In Diageo’s giant distribution warehouse in Huntingwood, western Sydney, automation has cut the workforce drastically. The shift to automated cranes has created a speedier supply chain and cost savings for the global liquor manufacturer: the facility now operates in the dark since its robotic workers function just as well without light.

It is a familiar story for manual workers, but now these changes are fast encroaching on the white-collar workforce.

Across the country, leaders pile into information sessions; they espouse the virtues of their forward-thinking, high-tech businesses and their new application of artificial intelligence, wearables or injectables, or they’re busy taking notes, trying to ascertain how far behind the main game they are and whether the impact on their workforce will be 30, 50 or 70 per cent reductions. But beyond that, most of us are just trying to make sense of where this might go and what to do about it.

Some of our largest businesses are facing dark warehouse moments: consulting firms are thinking through staffing reductions of up to 75 per cent in some departments now they have the capability to automate some auditing, processing and document review jobs.

ANZ has signalled ambitious plans that could dramatically shrink its 50,000-strong workforce in coming years, but it is not alone. There are estimates the finance sector as a whole will automate 100,000 roles over the next three years.

Faster, cheaper, higher quality

Research and development consulting firm Faethm estimates the jobs of 46 per cent of employees in Australia will change with automation, and its Future Workforce Index identifies those most vulnerable as: retail, healthcare, education, manufacturing and financial and insurance services.

Michael Priddis, founder and chief executive of Faethm, says it sets up a trend where gross domestic product grows but jobs may not.

Australia should not sleepwalk into this. At a recent discussion with senior human resources directors and CEOs, we discussed how their organisations are tackling the internal human capital, financial and social challenges. Among those taking part were representatives from big four accounting firm KPMG, lawyers Squire Patton Boggs and HR specialist CEB Asia Pacific.

Every company there was already deep into trials to compare the efficiency, cost and knock-on effects of automating various roles.

One large law firm is now using predictive coding to speed up the discovery of documents, a job traditionally done by graduates and paralegals. The process reduces time and cost for the client and identifies relevant documents more quickly.

The dilemma for the law firm: without simple jobs for trainees, how do you build careers?

A large consulting firm experimented with cognitive software to perform audit functions. The results were faster, cheaper and of higher quality. An unexpected benefit was higher staff engagement. Like many companies, its changing business model requires new roles: it is now hiring for coding skills.

Data matters

We need good data on the likely impact of automation on organisations. Most of the data on jobs is “dark”, it resides within company databases. A starting point would be the reduction of jobs, followed closely by the impact on the design of jobs. These two numbers determine the skills and quantum we need for our future workforce.

While most companies are racing to beat the competition by reducing their workforces (and associated costs), some leaders are thinking about the world they want to live in.

KPMG’s national managing partner of people, performance and culture, Susan Ferrier, says: “Companies need to invest in new skills and new ways of working so that we meet the challenge of our future workplaces.

“Now more than ever before, we need to make longer-term commitments to upskill everyone to be ready for the future.”

KPMG is already investing in the development of coding and analytics skills in functions that previously were untouched.

Christy Forest, CEB Gartner’s Asia-Pacific managing director, puts it best: “No single CEO or organisation can solve this individually. The only way to manage the impact of AI is collaboratively, across businesses, across industries and across the whole economy... this is not the time for competition.”

So, to ensure we bridge the AI Nirvana versus AI Armageddon extremes, we suggest some actions we can all take: open employment data (stripped of brand, as we do for WGEA analysis) on aggregate numbers, hours, geography and skills required, for the whole economy; allow people personal responsibility; ensure companies operate to a social licence; and use all three to create a much more mature bipartisan public debate.

It is a big future, but it is ours to decide how we want it to work.

Rhonda Brighton-Hall is co-founder and chief executive of Mwah. Narelle Hooper is an author, director and editor of Company Director.

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