So much of the current discussion about the future of work is about robots and artificial intelligence/AI taking human jobs. The concept of “robots stealing our jobs” misses the point, according to Ravin Jesuthasan, co-author of Reinventing Jobs: A Four-Step Approach for Applying Automation to Work. As managing director at Willis Towers Watson and a thought leader on the future of work, Jesuthasan helps organizations achieve the optimal combinations of humans and machines.

The NCMM caught up with Jesuthasan recently to discuss what middle market companies need to know about AI and how it’s impacting the way companies operate. What follows is an edited transcript of our discussion: 

Why does the popular belief that automation or AI will eliminate human jobs not reflect reality?
Jesuthasan: If you think of any job, it has many different aspects to it. You’ve got work that is fairly repetitive. You've got work that involves creativity. You've got work which may be mental in nature, versus physical. There are so many potential elements wrapped up into any job. Automation doesn't effect jobs: it effects tasks and applying automation to certain tasks within jobs. When you apply automation, one of three things happens. Some tasks are substituted, some tasks are augmented, i.e. the skills of the human are improved, and finally there’s a host of new tasks that are actually created.

Why should middle market leaders care about “Reinventing Jobs?"
Jesuthasan: “Reinventing Jobs” is equally relevant to middle market leaders as it is to the leaders of large companies. One of the most significant challenges leaders face now is getting to the optimal combination of humans and machines. The framework the book offers helps leaders do just that. It asks key questions about the nature of work. What are the different ways we can categorize tasks? What are we trying to solve for with a particular task? Then we look at the three types of automation that are relevant: robotic, AI, and social robotics. And then we lay out, through about 120 examples, how those different components come together to address those questions.

How can middle market companies determine which tasks might be subject to automation/AI?
Jesuthasan: Start by deconstructing the jobs and categorizing the tasks. The three ways in which we think of that categorization are as follows: Is the work repetitive versus variable? So things that are repetitive are rules-based and highly predictable with defined outcomes. They are more subject to automation. Is the work cognitive in nature versus physical in nature? And the third question is whether the work is performed independently versus interactively. Once you've categorized and deconstructed the job, you start to identify the opportunities for automation.

For instance, AI can make a big difference in supporting or augmenting a human in a customer care role. We've got an example in the book of how AI through natural language processing can categorize customer emotion, it can then feed the right text to a customer care specialist. When AI analyzes the customer’s tone, word choices, and emotions, it can help that human customer care worker deal more effectively with a customer.

Can you describe what each of the different types of AI does?
Jesuthasan: There's three broad categories of automation. The most mature is what's called robotic process automation or RPA, which can take on whatever tasks are highly repetitive. Cognitive automation is the second category or artificial intelligence. It includes the underlying technologies of machine learning as well as natural language processing, as in the customer care example in the previous answer.

Last is what we call social robotics. In the old days, equipment was often homogenized, fixed on an assembly line or an automotive plant. A machine did just one thing. Today, that piece of equipment is mobile and integrated with humans in the workplace. You have a complete transformation in how robots work near people in factories and distribution centers.

How is the company Unilever using a blending of AI and humans to optimize recruiting
Jesuthasan: What Unilever has done is recognize that there are parts of recruiting that involve huge volumes of data. The company set up RPA and AI to process all of the information from all the candidates. Second, they’ve looked at talent that has been successful beyond the usual criteria of “what school did this person come from” and “how were their grades.”

They’ve used AI to analyze many more data points. They've been able to look at people who bring in diversity and innovation and non-traditional criteria for success. Through blending AI and humans, they've been able to hire faster and cheaper, while getting more talent in the pipeline.

Why does AI require middle market company leaders to reimagine the structure or their organization?
Jesuthasan: We’re not talking about retooling a process, but about recognizing the cultural change that’s required. That includes recognizing that changes in leadership skills are needed. The second half of the book lays out six changes that leaders need to consider.

For example, we believe in rapid prototyping in helping organizations realize their ROI and understand its culture, as well as its legal and compliance issues. We highlight a company called Haier in the book which recognized that AI and automation provided them the power to move beyond the traditional debate about centralized versus decentralized structure. The company has created a network business of some 200 micro-businesses where their people and innovation are as close as possible to their customers. They’ve tapped into AI to re-envision their organization and create this networked ecosystem.

What else would you like to share with middle market company leaders about “Reinventing Jobs”?
Jesuthasan: There’s a huge opportunity here. This could be a game changer for middle market organizations to leapfrog competitors and rescale their businesses. Doing so doesn't require a ton of capital and presents the opportunity to realize huge returns. As a middle market company, you have less of a legacy of massive IT infrastructure and outdated processes, which larger companies need to dismantle to move forward. 

Legacy has gone from being a definitive advantage for established companies to probably the biggest impediment to their ability to transform. The mindset shift, the tool set shift, the cultural shift that's being called for is diametrically opposed to how these big companies have operated in the past. Well, middle market companies are more agile, more nimble, and can move faster to take advantage of these transformative opportunities than larger companies.

Listen to "Interview with author Ravin Jesuthasan ("Reinventing Jobs")" on Spreaker.