What artificial intelligence means for the future of work

There is no organisation, industry, or company that is immune to the effects of technology disruption, from connected devices to automation and artificial intelligence (AI). Whether it’s vehicles that gauge and react to their envi­ronment, online chatbots simulating conversation, or sophisticated algorithms that sort through massive amounts of data with unimaginable speed, the future of work is being shaped by new technologies and their promise.

AI is the technology that may well have the most impact. While AI means “artificial intelligence,” what it represents is far dif­ferent. Instead of being viewed as an alternative to human intelligence, AI should be thought of as a tool that augments human intelligence. In this context, AI’s potential to change the future of work – specifically, how people view work, deploy talent, and create value – needs to be rethought and reimagined.

There is a lot of fear surrounding AI because of its presumed potential to elimi­nate jobs. In fact, according to a report by the World Economic Forum, 65 per cent of children now entering primary school will hold jobs that currently don’t exist. Certainly there is no question that when it comes to such tasks as processing algorithms, rec­ognising patterns, and deep learning, computers can operate with a speed, breadth, and accuracy not matched by humans. But the idea that AI is a job destroyer is largely incorrect. To assess whether AI could replace humans at work, a McKinsey Global Institute team examined more than 2,000 different tasks that constitute jobs – an alternate view to looking at jobs themselves. Each was scored against 18 different capabilities that could potentially be automated.

The research found that approximately half of all activities people are paid to do could be automated through adaptation of currently demonstrated technologies. The research also indicated that this is unlikely to occur at this scale before 2055, pointing out various technological, societal and cultural obstacles.

But whether this happens in five years or 35 years, the real issue is what the elimi­nation of tasks – not jobs – will mean. And it should be viewed as a positive. When machines are allowed to do these tasks, humans will have time freed up to focus on those things machines can’t do: ask probing questions, perform critical analysis, use subjectivity, think creatively, and apply emotional intelligence. By relying on ma­chines for the appropriate tasks, humans will have more time to focus on overcoming business challenges to drive growth.

Research from Accenture speaks to AI’s potential to boost growth. According to Accenture’s Reworking the Revolution (released in 2018), if businesses invest in AI and human-machine collaboration at the same rate as top-performing companies, by 2022 they could increase revenues by 38 per cent and employment levels by 10 per cent. Of the 1,200 senior executives surveyed for the report, almost two-thirds (61 per cent) said they expect the share of roles requiring collaboration with AI to increase in the next three years. More than half (54 per cent) said that human-machine collaboration is important to achieving strategic priorities. In parallel, 69 per cent of the 14,000 workers surveyed said it will be important to develop new skills to work with intelligent machines.

Despite leaders’ conviction about AI’s importance and employees’ belief in the need for skill development, only 3 per cent of executives said they plan to increase investment in training and reskilling pro­grammes over the next three years. This disconnect could thwart AI’s potential as a driver of revenue and employment. Invest­ing in skills and talent is an investment in the future. When a significant number of tasks that have traditionally been part of a person’s job can be performed by a machine, the more accretive capabilities that an in­dividual is hired for – critical thinking and decision making, creativity, and innovative­ness – can rise to the surface.

Regarding the future of work, the focus needs to be on roles – where people are brought into a project because of a match between skills and needs – rather than jobs, where people are limited by narrow descrip­tions of duties. Organisations will structure themselves much more in this way, deliver­ing value through projects that come together and disband rapidly and frequently. People will contribute their specific capabili­ties to projects. Talent will be more fluid, mobile, and on-demand within organisa­tions, with teams shape-shifting as needed to deliver specific business outcomes.

Large consulting companies, such as McKinsey and Deloitte, already work exactly in this project-oriented manner. They are proof that multi-billion-dollar organisations can be as nimble and agile as start-ups in delivering value by viewing strategy through the prism of projects.

The nature of projects and programmes themselves is changing and will continue to do so. Project managers and business alike can prepare for this change. There will be more exploratory projects requiring different methodologies and frameworks. The project manager is going to have to rely on a very different toolbox that allows him or her to adopt the methodology, manage­ment style and thinking most appropriate for the project at hand. Value will be created by innovation-oriented projects and trans­formative programmes to support not only new products but new business models.

Businesses should be thinking about how to retrain and reskill individuals for a business landscape that will continue to be transformed by AI and other technologies. They also need to empower and encourage people to take risks, with the full under­standing that when they actually go forward and test, they may fail. But through fast failure they can learn and continue testing until they find the right way to add value.

Incremental change will not be sufficient for organisations to succeed in the future, and resistance to change or an unwillingness to invest in change could prove fatal. Indeed, organisations governed by the top-down, hierarchical business models that dominated in the last decades of the 20th century lack the innate resiliency that allows them to survive something as disruptive as AI. Such organisations are unlikely to have the vision to see its potential and reap the rewards.


by Murat Bicak, Senior vice president, strategy of the Project Management Institute

For more information, please visit pmi.org/uk

© Business Reporter 2021

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