Machine Intelligence – is your leadership style future-ready?

The future is here. 5G is about to change the way we use the internet in Australia. In fact, in some parts of Australia, this new technology has already begun to be rolled out.

At the end of May 2019, parts of Brisbane, Adelaide, Canberra, Sydney, Hobart, Melbourne and other major regional centres around Australia, for example, the Gold Coast, already have access to what is being referred to as the ‘next generation’ of mobile technology.

This new technology means more information can be shared faster and with less congestion. Faster connection speeds which allow for greater amounts of data to be shared means that data-hungry applications can now be used with greater reliability. However, this isn’t just about being able to send bigger files by email, the technology behind the 5G network enables smart machines to learn faster and automation (think driverless cars), to come ‘online’.

The combined power of robotics, machine intelligence, and 5G networks will create a wealth of opportunities for cooperation between robots and humans that has the potential to increase productivity and enhance the delivery of services to customers and stakeholders. Many researchers and market analysts agree that ‘smart manufacturing’ (the combination of smart machines and robotics used in production) is likely to represent the biggest slice of market revenues for the Internet of Things (IoT) in the near future. There are big things to come in this space.

For example, the factory of the future will be built to harness the power of digital manufacturing processes informed by machines that are constantly learning and adjusting the manufacturing process to better meet customer needs. Through the 5G network and future permutations of mobile technology, robots and machine intelligence will radically change the way products are manufactured and services are delivered.

However, as well as considering how automation and machine intelligence will change the way goods are produced we also need to put serious thought into planning the future of our human labour force.

Our organisations are in desperate need of leaders who can recognise the challenges we now face in reskilling and redirecting a substantial segment of the Australian workforce. As we come to accept the introduction and uptake of automation we need leaders who can adequately address people’s fear of the future through culture and an approach to leadership that guides people through this transition.

In his article Who Will Lead in the Smart Machine Age? Ed Hess, Professor of Business Administration at the Darden School of Business, University of Virginia, claims that the technological revolution that is being brought about by machine intelligence and other forms of technological disruption will result in a change in the skills that people will require in the workplace. Hess (2016) emphasises the need for business and management professionals to be able to undertake thinking processes and tasks that machines will remain unable to do well, including higher-order critical thinking, creativity, imagination, innovation, tasks involving high emotional engagement with other human beings (i.e. trust-based relationships).

Rather than developing traditional leadership skills managers wanting to succeed in the ‘smart machine age’ will be better positioned in developing ‘enabling’ skills – the skills required to enable the highest levels of human performance in the pursuit of the organisational mission and meaningful purpose.

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QUTeX has a number of courses to help leaders with transformation and complex change.
Explore your options here: www.qut.edu.au/qutex

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Dr Shari Read is an award-winning educator with a focus on teaching skills for our digital future. As a clinically trained social psychologist and design enthusiast, Shari emphasises human-centred approaches to leadership, management and new ways of working. Her research and teaching in the area of transformation and change management emphasise the capabilities required to lead effectively through uncertainty and complexity.

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