Of all of the technologies that underpin the 4th Industrial Revolution, AI has undoubtedly received the most hype in terms of its ability to transform the workplace. Breathless tomes have predicted the demise of millions of jobs as automated systems frogmarch their way through workplace after workplace.
Except the reality is somewhat different. A recent report on the state of digital transformation by MIT Sloan Management Review and Deloitte Digital suggests that progress is glacial. This is despite executives telling INSEAD researchers that AI and big data have the biggest potential for disruptive change.
This enthusiasm hasn’t actually resulted in much of significance however. Indeed, a recent survey of 2,300 executives conducted by MIT Tech Review and Pure Storage found a C-suite that was enthusiastic about the prospects of AI-driven change, but with little really to show but enthusiasm.
Many are engaging in pilot projects, but there is a profound sense of ‘me too’ in them all, as the pilots are usually at arms length from the rest of the business and with little hope or evidence that they will be scaled up. Indeed, in many organizations there is no resource to do any scaling up.
Back to basics
The experienced among you will have a profound sense of deja vu, that we’ve been here before, and they would be right. Way back in 1990 Michael Hammer, the godfather of reengineering, wrote his seminal article on the topic for the Harvard Business Review.
The usual methods for boosting performance—process rationalization and automation—haven’t yielded the dramatic improvements companies need. In particular, heavy investments in information technology have delivered disappointing results—largely because companies tend to use technology to mechanize old ways of doing business. They leave the existing processes intact and use computers simply to speed them up.
But speeding up those processes cannot address their fundamental performance deficiencies. Many of our job designs, work flows, control mechanisms, and organizational structures came of age in a different competitive environment and before the advent of the computer. They are geared toward efficiency and control. Yet the watchwords of the new decade are innovation and speed, service and quality.
It is time to stop paving the cow paths. Instead of embedding outdated processes in silicon and software, we should obliterate them and start over. We should “reengineer” our businesses: use the power of modern information technology to radically redesign our business processes in order to achieve dramatic improvements in their performance.
Just as previous investments in new technology required a fundamental reassessment of the processes that make up our work, so too do the investments we’re making in AI today. If you don’t do that and simply apply new technologies to legacy processes, the results are altogether underwhelming.
That’s kinda where we are at the moment, and it’s largely why despite the hoopla surrounding the technologies of the 4th Industrial Revolution, these early investments have not moved the dial on productivity one bit.
It should come as no surprise that the latest Willis Towers Watson Global Future of Work survey identifies this as one of the main barriers to successful automaton today. It highlights the crucial role HR can play in deconstructing and reconstructing jobs, and defining reskilling pathways to take into account the way AI-driven technologies will change the roles we have today (note change, not destroy!).
Sadly, there is little sign that HR is taking up the challenge, with just 5% of respondents to the survey saying they’re ready and prepared for what lies ahead.
“It’s critical for employers to address these issues in order to fully automate their work, adequately understand the new work requirements and address skill gaps,” the authors say.
If the lessons from the business process reengineering era tell us anything, it’s that we won’t see the benefits of AI-driven technology until we tackle the changing interface between man and machine.
