As industries journey towards the Fourth Industrial Revolution, where people and robots will work together seamlessly, it's becoming more important than ever for organisations to integrate artificial intelligence (AI), robotics and the internet of things (IoT) into their digital game plan. However, much like policy makers, business leaders are struggling to keep up with these advancements. They're failing to leverage technology in areas such as human resources, payroll and workforce management. According to Deloitte's Human Capital Trends Report 2018, almost 95% of organisations worldwide don't know how to manage their workforce effectively. It's a confronting statistic and it's one Jarrod McGrath, founder and CEO of strategic workforce management consultancy Smart WFM, has set out to change. "I couldn't believe how high this figure was," says Jarrod.

Banks Must Invest in Reskilling Their Workforces to Seize AI-driven Growth Opportunities, Accenture Report Finds Stronger commitment to AI could boost revenues 34 percent and employment 14 percent by 2022 NEW YORK; May 2, 2018 – Although bank leaders recognize that intelligent technologies are reshaping the core banking process and can transform customer experiences, few plan to significantly increase investments in reskilling their workforces to enable these technologies in the near-term, according to a report by Accenture (NYSE: ACN). Based on two surveys – one of 100 banking executives and another of 1,300 non-executive bank employees – the report, "Future Workforce Survey - Banking: Realizing the Full Value of AI," estimates that if banks invest in artificial intelligence (AI) and human-machine collaboration at the same rate as top-performing companies do, they could boost revenues by 34 percent and raise employment levels 14 percent by 2022. "As AI becomes more nuanced, its role in banks is moving beyond automation to elevating human capabilities," said Alan McIntyre, a senior managing director at Accenture and head of the company's Banking practice. "To benefit from the potential of AI, banks need to implement'applied intelligence' – combining technology and human ingenuity – across all areas of their core business. To achieve this, they will need commitment from the highest levels of leadership and an understanding that this evolution will require a dramatic change in their workforce."

Bangalore: An in-depth study on talent in the Machine Learning (ML) space by Zinnov, a global management consulting firm, revealed that while a few startups have a had success stories in their AI (artificial intelligence)/ML journeys, there still exists a deep chasm, and most startups and global enterprises haven't been able to succeed and/or scale, their ML initiatives. The AI/ML spend is predicted to touch $400 billion by 2020, according to industry estimates. Given this, it is more important for organizations to invest in the talent that will capitalize on this niche technology. However, acquiring and retaining, the right kind of ML talent continues to remain a significant challenge for organizations. Zinnov's study explained that a large contributor to this challenge is the skewed concentration of the niche ML talent.

The terms of the deal were not disclosed. The deal gives Knowlarity access to the Mumbai-based company's artificial intelligence and machine learning products. It also expands the Singapore-based cloud telephony service provider customer base, adding Sunoray's small and medium customers. "An AI revolution is underway right now, but I believe it needs to be complemented with a design revolution," said Jim Guszcza, chief data scientist at Deloitte Consulting LLP, as quoted in a Wall Street Journal piece. "We don't want to ascribe to AI algorithms more intelligence than is really there. They may be smarter than humans at certain tasks, but more generally we need to make sure algorithms are designed to help us, not do an end run around our common sense."

Over the years there has been a rise in the use of technology in everyday businesses. But, this doesn't simply mean the standard computers or hard drives we use in our daily routines. Newer technology, such as artificial intelligence (AI) is on the rise in the workplace especially because of the productivity benefits. According to a study by Accenture, artificial intelligence has the ability to increase productivity by 40% or more. Through data collection, automation, decision making, and cybersecurity, AI can boost profitability by an average of 38%.

Subscribe to receive updates on Industry 4.0 The digital supply network (DSN) can be a powerful tool for companies, allowing them to harness data and information to make more effective decisions in the physical world via their assets, machines, and people. The benefits can be myriad: deeper visibility into the supply network; greater connectivity with suppliers, partners, and customers; smarter factories; and the ability to act, respond, and adapt intelligently to shifts in the ecosystem. Whatever the result, data--and the ability to analyze and derive insights from it--lies at the heart of the DSN. Companies may think they need to make significant infrastructure investments to realize these benefits, given the typical cost, complexity, and time to "rip and replace" existing applications. However, the road to a fully realized DSN does not necessarily equate to a wholesale replacement of IT assets. In fact, legacy systems are often able to support more DSN capabilities than previously imagined--and the data they already generate often contains significant potential.

Subscribe to receive updates on Industry 4.0 The Fourth Industrial Revolution is upon us. The first three were based, respectively, on mechanization, mass production, and computing/automation; Industry 4.0 is all about the marriage of physical and digital technologies. Just as with the previous revolutions, Industry 4.0 is disrupting and redefining industries. This time, however, the revolution is progressing with unprecedented speed, driven by smart, connected technologies that are developing at an exponential rate.1 These technology innovations--including cloud computing and platform technologies, big data and analytics, mobile solutions, social and collaborative systems, Internet of Things (IoT) technology, and artificial intelligence (AI)--are fueling and accelerating a new era of digital business transformation. They're reshaping how organizations work, innovate, and create products--and enabling completely new kinds of products and services.2 They're spurring businesses to invent new business models and reimagine how they deliver value to their customers and markets. More broadly, industry boundaries are expanding and blurring, and relationships with business partners are being redefined. Yet too many organizations remain unprepared for the new revolution. A recent Deloitte Industry 4.0 study of C-level executives around the world indicates that, across all industries, only 14 percent of CXOs are "highly confident" that their organizations are ready to harness the changes associated with the new era.3

Teaching machines to parse through large volumes of data to learn new concepts and rules is a critical area of development in artificial intelligence, experts told CNBC. That concept is called machine learning, and it's been a longtime goal for the AI discipline: The term was coined in 1959 by AI pioneer Arthur Samuel who defined it as a computer's ability to learn without being explicitly programmed. To do that, mathematical models are built and then fed with huge volumes of data, experts said. The algorithms learn to identify patterns and assumptions from those data sets that are then applied to process new information. "We want to be able to use the machine's own capability to learn from complex data," Eric Chang, senior director at Microsoft Research Asia, told CNBC.

Over the years there has been a rise in the use of technology in everyday businesses. But, this doesn't simply mean the standard computers or hard drives we use in our daily routines. Newer technology, such as artificial intelligence (AI) is on the rise in the workplace especially because of the productivity benefits. According to a study by Accenture, artificial intelligence has the ability to increase productivity by 40% or more. Through data collection, automation, decision making, and cybersecurity, AI can boost profitability by an average of 38%.

Paul Daugherty is Accenture's Chief Technology and Innovation Officer. Over his career, he has worked with thousands of business and government leaders around the globe, helping them apply technology to transform their organizations. He has also been instrumental in evolving Accenture's business to respond to the exponential changes in technology. Daugherty oversees Accenture's technology strategy and innovation architecture, and he leads Accenture's research and development, ventures, advanced technology, and ecosystem groups. He recently founded Accenture's artificial intelligence business and has led Accenture's research into artificial intelligence over many years.