Science fiction anticipated the power of AI, predictive analytics and "talking" computers. But it typically showed only a small elite (Starfleet officers, hackers, robed mutant priesthoods) getting to use this influential technology. In real life, AI and its data-driven insights can benefit people with all levels of programming expertise – not just data scientists and computational linguists but line-of-business workers such as bankers, engineers, fashion merchandisers and insurance claims processors. OpenText knows that in every industry, AI-powered analytics and text mining can streamline operations and make them more cost-efficient, optimize the customer/citizen experience, and spot new business opportunities. EP6 (or Release 16.6), the biggest upgrade to the OpenText AI & Analytics offerings since Magellan was unveiled in 2017, continues OpenText's progress in analyzing and deriving value from both structured data (figures and labels that fit neatly into spreadsheet cells) and unstructured data (the billions of words of written documents, text chats, emails, social media, scanned images, and other content that wash around us every day).

It's been nearly a decade since Recommind (now OpenText) first pioneered predictive coding for legal document review with OpenText Axcelerate . The advent of supervised machine learning revolutionized eDiscovery with the simplest of principles: if those documents are of interest to you, these probably will be also. Now, all users searching for content across enterprises can benefit from this same principle -- and the same proprietary artificial intelligence technology -- with Predictive Research in OpenText Decisiv 8.2, released in advance of OpenText Enterprise World 2018. Decisiv's unsupervised machine learning provides sophisticated, conceptual analysis of unstructured content to help users find what they're looking for, faster. Decisiv helps legal teams, government workers and business professionals identify useful content, and people with specific expertise, by instantly searching across a wide range of enterprise sources, even when those searching are not sure what terms are likely to yield the best results.

Last Sunday, my husband and I went to visit our daughter. As we drove, my cell informed me that we were 30 minutes from our destination. I hadn't told it where we were going – there wasn't an appointment on my calendar. The cell had worked out this was a trip we regularly take on a Sunday and was able to provide us with useful information based on that knowledge. This is just an everyday example of how quickly Artificial Intelligence (AI) is becoming a normal part of our lives.

In my previous blog, I looked at how quickly Artificial Intelligence (AI) is rapidly becoming a part of the retail experience. Industry analysts agree that 2018 will be the year that AI brings top and bottom line benefits to innovative companies. So, where can AI most help retailers? Here's four questions I think a combination of AI and analytics are perfectly suited to answer. What do you think about being served by a robot?

With all the health tracking gadgets – pedometers, calorimeters, fitness pals – something is changing. Diseases or health problems that were once terminal, have become minor but new have surfaced. Tony Young particularly emphasized the use of technology – information technology in particular – as a driver for transformation and growth in future. With all the data collected, analyzed and then made available back to the users of the gadgets, the healthcare and the insurance industries are undergoing a major transformation today. Insurance – general or life, is no longer the focus of the traditional insurance practices.

With seven billion people on the planet, every one of them making choices and having opinions, it may seem odd to say there aren't enough people to make decisions, and that's why we need help from artificial intelligence. The increasing reach, power, and affordability of digital technology means more and more processes can be automated and theoretically made more efficient, producing more of the goods and services we want. But we don't live in a clockwork world where everything, once wound up, happens according to a plan etched on some master cylinder. In the real world, all these technological "servants" need to respond to a changing environment by learning from context and requesting instructions. They need examples and input so they can answer questions like: Should the store order more toothpaste?

We stand on the verge of a revolution in Life Sciences. Artificial Intelligence (AI) has the power to change everything. It can handle the vast amounts of data being created, continuously learn even as it's exposed to more data and deliver actionable insights for better decision-making. There is little doubt that the next few years are going to bring some incredible developments to the sector. How best do we get there?

Content Management today is more than corralling enterprise data into the right systems--it's about enriching that data and making it more valuable for your company. That's why we're announcing that we are bringing OpenText Decisiv Search to OpenText eDOCS as its default search engine. OpenText Decisiv Search takes the reach and depth of AI-enhanced search even further. It uses unsupervised machine-learning technology to develop a deeper understanding of content, and surface more accurate and comprehensive search results, enabling information to be more rapidly pinpointed, extracted, and leveraged into business advantage. This means that users in legal and professional services firms can spend less time looking for the information they need, and more time doing the work that matters.

During a recent visit to Los Angeles, California, I happened to stay at Residence Inn Marriott at LAX. Unable to sustain my hunger pangs in the middle of the night, I ordered some food. And I had the best, and the most surprising experience!. The food arrived quickly and was not carried by a server, but a robot – Wally! Wally is a 3 feet tall robot that moves on wheels, can be programmed for the room number and delivers to the room.

The pace of technological change today is being called the "fourth industrial revolution." New solutions powered by artificial intelligence (AI), robotics, and machine learning are enabling machines to handle processes that once required human decision-making. Just as mechanical muscle lowered the demand for physical labor in the first industrial revolution, today cutting-edge technology is reducing the demand for human intervention. The "migration" of tasks from humans to software and machines has been evident for quite some time. From ATMs to automated check-in at airports, technology has been performing relatively simple and repetitive tasks.