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.

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.

Technologies that most, if not every, technologist is well aware of. Maybe a little more nuanced for some to track? The beauty of being a budding technologist is that the landscape is constantly changing and forever in flux. What was once a herculean task of reading magazines and books with the hopes of finding the necessary information to connect the dots has been trivialized to a simple "online search" or a quick question to your phone. With the general accessibility of the internet, the ability to track and understand the technology landscape has simplified.

The market for Service Delivery Automation (SDA) is a fast moving one, both in terms of adoption as well as advances in technology. Many organizations have already tried and adopted SDA technologies, such as Robotic Process Automation (RPA) and cognitive automations, based on machine learning software. These organizations are looking beyond Proofs of Concept (PoC) and trials to wider adoption of SDA across their organizations. An SDA Center of Excellence (CoE) enables organizations to develop their SDA capabilities and competencies in a controlled and centralized manner. It helps organization to stay abreast of developments in the fast-moving world of SDA.

I recently spoke at the Deloitte Shared Services and Outsourcing Executive Forum at Deloitte University. The audience's interest level in automation strategies was high. For the most part, Deloitte doesn't outsource directly, but only provides consulting services to its clients about outsourcing and shared services strategies, so the event and this essay seem appropriate venues to discuss the impact of "cognitive automation" technologies on the outsourcing industry. I use quotation marks around the term "cognitive automation" because though I am told that that is the preferred term these days at Deloitte, I am still getting used to it. I like the term because it suggests a broad approach that goes beyond current automation-oriented technologies and methods.

KPMG's recent announcement was particularly noteworthy from my perspective, because it indicated that the audit firm would be deploying IBM's Watson "cognitive computing technology" to KPMG's professional services offerings.--According "One current initiative is focused on employing supervised cognitive capabilities to analyze much larger volumes of structured and unstructured data related to a company's financial information, as auditors'teach' the technology how to fine-tune assessments over time. This enables audit teams to have faster access to increasingly precise measurements that help them analyze anomalies and assess whether additional steps are necessary." IBM is, of course, one of KPMG's biggest software-auditing clients. All of these recent reports mention that the AI technologies currently are being contemplated for use in connection with financial audits.

News flash: Artificial intelligence (AI) and other cognitive technologies are eliminating jobs left and right. The short answer is no…don't lose sleep over it. First off, cognitive technologies (even super cool advanced ones) are best with structured tasks and finding patterns. You know, auditing grunt work. I assume most sane people would prefer to not be subjected to the mundane, mind-numbing work anyway and say, "Go ahead, automate the cross-footing and put me out of my misery!"

Artificial intelligence (AI), one of 20 core technologies I identified back in 1983 as the drivers of exponential economic value creation, is rapidly working its way into our lives from Amazon's Alexa and Facebook's M, to Google's Now and Apple's Siri. An example of how far AI has come is the recent news that a Google supercomputer, using its advanced AI software, was able to win a stunning 3-0 victory in a man vs. machine face-off against Go grandmaster, one of the game's all-time champions. For those who are not familiar with Go, it is a 3,000-year-old game that is widely considered to be the most complex game ever invented because it is reported to have more possible board configurations than there are atoms in the universe. Until just a few months ago, it was thought that a computer could not defeat a human grandmaster for at least another decade due to the game's complexity. How did Google's AlphaGo program advance so much faster than many expected?

Accenture has introduced an intelligent automation platform for application services that provides human technology workers with better productivity and insights to enhance business performance. The platform, Accenture myWizard, augments human technologists with virtual agents powered by artificial intelligence. It helps humans and machines reach their exponential potential in application services. The platform currently includes several intelligent virtual agents that use machine learning to collaborate with their human co-workers. The platform brings together various Accenture industry assets such as intelligent and analytics tools and methods, as well as tools from across the company's alliance partner ecosystem.

For the consumer & retail and banking industries, standard features can be configured into customer interaction templates for use in attending to customers or for marketing activities. In addition, Pepper can store information from interacting with customers on the cloud for future analysis, and the data can then be visualized, providing an integrated streamflow through to customer support. Pepper also has sensors to detect anyone approaching it, which enables interaction with that individual. Following the interaction, the new customer information can be reviewed through Interactive Analytics. "We need to know more about Pepper. In ten years, Pepper will be used in ways we never imagined. Accenture is working together with Softbank Robotics to take it to another level, thinking about how it can help solve our client's challenges and how it can be used to provide better customer services."