Estimates suggest that by the year 2020 we will have 20 billion devices connected to the Internet. Industries are shifting, lines are blurring, and markets are changing all as a result of a technology and digital-centric approach to commerce and business. In this podcast, Cliff Justice, Partner in KPMG's Innovation and Enterprise Solutions group, sits down with Stan Lepeak to discuss: The convergence of robotic process automation (RPA), machine learning, cognitive computing, artificial intelligence, and advanced analytics are driving unparalleled business model transformation. To learn more visit KPMG's Digital Labor website: www.kpmg.com/us/digitallabor. To discover more, read Embracing the Cognitive Era.

We employ some of the brightest and best in professional services, but too much of their time and talent is taken up in research tasks that fail to inspire them. Take our Financial Services Risk and Regulation team – their role is to provide accurate, up-to-date advice on this crucial and increasingly complex area, but the sheer volume of information that needs to be assimilated to do that is growing exponentially. This is one area where AI comes into play – we can now use an AI powered assistant to do the first stage of information processing, using technology tools that can cope with both structured and more importantly unstructured data. That helps speed up research tasks, and frees up time to focus on the intellectual challenges of an engagement turning the gathered information into deep insights. And the best bit is that the tools get cleverer over time: thanks to the inherent machine learning capabilities, the more you use them, the more precise results will be delivered at the first pass.

Today, companies compete for analysts, engineers and data scientists who have hard technical skills and knowledge of distributed computing systems and analytical tools.3 But in the world of machine-reengineering, workers will also need other skills that could be as unconventional as the processes they support.4 These include the ability to program "belief spaces"--advanced probabilistic models that help robots deal with uncertainty--and to work well with intelligent machines.5 Mercedes-Benz, for example, has replaced large, inflexible factory robots with people and smaller, more flexible robots. Now Mercedes-Benz needs a workforce that can teach robots how to collaborate closely with employees on the factory floor.

Deloitte said that around 3.3 million jobs could be classified as business services roles, and that of those, there was a "high chance" that 800,000 to one million jobs would no longer be performed by humans over the period. Simon Barnes, a Deloitte partner, said that the sector's workforce would "fundamentally change over the next 10 to 20 years". Humans are likely to be liberated from "repetitive and highly structured" roles, while new higher-skilled positions are expected to be created to replace them. Mark Carney, the Bank of England Governor, said last month that many of the jobs and industries we are now familiar with "will be gone tomorrow". The rising speed of technological change threatens to make it difficult to choose a career, and for young people to plan their lives, he said.

Up until recently, artificial Intelligence (AI) was regularly associated with sci-fi films and dystopian futures -- but a shift has occurred and it already plays a much more commonplace and integral role in our everyday lives. From betting on the Kentucky Derby, to helping us interact with our banks, emails, and families through AI assistants such as Alexa and Siri, AI is becoming ever more important. It is also becoming more integral to businesses. The 2016 Accenture Technology Vision report showed that 70 percent of corporate executives are making more investments in AI-related technologies than they were two years ago, with 55 percent stating that they plan on using machine learning, deep learning, as well as embedded AI solutions like Amelia. Businesses are using this technology to fundamentally change the way they operate and to drive a new, more productive relationship between people and machines.

During the next five years, messaging will become the preferred path for customer and stakeholder interaction, ultimately displacing call centers and replacing or augmenting mobile apps. For commercial brands and government programs looking to extend and expand their customer base, they must satisfy this customer demand for next-gen messaging channels and rapid response. Booz Allen Hamilton (NYSE: BAH) and Conversable announced today a joint strategic focus to advance, test, and deliver world-class automated interactive messaging, tools, services, and experiences that fundamentally enhance and transform customer care in all channels. The days of commercial brands and federal programs spending millions of dollars and many years to launch an essentially single-use mobile application are coming to an end. Leading brands and programs will increasingly look to bots and automation in messaging to better analyze and understand customer requests, and reach out to new consumers who are rapidly becoming more adept and comfortable with executing commerce through more robust, tailored, responsive and secure messaging platforms.

In 2012, Dennis Mortensen had 1,019 meetings, each of which required an average of roughly eight back-and-forth emails to schedule. Every time Mortensen comes across a contact interested in meeting with him, the CEO and founder of New York City-based artificial intelligence firm x.ai simply sends them a return email copying Amy, who takes care of the rest. "In raw numbers, I've saved about an hour every day -- an hour which I would otherwise have to use in really rudimentary work where I add not much value," Mortensen said of Amy's help scheduling meetings. Virtual assistants like Amy are becoming more common. Just as household technology platforms like Apple's "Siri" and Microsoft's "Cortana" has helped consumers navigate their lives more easily, other forms of rudimentary artificial intelligence platforms are starting to proliferate the market, many of them upending traditional business roles.

The quality of "judgment work" is poised to become a source of competitive advantage for the workforce of the future.

Christopher Crosbie is a Healthcare and Life Science Solutions Architect with Amazon Web Services. This post is co-authored by Gopal Wunnava, a Senior Consultant with AWS Professional Services. SparkR is an R package that allows you to integrate complex statistical analysis with large datasets. In this blog post, we introduce you running R with the Apache SparkR project on Amazon EMR. The diagram of SparkR below is provided as a reference, but this video provides an overview of what is depicted.

Intelligent machines are poised to dramatically shift management roles and recast the workforce of the future.