Recent years have seen plenty of fearful commentary about the workplace of the future. That fear is misplaced.

In recent years, much has been written about technologies like artificial intelligence (AI) and automation, and their expected impact on businesses and their workforces.

Often enough, such conversations are downbeat: Technology will be used to cut costs by replacing humans—with all the negative social and individual consequences that brings.

Optimistic commentators, on the other hand, envision a world in which technologies unlock new sources of growth, create jobs and free employees from mundane tasks.

Although we can’t be certain where we will end up, I side with the optimists. First, in any business—and especially in services-based ones like finance—it is the workforce that drives value. When trained with the right skills, people make the difference between leaders and laggards. Adding technology to help them might prove a huge positive.

Second, although automation can be used to cut costs, that’s not where it adds most value: this lies in deploying it to create new opportunities. Of course, smart firms apply technology to automate certain tasks, but with the aim of freeing up funds to re-skill workers and allowing them to better understand their customers and improve their service.

Upside-down

It’s no surprise that the views of executives and workers mostly differ when it comes to the expected impact of technology. But here’s what is surprising: You’d think management would be keen to apply solutions like AI and automation, while staff would be resistant. That’s not the case.

In 2018, we surveyed more than 1,200 CEOs and senior executives working with AI in 12 industries and 11 countries, along with more than 14,000 workers representing all skill levels.1 The banking subset (which you can read about here) included 100 CEOs and senior executives, and more than 1,300 staff at large organisations.

We found staff were more enthusiastic about the benefits that AI, for instance, would bring. They were impatient to learn the necessary skills, and had a vision of how AI would help customers. More than two in three banking staff felt AI would improve both their work and their work-life balance.2

Banking executives, on the other hand, wrongly assumed workers would resist the introduction of AI. And, because they didn’t recognise staff enthusiasm for AI, executives weren’t funding the necessary resources for building those skills.3

They should. Our analysis shows that banks that invest in AI and human-machine collaboration at the same rate as top-performing businesses could increase revenues by 34 percent on average between 2018-2022, and their employment levels by 14 percent.4

As it turns out, most employees see how AI and automation benefit their lives outside work; they want to know why it’s not being used more at work.

What happens next?

Despite huge advances in technology, the way organisations are structured hasn’t changed—nor has the nature of work. Society itself must prepare for a world in which—as the authors of The 100-Year Life note5—we live longer, re-skill during more diverse and lengthy careers, and create a better work-leisure balance.

Within organisations, the old career path in which you toiled for years before being elevated to a managerial position is at an end. The workforce of the future will need professional skills, of course, but it will also need competencies like problem-solving. In times of change, it is the problem-solvers who navigate organisations through trickier waters.

The good news is that these skills can be taught—which takes us back to the fact that employers need to fund them. Neuroscience has shown that the belief that “you can’t teach an old dog new tricks”6 is false: Humans can continue to learn and adapt throughout their lives. They just need the opportunity and the willingness to do so.

Scientific advances have shown us, too, that it is experiential and immersive learning that creates new neurological pathways. That can be team-based learning, taking a concept learned in a classroom and applying it on the job, or a virtual-reality-type experience.

On the organisational side, firms must build organisational agility, or “the ability to respond effectively, with speed and stability, to opportunities and disruption”.7 They must also better understand the skills they have on hand, and then—based on future work needs—determine the skills they need to develop.

Additionally, they must understand how they create data, and ensure they make better data-driven decisions as the demands around the nature of work change. And lastly, they should think about the evolution of work: how its nature will change given the technologies they want to employ—and what that means for their workforce.

To hear more, listen to the podcast, where my Accenture colleagues Pia Dupont and Tim Broome explore the topic further. The second episode of our series is called Augment or automate—How are you reimagining work and creating a future-ready workforce?


1Future Workforce Survey – Banking: Realizing the Full Value of AI, Accenture (2018)
2Ibid.
3Ibid.
4Ibid.
5The 100-Year Life: Living and Working in an Age of Longevity, Lynda Gratton and Andrew Scott (Bloomsbury Business, 2017)
6Can’t teach old dogs new tricks? Nonsense. Tips for learning later in life, The Conversation (12/5/2017)
7Talking Agility, Accenture podcasts

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