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Smart machine are here, and they are getting better and smarter every year. With the advent of the Internet of Things (IoT), these sector look like they will collide creating many new opportunities for businesses.

In general, a smart machine is an intelligent device that uses machine-to-machine (M2M) technology. Smart machines may include many products and technologies, including robots, self-driving cars and other intelligent machinery that are able to make decisions and solve problems without human intervention.

Smart machines are making a huge difference when it comes to gaining a competitive advantage in the industry. However, other considerations need to be taken into account, especially when smart machine replace human labour. In this case, the market would set speed at which intelligent machines would take over or replace human labour. Of course, smart machine do not have to replace human labour entirely. More than likely is that they work collaboratively with human workers, making their job easier and more productive. Much higher profit margins should be expected from companies that use such intelligent devices effectively that can also enable more efficient manufacturing processes.

Colliding Technologies

Two major trends are reaching a level of advancement that their respective roles will begin to interact seamlessly with each other. These are Smart Machines and the Internet of Things (IoT). When these two technologies are fully realised they will create an explosion of new opportunities in areas as diverse as entertainment, healthcare, disaster management and smart cities. This last one is particularly applicable to Singapore and their Smart Nation drive. There are some indications that the type of opportunities that will arrive from these two colliding technologies will far surpass even those created from the mobile revolution.

A major factor here is cost and technologies that are flexible and efficient enough to realise this potential. In the case of warehouse management where location awareness could be important, however, it is more difficult to track locations indoors as compared to outdoors. This difficulty level however is decreasing and the cost to do so is decreasing all the time.

Another issue here is bandwidth and efficient communications, especially when perhaps thousands of sensors are located and communicating a constant stream of information. Two way communication to a dense population of thousands of sensors is important as well. For instance, in a restaurant where the lighting, music, decor, temperature, humidity and even smells are controlled by feedback from wearables attached to customers. Or a nightclub where the music and lighting are controlled by the movement and bio-feedback of the dancers.

However what if you wanted to do the same for a large rock concert, or the real time control a herd of robots on an automated construction site or choreographing a swarm of nanobots cleaning up an oil spill.

These are some of the IoT Challenges that the industry will need to work out going forward where conventional communication solutions will not cope with the density of devices.

In the case of Smart Machines, which must exhibit a high level of autonomy, products such Google Now for instance is an example of a Smart Machine working on proactive search, cognitive analytics, digital assistants and smart agents.

We already employ a lot of machine learning, optimisation and data science techniques to make our end to end solution very smart. We can see so many opportunities where advances in areas such as deep learning will enable us to make it much much smarter.

Smart machines talking to all these internet enabled devices and in so doing, becoming much more aware of the world around them. This is where the opportunities lie.

The Market

Sixty percent of CEOs believe that the emergence of smart machines capable of absorbing millions of middle-class jobs within 15 years is a ‘futurist fantasy,’ according to Gartner’s 2013 CEO survey. However, Gartner predicts that smart machines will have widespread and deep business impact through 2020.

“Most business and thought leaders underestimate the potential of smart machines to take over millions of middle-class jobs in the coming decades,” said Kenneth Brant, research director at Gartner. “Job destruction will happen at a faster pace, with machine-driven job elimination overwhelming the market’s ability to create valuable new ones.”

CIOs must change their mission to address the proliferation of smart machines in a widening range of jobs and consider the impact this trend might have on their career paths and on increasing levels of unemployment, according to Gartner’s latest ‘Maverick’ research.

Gartner’s Maverick research is designed to spark new, unconventional insights. Maverick research is unconstrained by Gartner’s typical broad consensus-formation process to deliver breakthrough, innovative and disruptive ideas from the company’s research incubator to help organisations get ahead of the mainstream and take advantage of trends and insights that could impact IT strategy and the wider organisation.

Machines are evolving from automating basic tasks to becoming advanced self-learning systems as capable as the human brain in many highly specialised professions. As such, the next wave of job losses will likely occur among highly valued specialists during the next decade.

Gartner research has found that many CEOs are failing to recognise the widespread and deep business impact that smart machines will have through 2020.

“The bottom line is that many CEOs are missing what could quickly develop to be the most significant technology shift of this decade,” said Mr Brant. “In fact, even today, there is already a multifaceted marketplace for engineering a ‘digital workforce,’ backed by major players on both the supply and demand side. This marketplace comprises intelligent agents, virtual reality assistants, expert systems and embedded software to make traditional machines ‘smart’ in a very specialised way, plus a new generation of low-cost and easy-to-train robots and purpose-built automated machines that could significantly devalue and/or displace millions of humans in the workforce.”

The organisation believes that the capability and reliability of smart machines will dramatically increase through 2020 to the point where they will have a major impact on business and IT functions. The impact will be such that firms that have not begun to develop programs and policies for a “digital workforce” by 2015 will not perform in the top quartile for productivity and operating profit margin improvement in their industry by 2020. As a direct result, the careers of CIOs who do not begin to champion digital workforce initiatives with their peers in the C-suite by 2015 will be cut short by 2023.

A number of forces are colluding to make this threat a reality, not least the fact that the technologies for building a large-scale and diverse scope of smart machines are coalescing and being tested by ‘first movers.’ At the same time ongoing weak revenue growth in the global economy will spur demand for cost reduction and productivity improvement by employing smart machines in place of humans.

“It is worth remembering that IT cost is typically about four percent of annual revenue, whereas the labour costs that can be rationalised by smart machines are as high as 40 percent of revenue in some knowledge and service industries,” said Mr Brant. “The supply side of the market — including IBM, GE, Google, Microsoft, Apple and Amazon — is placing large bets on the success of smart machines, while the demand side includes high-profile first movers that will trigger an ‘arms race’ for acquiring and/or developing smart machines.”

While the organisation’s maverick research asserts that smart machines will have widespread and deep impact through 2020, they also recognise there are significant impediments in the business, political, economic, social and technology spheres that must be overcome.

“We certainly will not approach a state of mass unemployment at any time in the near future,” said Mr Brant. “What is also certain, however, is that many new combinations of technology — from intelligent software agents, expert systems and virtual reality assistants to software systems embedded in smart products and revolutionary new forms of robotics — will emerge and have great impacts in this decade. We will not need to develop a full-functioning artificial brain by 2020 for smart machines to have radically changed our business models, workforce, cost structure and competitiveness.”

Building Trust

Realising the potential of smart machines — and ensuring successful outcomes for the businesses that rely on them — will hinge on how trusted smart machines are and how well they maintain that trust. Central to establishing this trust will be ethical values that people recognise and are comfortable with.

“Clearly, people must trust smart machines if they are to accept and use them,” said Frank Buytendijk, research VP and distinguished analyst at Gartner. “The ability to earn trust must be part of any plan to implement Artificial Intelligence (AI) or smart machines, and will be an important selling point when marketing this technology. CIOs must be able to monitor smart machine technology for unintended consequences of public use and respond immediately, embracing unforeseen positive outcomes and countering undesirable ones.”

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