Artificial intelligence (AI) is rapidly moving from "nice to have" into "must have" territory for organizations. In fact, nearly six in ten AI early adopters think it will be a necessary element to remain competitive within the next few years. Two-thirds say AI is very important to their organization's strategy and success. AI can be a powerful tool for getting people the right information at the right time for decision making. By augmenting human intelligence and improving planning, AI has the potential to transform workplace productivity.

A Japanese insurance company has decided to get rid of 34 jobs and instead get artificial intelligence to take over assessing medical insurance claims over the phone. Starting from January 2017, Tokyo-based Fukoku Life Insurance Mutual Company is handing over the roles of 34 human insurance agents to IBM Watson Explorer, which is a cognitive search and content analysis platform that uses machine learning and language processing to analyse data for trends and patterns. According to a press release, Fukoku Life is using IBM Watson Explorer to classify and categorise diseases, injuries and surgical procedures. When insurance policy holders call the company's hotline to make an insurance claim, the IBM Watson supercomputer is able to analyse the customer's voice and detect keywords. As part of making the claim, the policyholder has to submit a medical certificate showing what condition they have, and IBM Watson can detect the name of the injury or disease listed, as well as dates such as the hospital admission date and surgery date.

LONDON, UK, 3 January 2017 – Digital Catapult is proud to announce that it is the advocate UK partner involved in the IBM Watson AI XPRIZE, a $5m competition challenging teams to demonstrate how humans can collaborate with AI to tackle the world's grand challenges, such as poverty, health and sustainable energy. As part of its wider strategy to support market-led technology and innovation, Digital Catapult will support IBM Watson AI XPRIZE via its technical experts as resources and mentors for competing teams. Digital Catapult will also form a hub for UK teams by hosting events, meet-ups and take a lead in helping to showcase the best competitors to come out of the UK. XPRIZE offers competitors a rare chance to work on applications using AI, machine learning, predictive technologies, robotics and other advanced technologies to develop powerful cognitive applications. Teams have the freedom to define their own goals and have the unique opportunity to potentially attract investment and compete for the main prize in the final at TED 2020.

IBM on Wednesday announced it was teaming with General Motors to put Watson artificial intelligence to work to personalize the driving experience for motorists. OnStar software built into GM cars will be imbued with Watson smarts, enabling them to get to know their drivers, IBM chief executive Ginni Rometty told the WSJD Live technology conference in California. "It learns from how you behave and what you do," Rometty said. "It knows how you like your coffee and orders it for you; it reminds you to pick up your children." The resulting OnStar Go system will be the auto industry's first "cognitive mobility platform," according to the companies.

It has been less than two weeks since a White House report warned that automation has the potential to disrupt millions of jobs, and this week a Japanese insurance firm proved how close that future might be. According to Japanese news publication Mainichi Shinbun (via Quartz), Fukoku Mutual Life Insurance Co. will be replacing roughly 30 percent of the employees in its payment assessment department with an artificial intelligence system powered by IBM Watson. Fukoku Mutual plans to lay off 34 employees by the end of March, and the company will not renew contracts for an additional 13 employees once they expire. The new AI will determine how much insurance should be paid out for each claim based on a number of factors, including the insured's medical history, the procedures they have undergone, the doctor's diagnosis and so on. According to Mainichi Shinbun, the types of cases the AI would handled totaled around 132,000 in 2015.

Snapchat debuted its camera-equipped Spectacles this fall. Snapchat is adding ways to optimize campaign performance with the help of machine learning. Earlier this month, Snap Inc. began rolling out what it calls Goal-Based Bidding (GBB). The option, available to marketers buying ads through Snapchat's API, uses machine learning to know which users are most likely to swipe a certain type of ad. Here's how it works: With goal-based bidding, advertisers can inform Snapchat of when their main goal is increasing swipe-ups--perhaps for app installs, web views or movie trailers--instead of focusing solely on impressions.

The age of artificial intelligence (AI) is upon us. In the past few years, vast improvements have been made in how well computers can recognise objects in images and understand human voices. Progress in these areas has been made due to increased computing power and the availability of large stores of data, which, when combined, have made AI systems dramatically more effective. These same forces are also being used in marketing. AI, or'cognitive', marketing systems use industrial computing power, big data, and machine learning to improve marketing performance.

As someone who will become a future Software Engineer (Embedded / Cyber Security / AI most likely), my concern is this: lets say we increase the wages of undesirable jobs so as to compensate, then how do we handle other types of jobs? Certainly, one could argue my profession will have more'relevance' in this robotically automated world, so from my stand point it would seem unfair that wages increase for, say, the grass-cutter or dishwasher, while my job stays where its at. I suppose one could argue that "all jobs are equally important" but this simply isn't how our world works. Engineers make more money than teachers because we build the things that private / government entities need, and teachers make more money than grass-cutters because the future generations need to learn. The follow-up concern with this is that we're right back where we started in a sense: we have a hierarchical system of what is and is not important.

Agriculture is the industry that accompanied the evolution of humanity from pre-historic times to modern days and fulfilled faithfully one of its most basic needs: food supply. Today this still remains its core mission, but it's integrated in a more complex than ever mechanism driven by multiple sociological, economic and environmental forces. This $5 trillion industry representing 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse gas emissions continues to keep pace with world's evolution, changing tremendously over the past years. Digital and technological advancements are taking over the industry, enhancing food production while adding value to the entire farm-to-fork supply chain and helping it make use of natural resources more efficiently. Data generated by sensors or agricultural drones collected at farms, on the field or during transportation offer a wealth of information about soil, seeds, livestock, crops, costs, farm equipment or the use of water and fertilizer.

Today's consumers seek brands that create seamless experiences that feel less automated and more human, less generic and more personal, and less about the brand and more about them. With IBM Watson, Invoca is helping marketers across industries live up to and exceed these consumer expectations. By transforming phone conversations into a source of actionable data, Invoca is using IBM Watson to provide marketers the insights they need to deliver more personalized customer experiences. According to an IBM survey of over 700 CMOs, one of the top four priorities this year is to "inject data-driven insights into every marketing decision." When effectively applied to the customer experience, data has the potential to improve the customer experience, and this applies well beyond workflow automation and customer service bots – it applies to every single customer interaction.