It wasn’t a relaxed start to the day for Shibu Nambiar, who is Chief Operating Officer at Genpact, when we met him at the London office of the global technology services giant. An early morning flight from Romania into London, a long wait due to rush at the immigration counters at Heathrow and then a dash, suitcase in hand, from the Paddington Station to the office, somewhere nearby.
This morning routine, a walk in the park for Nambiar, who seems to have unlimited energy reserves to tap into. He needs it. The Chief Operating Officer role sees him looking after the Americas, Europe, Middle East and Africa. Australia already ticked off the list. He believes being based in London places him best for the travels, that are inevitably needed, across these markets. Nambiar spoke with HT at length about artificial intelligence, data and tech, and something that’s close to his heart, what he calls “collective intelligence”.
Edited excerpts.
With the intersection of data, tech and AI, how has developing and scaling of solutions for enterprises eventually evolved?
Shibu Nambiar: If you think about our heritage, we were a GE company. Lean Six Sigma is something we take a we take a lot of pride in, even today. I would go to a client, sit with them and talk about our heritage of Lean and Six Sigma. When we started to apply these to business processes, which run large enterprises, we got the optimized view, we got simple principles like Muda (this is defined as wastefulness, uselessness and futility, which is contradicting value-addition) and remove steps to make it leaner. So those were our initial set of things which we were working on. As the world move forward, technology started to emerge, we developed our own IP product called Smart Enterprise Processes.
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It is basically the performance measures and performance drivers, which when you move left and right or you improve the status quo of those, it ultimately has an outcome to the core business metrics. They could be day sales outstanding or revenue dilution, or one of my favorite metrics, cost to process sales. What are the various interventions you need to do to hit that key outcome metric?
We created that smart enterprise processes and moved to the next stage to bring a digital layer and then we started to introduce machine learning concepts to it. We started to introduce no code, low code, quick process automation to it and then of course, generative AI. But as you know better than me, generative AI has been there for many years, almost a decade now – 2014, there were use cases available. We acquired a company Rage Frameworks in 2017, and they were at the core of using generative AI. All of this coming together, the intersection which we’re talking about, which is deep domain combined.
The combined power of bringing data, domain and AI together to generate real world Insights is the new avatar, which we are all working towards now. We’re not perfect. I don’t think anybody’s perfect. Some of us want to continue to keep improving our status quo, but that’s the big intersection for me.
Have any unique use cases emerged in this time, particularly with generative AI?
SN: Take the example of the launch of a new product in the consumer-packaged goods industry. The acceptance of that product for the consumer like you and me and tracking that work back in terms of consumer behaviour, generative AI can play such a key role in not just learning about people and they will react to a new product using the demographics from where they come from, in terms of the location, city country or region of the world, to what part of the society they live in. All that data and how does that get data get reflected on this new launch of a product? Is a great test case to look at and say how generative AI can improve the time to launch of a product significantly.
We play a critical role in some of those aspects. People have stopped talking about COVID and the pandemic, but it’s not too far back when you think about what happened to our lives, but the work which we do as part of our pharma co-vigilance and the tests, lead us to think about launch of a new vaccine in the future and the use of generative AI for the test and to the user towards the end outcome. All the variables which probably took 18 months to two years during the pandemic or in the past, 5 to 7 years, are going to be matter of few weeks. If not less.
Similarly for the work which we do for trust and safety for our high-tech clients in the social media space as an example. For many years now for large platforms social media platforms, Genpact has been working with them to help their algorithms do better for child safety as an example. Generative AI, in my view is the next step to remove certain aspects of that work, which in fact is doing what other providers are doing right at the source, which is somebody’s trying to put the content and it cannot go in, because the algorithm doesn’t let it.
I think it’s super exciting to look at what technologies such as generative AI are doing, and not just limited to how it will help us do things differently.
You’ve often spoken about collective intelligence. Is that definition constantly evolving?
SN: I use collective intelligence and now I’ve started to use AI inclusive. Exciting our teams to stay relevant for future, is so critical for us. The fact that we operate from 35 countries, we get to have so many different cultures come into being in this company of around 1,20,000 people. Large organizations like Genpact, and sometimes we also did this in the past, we did not pay attention to the cultural nuances of people who are part of the organization and what they bring in the way they look at the world versus the way you and I look at the world. Perhaps because we come from part of a world which we are taught to look at things in a certain way, such as the education background, social demographics, exposure and experience, plays a very critical role in how people shape up their thinking.
Perhaps the time I have spent in your offices the last 15 years, made me realize that bringing as many as 20 different nationalities together and just listening to them carefully, allowed me to learn about certain things so differently. Especially when you become leaders of a group, there’s a tendency to go with preconceived notions and views about certain things. And when you don’t allow a conversation to happen, I think it’s a missed opportunity.
Now let’s put in the mix generative AI because we are now AI inclusive. It will allow a very different intellect to come together and hence I call it collective intelligence for the opportunities of any conversation. It can be small ideas, or it can be big ideas. Both are equally important. And then how do you practically put that in place? Having thousands from our teams to participate and finally down to fewer concepts. Ideas which we can then invest our R&D money on. This allows for this collective intelligence to flourish. I’m very passionate about it and will continue to track for sure.
We have the advancement of machine learning algorithms on one side, we have the human element and empathy on the other. Is AI competent enough, for organizations to hand over tasks and completely and remove the human element?
SN: The answer is a resounding yes. Having said that, I think the catch is – as things get automated, it creates a void. What are you filling that void with? I was giving this example recently to my team. In London, there’s a grocery store three minutes’ walk from where I live. Take a bag, walk into the store, buy what you need. What do we do today? I have the Waitrose app. I open the app, choose what I need and buy. It gets delivered next day morning at six o’clock or seven o’clock, and that is convenience.
If I’m going into the store and buy because the store is already there, it’s not an increased activity for the store because it already exists. For me to go in there, walk in and come back, means is zero additional jobs because I’m doing it myself. But to enable me to be able to do it online, 300 jobs get created. When we say 1000s of jobs will be removed, and 1000s of jobs will go away, yes, it is true. But the void will also create so many of new jobs because that void is my need for a different experience.
The experience of me ordering online, will mean generative AI will change the dynamics of app. It can potentially say, you have been ordering a particular kind of cereal for your children for the last 12 months, our recommendation based on dietary requirements would be x-y-z. I expect that to happen in Waitrose app, because then I am told how to live a healthy life on a grocery app. How many jobs will that create? 3000 jobs.
It’s a little bit about how are we looking at the world today, and how we’re looking at the future. And then seeing it’s a big transition, which is going to happen now. Everybody’s worried AI will take their job. When I hear this, I say yes, they will definitely take your job because you’re already succumbing to the pressure and you’re not reinventing yourself. The newly created 3000 jobs are different jobs, not the jobs, which you and I do. I’m super excited with the opportunity. I’m also telling my own teams and lots of people, that need to rescale and adapt.
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