According to global consulting firm Accenture, intelligent automation powered by machine learning processes is 2016's biggest tech trend. For tech giants like Amazon and Google, machine learning has long been central to their operations - the most famous example being Amazon's recommendation engine, which many see as having been the key to its success. Such technology has huge implications for organizations across all industries though, and the wealth of data that companies now hold, along with the rise in affordable products like Microsoft Azure ML and IBM Watson, mean that they are rushing to adopt it.

Young people will bear the brunt of Artificial Intelligence (AI) fuelled job losses as smart systems undercut entry-level roles in everything from marketing to retail. Machine learning and expert systems will not destroy jobs wholesale, predicts George Zarkadakis, digital lead at advisory firm Willis Towers Watson, but will remove the need for many tasks that employees have traditionally cut their teeth on at the beginning of their careers. Zarkadakis cited a study by consultants McKinsey, which found that just under one third of activities that make up 60 percent of existing jobs will be automated. Unfortunately for new entrants to job markets, the bulk of these activities will be concentrated in starter roles, said Zarkadakis. "We've done some research ourselves and looked at the impact on entry-level jobs. Jobs that graduates get once they leave university. We found that many of the entry-level jobs are very susceptible to complete obliteration," he told The AI Summit in London.

We began by considering the broad discoveries of Accenture's Technology Vision report. It reveals that '70% of executives are making significantly more investments in artificial intelligence technologies than they did in 2013'. So are there any particular industries that are taking to AI more than others? "At Accenture we see AI being adopted across all industries", Marc says. "Some disciplines are using AI more than others, but we really are seeing it across the board, and I would not say there is one industry specifically that is using AI more than another".

Intelligent machines inform better, faster decisions. They enable managers in insurance to shift their focus to activities that call for decidedly human traits such as complex thinking and higher-order reasoning. Providing guidance and recommendations, machines complement managers' expertise, experience and ethics, as well as their ability to experiment and innovate. The overwhelming majority of insurance managers believe machines will make them more effective and their work more interesting. However, the survey also revealed a lack of trust in machines among managers that might affect an organization's ability to make the most of cognitive computing.

Artificial Intelligence is a technology that uses human-like learning to perform tasks. The idea of Artificial Intelligence or AI is nothing new. As a concept it has been in our literature and art for centuries. But these ideas had no foundation other than as philosophies of nature and science fiction. Connectionist paradigms of Artificial Intelligence have a somewhat more flexible approach than their rule-based cousins, but both have applications in modern technologies. Machine learning is based on artificial neural networks, which are a much-simplified version of how our brains work.

As the Director of Data Science for an advanced analytics company, Sean brings machine learning automation into business applications to help organizations build core strategies around data. Having worked across diverse industries, and alongside many talented professionals, Sean has seen the blend of approaches required to successfully convert raw data into real world value. Sean holds his doctorate in scientific computing where he used advanced mathematics, parallel computing and optimization to solve challenges in nanotechnology, chemistry and renewable energy. After completing his Ph.D. Sean started his own Data Science consulting practice, helping companies automate decision-making and uncover the underlying patterns that drive business environments. Sean has since worked for global consulting firms and silicon valley startups to help bring the advances in machine learning to business applications.

In our first blog post on AI Everywhere and Nowhere, we outlined the challenges of defining Artificial Intelligence and in our second blog post, we described how ubiquitous AI is becoming and defined it as Ubiquitous Intelligence. In this blog, we define the continuum of AI as AAAI–Assisted, Augmented, and Autonomous Intelligence. Over the past couple of decades, AI has replaced many of the repetitive and standardized tasks done by humans. For example, industrial robots are tackling many manufacturing tasks. Similarly, many administrative tasks like taking minutes of a meeting, answering the phones, and searching for information are all done by some form of an automated system.

Accenture is expanding its machine learning and operations analytics capabilities with the acquisition of OPS Rules, a boutique analytics consulting company that specializes in operations analytics solutions.

Global consulting firm Accenture has released a report looking at the potential benefits of autonomous vehicles in Australia and what connected industries may be affected by the advent of self-driving.