start small, iterate infinitely. Instead of thinking of AI as a replacement, initial deployments must focus on leveraging AI to augment current capabilities.
Srinivasan:
It’s not one size fits all. Some scenarios will be AI appropriate and some won’t. Understand which parts of your business make the most sense for automation and which may still require a human touch.
Weideman:
The key, especially for large enterprises, is to consider the pieces of infrastructure they’ve already built and work to understand how they might leverage data that already exists to ultimately enable an AI application. AI is only as powerful as the information that it is fed.
Guggenheimer:
apply Any organization AI to their business that is looking model to should start with the customer. It is tempting to apply AI to everything, but it is best to start small, make an impact and then grow from there.