David Cearley, vice president and Gartner Fellow, wrote that promises of artificial intelligence (AI) magically performing intellectual tasks that humans do and dynamically learning as much as humans is "speculative at best." However with 2018 rapidly approaching, AI is clearly on the minds of many businesses. Where are businesses practically applying AI in their digital workplaces? In October 2017, Cearley noted at the Gartner 2017 Symposium/ITxpo in Orlando, FL that Narrow AI currently holds the most promise. Narrow AI is composed of "highly scoped machine-learning solutions that target a specific task (such as understanding language or driving a vehicle in a controlled environment) with algorithms chosen that are optimized for that task," he says.

David Cearley, vice president and Gartner Fellow, wrote that promises of artificial intelligence (AI) magically performing intellectual tasks that humans do and dynamically learning as much as humans is "speculative at best." However with 2018 rapidly approaching, AI is clearly on the minds of many businesses. Where are businesses practically applying AI in their digital workplaces? In October 2017, Cearley noted at the Gartner 2017 Symposium/ITxpo in Orlando, FL that Narrow AI currently holds the most promise. Narrow AI is composed of "highly scoped machine-learning solutions that target a specific task (such as understanding language or driving a vehicle in a controlled environment) with algorithms chosen that are optimized for that task," he says.

On February 9, 2017, two technology market leaders made announcements: SAP unveiled its next-generation intelligent ERP system, and Nvidia announced that demand for artificial intelligence (AI) applications was driving demand for its graphics platform. On the face of it, these announcements were business as usual--routine sound bites that proliferate in the tech news landscape. Look a bit deeper, though, and you realize that this day marked a profound shift in both the way businesses use technology and the implications for the rest of us. For decades, developing a computer that could think has been the Holy Grail of technology. And while we have made tremendous progress in our ability to process vast amount of data, the "thinking" part has remained mostly elusive.

Whenever we hire any personal assistant, we look forward to many qualities and skills. We watch the person who is familiar with the business, having analytical skills and also give some suggestion. Could this be possible through a virtual entity? Though the scenario seems unreal. It is going to be reality soon with an application having the functionality of a digital assistant with artificial intelligence.

On February 9, 2017, two technology market leaders made announcements: SAP unveiled its next-generation intelligent ERP system, and Nvidia announced that demand for artificial intelligence (AI) applications was driving demand for its graphics platform. On the face of it, these announcements were business as usual – routine sound bites that proliferate in the tech news landscape. Look a bit deeper, though, and you realize that this day marked a profound shift in both the way businesses use technology and the implications for the rest of us. For decades, developing a computer that could think has been the Holy Grail of technology. And while we have made tremendous progress in our ability to process vast amount of data, the "thinking" part has remained mostly elusive.

On February 9, 2017, two technology market leaders made announcements: SAP unveiled its next-generation intelligent ERP system, and Nvidia announced that demand for artificial intelligence (AI) applications was driving demand for its graphics platform. On the face of it, these announcements were business as usual – routine sound bites that proliferate in the tech news landscape. Look a bit deeper, though, and you realize that this day marked a profound shift in both the way businesses use technology and the implications for the rest of us. For decades, developing a computer that could think has been the Holy Grail of technology. And while we have made tremendous progress in our ability to process vast amount of data, the "thinking" part has remained mostly elusive. We are still stuck between two diametrically opposed visions of AI – on one side, it's the smart but deeply dystopian world of HAL ("2001: A Space Odyssey") and on the other, it's a simpler world of devices like Alexa or Siri playing songs or ordering items for us.

"If you don't innovate fast, disrupt your industry, disrupt yourself, you will be left behind." To orchestrate this transformation, organizations must revamp their IT strategies and roadmaps and ingest the value of artificial intelligence and enterprise resource planning (ERP) integration. These technologies go hand in hand because they cover the same spectrum. AI-enabled ERP solutions will by default impact the heart and soul of day-to-day operations. The mix of people, process and technology is going to change.

"If you don't innovate fast, disrupt your industry, disrupt yourself, you will be left behind." To orchestrate this transformation, organizations must revamp their IT strategies and roadmaps and ingest the value of artificial intelligence and enterprise resource planning (ERP) integration. These technologies go hand in hand because they cover the same spectrum. AI-enabled ERP solutions will by default impact the heart and soul of day-to-day operations. The mix of people, process and technology is going to change.

Talking to a smartphone as if it were a person may seem strange at first, but chances are you will be getting the weather report, ordering a new laptop or requesting a day off with a chat bot pretty soon… if you aren't doing so already. And this is just the beginning. Using natural language – whether via voice or text – is so powerful because it is so human. People want to talk like humans, not in a limited set of staccato commands that are easy for machines to understand but require us to learn and just plain feel ridiculous. Although the richness of human speech, with its jargons, dialects, and turns of phrase, has taken computer engineers time to master, the technology has evolved rapidly.