It has been interesting reading a variety of predictions on the impact AI will have on Healthcare in the coming decade! Philips have also shared their thoughts on where the technology could take us. It has been interesting reading a variety of predictions on the impact AI will have on Healthcare in the coming decade! Philips have also shared their thoughts on where the technology could take us.

Artificial intelligence at the enterprise level has truly reached critical mass. It's no longer an "if" question, but more of an inquiry into "how" and "when" AI will be a major component of every strategic initiative. So what started out as a way to perform simple tasks and data mining has become a crucial part of many organizations' strategic planning and competitive decision-making. Heading into 2020, many enterprises are entering a new phase, moving from experimentation and pilots to implementation across the organization, and looking at how AI and data analytics can drive the digital transformation journey. In particular, there are five trends that will be key to enterprises' competitive abilities.

Artificial intelligence is going to overhaul the way we live and work. But will the changes it brings be for the better? As the technology slowly develops (let's remember that right now, we're still very much in the narrow AI space and nowhere near an artificial general intelligence), whether it will end up doing us more harm than good is a question at the top of everyone's mind. What kind of response might we get if we posed this question to an AI itself? Last week at the Cambridge Union in England, IBM did just that.

The vast scope of GDPR has raised fresh challenges -- chief among them is the complex interaction between AI and the GDPR. In particular, this shines a spotlight on Article 22, which concerns automated profiling and decision-making, where the incorrect use of personal data can have huge ramifications for the individuals concerned. The problem is that existing AI system logic takes automated decisions without user consent. Since data is the engine behind AI, Article 22 impacts every industry hoping to leverage the power of technology to drive efficiencies through automated means. In an increasingly data-reliant business landscape, how can organisations reconcile the advent of disruptive technologies and their inherent risks while remaining fully compliant?

Cécile Wendling also led a roundtable on governance tools for responsible AI during the conference organized by Impact AI on AXA's Java site on January 25, 2019. Artificial intelligence will impact insurance in several ways. First of all, it can help change the way insurance companies interact with customers and improve the customer experience. Take the example of damage occurring overnight during a major disaster. At a time when a traditional call center may be closed or busy, we can now imagine customers contacting a chat bot or voice bot to get instructions on the first steps to take in case of damage.

And yet according to 313 executives recently surveyed by Forbes Insights--63% of whom were in the C-Suite--almost all (95%) believe that AI will play an important role in their responsibilities in the near-future. The majority of CEOs today are not drivers of AI adoption--that responsibility falls on C-level technology leaders who need to build a strong business case and show results that encourage a deeper dive into change. With that firmly in mind, Forbes Insights and Intel have taken their combined experience covering and developing technology to produce this introductory guide to AI adoption, from buy-in and deployment to building a corporate culture around data. Consider the below three steps your beginner's guide to AI. It's important to see beyond the swirl of hype and expectations around AI technologies and view them for what they really are--massive accelerators of processes and insights and profound amplifiers of human capability.

A recent Accenture survey found that 85% of business executives plan to invest heavily in AI-related technologies over the next three years. Most investments, according to the report, will be in major business processes, underpinning a company's finance and accounting, marketing, procurement, and customer relations activities. Ruchir Puri, an IBM fellow and chief architect of IBM Watson, certainly thinks so. "There are many opportunities for AI across front, middle, and back office process, throughout lines of business and within various verticals," Puri noted. "AI capabilities, such as conversation, vision and language technologies, can be used to solve a range of practical enterprise problems, boost productivity and foster new discoveries across any area it is applied to."

A recent Accenture survey found that 85% of business executives plan to invest heavily in AI-related technologies over the next three years. Most investments, according to the report, will be in major business processes, underpinning a company's finance and accounting, marketing, procurement, and customer relations activities. Ruchir Puri, an IBM fellow and chief architect of IBM Watson, certainly thinks so. "There are many opportunities for AI across front, middle, and back office process, throughout lines of business and within various verticals," Puri noted. "AI capabilities, such as conversation, vision and language technologies, can be used to solve a range of practical enterprise problems, boost productivity and foster new discoveries across any area it is applied to."

In the argument between Mark Zuckerberg and Elon Musk, it's hard to know which side to join. Both of them are right. Or, if you like, both of them are wrong. Musk is wrong to worry about artificial intelligence (AI) being a threat to humanity, so I agree with Zuckerberg. And Zuckerberg is wrong to dismiss all concerns about AI, so I agree with Musk.

We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments. The following proposed list does not want to be either exhaustive or truth-in-stone, but it comes from a series of personal considerations that might be useful when thinking about the impact of AI on our world. Companies like Vicarious or Geometric Intelligence are working toward reducing the data burden needed to train neural networks.