Many organizations think AI is a'plug and play' technology that will deliver immediate returns to the business right from deployment. In reality, it all depends on which type of AI your business is using, and the type of challenge you're looking to overcome by implementing it. Take machine learning as an example. While companies may initially decide to adopt the technology to help identify patterns in their data and solve pressing business problems, this doesn't happen overnight. IT management teams will have their work cut out before the business ever begins to see value.

The topic of machine learning (ML) and artificial intelligence (AI) gets more sensitive as we delve further into the second decade of the third millennium. With each study, announcement, and discovery, we dig deeper into the matter, having more and more trouble when it comes to differentiating hype and reality. Perhaps the hype is something that we may call human nature as an extension of our everlasting yearning for the next big technological advancement. First, we discovered fire, and then we discovered how to manipulate fire. Later came the industrial and the digital revolution.

The topic of machine learning (ML) and artificial intelligence (AI) gets more sensitive as we delve further into the second decade of the third millennium. With each study, announcement, and discovery, we dig deeper into the matter, having more and more trouble when it comes to differentiating hype and reality. Perhaps the hype is something that we may call human nature as an extension of our everlasting yearning for the next big technological advancement. First, we discovered fire, and then we discovered how to manipulate fire. Later came the industrial and the digital revolution.

Do you use it at all to help you do your work? I reviewed the new Pixel phone. But I get along fine with my older Android phone. The irony is that I am a techno-skeptic. At least in my own head, this makes good sense. I don't cover a consumer technology company.

Conversations on Artificial Intelligence (AI) range from the extremely progressive views on the possibilities it offers to the other side of the spectrum where the chatter is all humdrum and the fear of losing jobs to machines overtakes everything else. Well, the fact is, both perspectives are right and matter equally. Like with every new technology, changes due to advances in AI are difficult to comprehend in entirety since there are more unknowns than knowns. I am of the firm belief that we are barely scratching the surface with AI and significantly far from reaching the singularity. Hence, the need of the hour is to not fear AI and instead focus on understanding its relevance for our organizations and the human race at large.

Manufacturers face a difficult task juggling the current "innovation agenda." Today, the Industrial Internet of Things (IIoT), robotic automation and artificial intelligence (AI) are all poised to be the next big thing. But those on front line of manufacturing are cautious to embrace innovation--and rightly so. Too often expectations are unfulfilled, capital investments are made in vain, and experimentation doesn't translate positively into profits. Instead, many enterprises take a wait-and-see approach.

You probably won't get to the end of this article. Everyone knows our attention spans are getting shorter. In the always-connected world of social media, smartphones and hyperlinks in the middle of everything you read, it has become that much harder to stay focused. And there are statistics too. They say that the average attention span is down from 12 seconds in the year 2000 to eight seconds now.

Word has spread that artificial intelligence (AI) is the next big thing in business. But don't be fooled; in reality, it's so much more than that. Take a look at how it's set to overhaul your organisation.