Using machine learning in customer support equates to taking your most experienced rep – someone with years of experience responding to customer questions – and making her/him exponentially faster. Taken a step further, machine learning allows you to replicate their expertise and newfound proficiency amongst all of your reps.
There’s a tremendous amount of buzz these days around Artificial Intelligence, and the concepts and techniques associated with it. These concepts and techniques involve sophisticated technology, and their explanations are often confusing to a non-technical audience. But we'd like to help you better understand what an AI search engine is.
Key Terms Related to an AI Search Engine
To make the explanations more accessible to the layperson, we’ve created a list of definitions for a number of key AI terms related to an AI search engine.
What is artificial intelligence (AI)? The concept of AI has been around for so long that most of us have a good high-level understanding of just what artificial intelligence is: it’s the technology that makes it possible for computers to act and react like humans. And most of us also understand that AI is becoming more and more intelligent, and seemingly less and less artificial. Yesterday, it was Amazon suggesting books we might like. Today it’s Alexa answering our trivia questions and turning the thermostat down. Tomorrow it will be driverless Ubers finding the quickest way to get us to wherever we need to go.
Although artificial intelligence (AI) draws a lot of attention in the consumer engagement space, it’s also poised to make a dramatic impact in life sciences. AI for life sciences is becoming particularly relevant due to several trends that are converging and bring new challenges and opportunities for which AI technologies are ideally suited. These trends include precision medicine, improved treatment safety and efficacy evaluations, the increasing complexity of scientific questions, and the explosion of data from wearable and implantable devices.
With customer support & service at the forefront of the brand battle, it's no wonder that companies are turning to artificial intelligence (AI), such as a chatbot, for help. The customer churn caused by poor customer service is $62 billion problem, so finding ways to speed response time is no small matter.
On CMS Wire, David Roe took a look at "10 Ways AI Helps Improve Customer Experiences" based on a report from PointSource. The report found that of more than 1000 people surveyed, 83% said they'd be OK shopping with a brand that uses chatbots or other AI capabilities.
One of the biggest fears with the coming world of artificial intelligence and automation is the loss of jobs. It's a logical fear, as automation often brings with it visions of humans becoming part of the machine itself, or worse: those machines taking over for humans.
Your customers have multiple channels by which they can seek support for issues, problems, and questions. This could be self-service through an online portal, via social media or online chat, or through more traditional means like phone and email. In recent reports, 70% of consumers prefer to resolve problems and issues via self-service; however, 65% of self-service attempts fail. Self-service is the most cost-effective channel, so companies are looking for means to deflect routine and simple issues from the call center by enabling customers to solve their problems on their own.
When we conducted our survey of top AI in the movies, we didn't include HAL 9000. You may think it's an oversight, but really it's that HAL is such an icon that it would be almost unfair for any other AI to compete.
HAL's legacy is more than just as a movie icon, but one that influenced technology, and our reaction to it, since 2001: A Space Odyssey debuted a half-century ago last week.
In tech terms, what we see and hear on-screen is just the user interface. HAL's true function is to monitor and maintain the ship's systems, which means most of what HAL does we just don't see. If the movie were made today, we would consider the bulk of HAL to be happening in the cloud.
You can hear that line in dozens of movies and it's a clear indication that a lead character spends a lot of time at a particular diner. Of course the long-time waitress (and it's almost always a waitress) knows exactly how the main character likes his eggs (and yes, it's often a "him").
What does this have to do with AI? Randi Zuckerberg, president of Zuckerberg Media, recently launched a pop-up experience to help kids better understand science through food. Called Sue's Test Kitchen it had some very interesting experiments, like serving 3D printed pancakes or freezing with liquid nitrogen, but Andrew Brust found a much more interesting take on it: the use of AI to get to know you, the person eating the food.
Did you know employees in 44% of life sciences companies typically need to draw from 7 or more structured data sources to find answers? And when you add unstructured data to the mix, another 38% also have 7 or more unstructured data repositories where they could find possible answers? That's a lot of data silos to look through, and as much as 36% of an employee's day can be spend looking for information.
Unifying Unstructured & Structured Data through Intelligent Search
But AI-powered, cognitiive search can help - by unifying unstructured and structured data, and adding AI-capabilities like machine learning, natural language processing, and text analytics, employees can find the answer they need to virtually any question, right away.
