IBM morphs itself and its staff, as AI looms large

Big Blue's employee training programs and assessment procedures are helping it adapt to AI and other technological breakthroughs.
2 August 2018 | 841 Shares

IBM Engineer, Stefanie Chiras tests the IBM Power System server in Austin, Texas, using the The IBM POWER9 processor delivers unprecedented speeds for deep learning and AI workloads. Source: IBM

Standing still in business simply isn’t an option, in the vast majority of cases. And there’s nowhere where this is truer than in IT companies. Technology’s rapid rate of change means that any organization trying to make its living by selling or trading in technology in some way has to be especially fleet-of-foot.

There are some examples of tech businesses which are frankly unrecognizable from their manifestations of only a few years ago. One such is that stalwart of the hardware market of old, IBM, which is continuing its massive transformation from de facto hardware supplier to businesses, into a service-based and cloud-led company.

IBM’s changes over recent years have not been without their trials and tribulations. The company has divested itself of literally billions of dollars worth of businesses, mainly through selling off discrete divisions and projects, but also through HR realignments – that is, staff layoffs and management culls.

However, Big Blue’s historical emphasis on staff training programs has stood it in good stead, with many personnel able to reskill inside the business and adapt themselves in parallel with the changes the overall company continues to make.

Internal staff assessment & training

There have been other changes for staff too. IBM ditched its internal staff assessment model, called Personal Business Commitments in 2016, which was unpopular firstly because it rated individuals against their colleagues’ performance, but also because it ran in annual cycles. The speed of change in the business (and the tech marketplace) meant that discussing targets set 11 months ago just seemed irrelevant.

Instead, the company now encourages feedback on individuals’ progress much more often and assessment is altogether more adaptive and iterative as skillsets change.

Additionally, IBM’s repositioning into a services company is helped by its staff training budget of US$0.5 billion annually – representing 40 hours per employee, per year. (Perhaps unsurprisingly, as the ones with the most to lose, it’s the more experienced and older staff members who are the most dedicated re-skillers.)

“How do you manage the transition from job to job? By being transparent about employees’ skill profiles – what’s hot, what’s not, and what’s needed,” said Stephen Braim*, in an interview with Tech HQ last week.
* Vice President, IBM, Global Market Support.

In today’s workplace, it’s more important that the employee is open to learning new skills and changing their role according to the need of the company which employs them. “We put the emphasis on agility […] and developing the tools to get the job done. That skill is more important to us than having six [programming] languages under your belt,” said Braim.

At no time in the recent past has the ability to transform been so pressing. The rise of artificial intelligence will indubitably change our world, and a considerable part of that will be which jobs will be done by “robots”, and which jobs will mere human beings still have to do?

AI means change

IBM’s work with AI is well publicised – Watson’s APIs are being leveraged every day in literally thousands of ways – and the company is even using machine learning-driven predictive analysis to try and see what’s likely to happen on the job horizon in the future; in particular, in those roles which have specific technical skills. The results “get fuzzy after the next six months to come,” according to Professor Iven Mareels, IBM’s research lab director.

Change, of course, is nothing new, and its effects can’t be predicted right across the board. The effects of AI will vary according to the time the impact’s felt, the location of industries in question, which jobs are being considered suitable for AI, and even what moral imperatives in a particular geography dictate what is or isn’t OK to have a machine do for us, according to Braim.

When China ceded to the WTO (World Trade Organization) in 2001 the effects were, on some levels, highly localized. “Individuals got hit hard, but that didn’t mean whole economies got hit hard. AI affords us a decent opportunity to plan on the skills front,” he said.

Not every business has US$500 million every year to spend on its workforce’s training to ensure that change is assimilated with minimum pain, of course. That’s where central or local authorities might play a role: “Governments could provide incentives to reskill, in the form of subsidies,” said Braim.

A tax break for companies needing to retrain staff, and retrain quickly, perhaps, as AI changes the employment landscape? It would be refreshing to see a legislature or executive with the foresight and nous to cope with (or even understand) technological progress, for once.