Everything invented in the past 150 years will be reinvented using AI within the next 15 years. Artificial intelligence is a term often reserved for the likes of Skynet in the "Terminator" films or ENCOM's mainframe in the 'Tron' movie, Artificial intelligence (AI) and a world in which machines threaten humanity's status quo has been the preserve of science fiction and movies for decades.

The reality is the bot has bolted. AI is walking and talking among us. In 2016, we use voice-recognition systems like Siri, driverless cars are being trialed and robotic hotel receptionists' work in Japan. The advent of certain technologies, inexpensive high-speed Internet, secure cloud storage, mobility solutions and low-cost devices has allowed the fantastical possibilities of the past to become reality. Instead, they see AI as an indispensable tool for supporting humans in virtually every aspect of life, especially in commercial applications.

AI and Business Today
Rather than serving as a replacement for human knowledge and ingenuity,AI is generally seen as a support tool for the humans using the technology. Although AI currently has a difficult time completing common sense tasks in the real world, it is adept at processing and analyzing troves of data far more quickly than a human brain could. AI can then return with a number of synthesized courses of action and present them to the human user. In this way, humans can use AI to help game out possible consequences of each action and streamline the decision making process.

It allows shoe shoppers to whittle down a catalogue into personal choices with a few swipes, factoring in subtle details such as slope of toe, height of heel and shape of sole. A restaurant could use AI, for example, to decide which music to play based on the interests of the guests in attendance. AI could even alter the appearance of the wallpaper design based on what the technology anticipates the aesthetic preferences of the crowd might be.

Some Applications of AI in the Future Could Be:
Virtual Assistance
The first and most obvious way to use artificial intelligence is for virtual assistance. Many have already had the experience of speaking into a phone to search for answers to basic questions, like who invented Electricity or a sum of two numbers or directions to the nearest Petrol Pump. It's become so commonplace that we rarely stop to think that it would have seemed like science fiction a decade ago.

Generating Insights
Data has been called the new oil because it is essentially the raw material of the digital economy. What used to be trapped in a vast maze of incompatible database and protocols or worse, filing cabinets is now quickly becoming a fungible commodity that can be accessed by new technology platforms like Hadoop and Spark.

Yet much like oil, data is largely useless without effective machinery to transform it into something of value. That's the role that machine learning is starting to play. Today's systems can not only take in billions billions of data points and analyze them in minutes, they can also learn from the data and get better over time.

Automation of Manual Processes
One of the constants throughout the rise of technology is the automation of work. First, came labor saving machines such as tractors and home appliances and later industrial robots and basic systems to automate things like travel reservations arrived. Today, more advanced robots are even able to work alongside humans in factories.

Unlocking Unstructured Data
Traditionally, almost all of the data we analyzed was structured data, the kind that gets captured and stored in a database. So we were reasonably good at deriving insights from data generated for that purpose, like sales from a cash register or answers to a consumer survey, but most everything else got lost. That's a bigger problem than most realize, because structured data represents only a small part of the information available to us. In fact, it has been estimated that 80 percent of digital data is unstructured.

Finally, what makes artificial intelligence systems so powerful is that, unlike purely statistical approaches, they can learn. That allows them to adapt when market behavior changes as well as continually improve performance as more data comes in. We are entering a new era of cognitive collaboration in which machines become far more than just agents to perform tasks, but help us to understand the world and make better decisions.