For many consumers, the concept of "customer service" is frustrating to the point of humor. Even with the many advancements in digital technology today, consumers still experience lackluster resolution to often simple problems. They find themselves upset because whenever they have an issue, the in-person employee doesn't know how to help them or they "never get to talk to a real person" when automated responses do not answer their question. Customer service shouldn't be this way! The solution is an Anticipatory mindset that starts with a foundational understanding that exponential digital change will only increase, and consumers' wants and needs will transform as well.

Daniel Burrus is considered one of the World's Leading Futurists on Global Trends and Disruptive Innovation. The New York Times has referred to him as one of the top three business gurus in the highest demand as a speaker.

While reviewing documents is just one of several parts of the job of a lawyer, this data further proves the Hard Trend that I implore everyone to pay attention to in the years to come. Artificial intelligence is here to stay, and by using machine learning and deep learning techniques, new A.I. systems are learning how to think better and better every day. So the question remains: Are you anticipating how A.I. can be used to automate tasks and do things that might seem impossible today -- in other words, disrupt your industry? Are you starting to learn more about A.I. so that you can become a positive disruptor rather than become the disrupted?

One of the biggest news subjects in the past few years has been artificial intelligence. We have read about how Google's DeepMind beat the world's best player at Go, which is thought of as the most complex game humans have created; witnessed how IBM's Watson beat humans in a debate; and taken part in a wide-ranging discussion of how A.I. applications will replace most of today's human jobs in the years ahead. Way back in 1983, I identified A.I. as one of 20 exponential technologies that would increasingly drive economic growth for decades to come. Early rule-based A.I. applications were used by financial institutions for loan applications, but once the exponential growth of processing power reached an A.I. tipping point, and we all started using the Internet and social media, A.I. had enough power and data (the fuel of A.I.) to enable smartphones, chatbots, autonomous vehicles and far more. As I advise the leadership of many leading companies, governments and institutions around the world, I have found we all have different definitions of and understandings about A.I., machine learning and other related topics. If we don't have common definitions for and understanding of what we are talking about, it's likely we will create an increasing number of problems going forward.

One of the biggest news subjects in the past few years has been artificial intelligence. We have read about how Google's DeepMind beat the world's best player at Go, which is thought of as the most complex game humans have created; witnessed how IBM's Watson beat humans in a debate; and taken part in a wide-ranging discussion of how A.I. applications will replace most of today's human jobs in the years ahead. Way back in 1983, I identified A.I. as one of 20 exponential technologies that would increasingly drive economic growth for decades to come. Early rule-based A.I. applications were used by financial institutions for loan applications, but once the exponential growth of processing power reached an A.I. tipping point, and we all started using the Internet and social media, A.I. had enough power and data (the fuel of A.I.) to enable smartphones, chatbots, autonomous vehicles and far more. As I advise the leadership of many leading companies, governments and institutions around the world, I have found we all have different definitions of and understandings about A.I., machine learning and other related topics.

Business people, not to mention the public on a global basis, are getting increasingly excited, as well as concerned, about the potential of artificial intelligence (A.I.)--so much so that China's growing involvement in A.I., and the vast quantity of data that China is capable of generating on a daily basis, has many wondering if the U.S. will be a leader or follower in this important technology category as the future unfolds. Data is the fuel that feeds A.I. The more data you have, the more A.I. can learn and adapt. Most feel it's all about the quantity of data. I have been sharing both in my international speeches and consulting that data quantity is good but not if the quality is bad, and this concern should be forthright for anyone involved in A.I.

Business people, not to mention the public on a global basis, are getting increasingly excited, as well as concerned, about the potential of artificial intelligence (A.I.)--so much so that China's growing involvement in A.I., and the vast quantity of data that China is capable of generating on a daily basis, has many wondering if the U.S. will be a leader or follower in this important technology category as the future unfolds. Data is the fuel that feeds A.I. The more data you have, the more A.I. can learn and adapt. Most feel it's all about the quantity of data. I have been sharing both in my international speeches and consulting that data quantity is good but not if the quality is bad, and this concern should be forthright for anyone involved in A.I.

For many of us, our experience with artificial intelligence (AI) may be, for lack of a better way to put it, "helpfully cool." That can mean asking Amazon's Alexa to play a particular song or querying Google's Home to see if butter is a suitable replacement for vegetable shortening. But the potential for AI goes far beyond cool. Its application in businesses and industries of all sorts will exponentially revolutionize how we both think and work. And that sort of change is coming faster than you might expect.

The single most disruptive influence on business, as well as society, will be artificial intelligence (A.I.), which includes technology such as machine learning and cognitive computing to name just two. In other words, there is more than one type of A.I. and each represents a new way of doing both big things as well as everyday things in amazing ways. When I say big things, I mean solving highly complex problems such as enabling the development of highly personalized drugs and genetic therapies designed for your genetic makeup. A.I. will keep you from having an accident, whether you are driving your car or not, by knowing the surroundings in real time, predicting a problem, and helping you avoid the accident. Eighty-five percent of traffic accidents are caused by blind spots, and soon your car won't let you have that accident.

Users are looking for more than the humble SMS text message to communicate with friends and family. Our communication requirements now demand group messaging capabilities with the ability to seamlessly share an image or video on the move. Apple's iMessage, WhatsApp and Facebook's Messenger are leading the way, but the recent release of Google Allo suggests that messaging has become the new tech battleground. Our love affair with mobile apps is changing because we have so many, often over 50, yet on average we only actually use five of them on a regular basis. Searching for an app that is hidden in a folder of apps on page 3 of our phones is no longer deemed productive in an age of instant gratification.