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Markets India podcast January 2024
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AI, automation and the future of Indian enterprise
03 May 2024
Please note: Barclays Private Bank does not endorse any of the companies or individuals referenced in this podcast.
In this latest podcast episode – hosted by Narayan Shroff, Head of Investments at Barclays Private Clients India – special guests Jamie Montgomery and Sumant Mandal of March Capital weigh in on how AI and automation are transforming Indian businesses, and the increasing role of Indian diaspora and technology businesses in shaping the future of enterprise technology in India.
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Narayan Shroff (NS): Hello, and welcome, everyone, to our monthly podcast for Barclays Private Clients India. I’m Narayan Shroff, part of the India investments team and I will be your host for this podcast. Today, we have two exclusive guests, Mr Jamie Montgomery and Sumant Mandal, cofounders and managing partners at March Capital.
Without much ado, I’m going to start with a few questions to gauge and get their insight into the technology world. Starting with you, Jamie, what are the key trends and opportunities in enterprise AI, data infrastructure and cyber security?
Jamie Montgomery (JM): Thank you, and good morning, Narayan. Sumant and I am pleased to join you and your colleagues from Barclays and all your colleagues in India. India’s a big part of the technology diaspora. And, look, gen AI is always just top of mind everywhere. Cyber, the tempo and sophistication of the techs remain unprecedented. The tech surface continues to grow. Cloud applications, AI datasets just gets more and more complex and the threats and the nation state actors making attacks, it’s just incredibly more complex.
Cloud migration, we’re only 30% to 40%, a long way to go. Digital transformation, I guess it sped up during COVID, and what does an enterprise look like at the end of the day? Knowledge workers, tools, training, collaboration, culture, productivity. There’s been a massive cost reduction from productivity gains and we had real growth in America, so it’s all about productivity growth. And you compound that and what’s going on in India and what’s going on in the US. We say AI as America and India, I mean it’s really just incredible the opportunities that our two countries have in front of us.
Regulation, you know, kind of looms over us, whether it’s going to get in the way or help us. And then I think the most important issue really is human capital. We couldn’t do this without the human capital and our education system is falling short and we just wouldn’t be successful without thoughtful immigration policy. And you look at that almost 80% of the AI companies have been founded by either immigrants, children of immigrants or, you know, second generation Americans. Same with generally the venture-backed unicorns in America, and obviously the largest percentage of those are from India.
Third of all of our Nobel Laureates and technology over the last century are foreign born and 83% of all PhD students in America are from overseas and, again, many of those are from India. And it’s going to continue on for at least a couple more generations. And births in 2024 are expected to be 24 million in India and about eight times that of the United States next year, so it’s going to continue to really, you know, feed our innovation economy.
So it’s all about talent and it’s all about focus on these growth sectors. So it’s a great question to start with but we’re really married at the hip with India in bringing AI to life.
NS: Yeah, thanks Jamie. Thanks for bringing in, we do keep talking locally on the demographic dividend. I’m glad that you brought that out. Of course, the big thing is about skilling up, you know, to keep pace with the technology development. So coming back, do you see more value in B2B or B2C businesses, and why?
JM: Well, we’re focused on B2B and that’s where we see the investment opportunity. Every IT cycle, investment begins in the infrastructure layer, then the investment in the application layer follows. That was true in the movement to the cloud in the last decade, and before that and, you know, the move to laptops. And, you know, the pattern in the AI appears to be following the same route. The past few years we’ve seen incredible levels of investment in AI infrastructure by the hyperscalers, and hyperscalers mean, you know, Google and Amazon and Nvidia, AMD and others. And, hence, the appreciation in the AI infrastructure value chain, Nvidia, AMD stocks. And 90% of the venture investment AI has been by the hyperscalers and it’s been focused on infrastructure.
But our view as the next wave of value creation and, hence, the investment opportunity will be driven by intelligent automation enabled by AI. This will be automation across industries and within industries. And with prior cycles, new companies will emerge which will compete with and displace the incumbents like Salesforce and ServiceNow were the leading cloud software companies and I expect, well, Sumant and I expect, we’ll see AI core areas of that emerging.
And every cycle sees a few great companies emerge and this holds true. Much of the returns for investors in intelligent automation could be captured in the private markets and that’s what makes it interesting and an opportunity in both the Indian and US economies.
NS: Thanks, Jamie. Overall, at a macro level in this generative AI, machine learning, robotics and automation world, do you see value creation happening more due to societal knowledge expansion, productivity gains, or due to market expansion for enterprise customers?
JM: Well, I think they all fit together. You know, I think, I mean AI advancements allow for the automation of work previously done manually. We are now referring to that as service as software. Based on a recent McKinsey study, generative AI could touch on 80% of the workforce and automate almost 50% of the tasks performed by humans today. This meaningfully expands the overall enterprise software market to previously unpenetrated market segments as you’re taking our labour costs. But we look at both sets of opportunities, companies leveraging AI drive productivity gains in existing processes and those using AI to penetrate untapped markets. Vertical markets such as legal, dental and others.
Altogether, McKinsey estimates this could unlock 8 trillion in incremental economic impact globally and add 500 billion to the software count by 2030. Previously, their estimates were at 2040 or 2050. They’ve moved them into 2030. So I think when I see this bow wave of spending which is really, really interesting and, again, it’s going to be in the application layer, not so much in the infrastructure layer. The infrastructure layer is being invested now as the big boys I think this application layer is an area for, you know, for the venture firms to play in.
NS: Jamie, what has pivoted adoption in the AI space? Is it fear of missing out, or is it due to reducing costs and time for implementation and running enterprise wide programmes? What are the biggest challenges in adoption?
JM: Well, I think, you know, ChatGPT was a real sputnik moment and raised awareness in the boards that this is something that they could and must do. And, you know, companies had to adopt AI to stay competitive and, as a result, gen AI is being adopted at 10x the pace that SaaS was adopted following its inception.
So obviously there’s real cost savings occurring, but there had to be this sputnik moment, you know, 15 months ago when ChatGPT came out. But there’s challenges, you know, talent, change management, data management. You know, it’s not easy, particularly when you’re dealing with the enterprise. There’s always been these transitions and compute and storage and managing it and orchestration of data, so it’s not easy. It’s one thing for companies to make these grand announcements that they’re going to make all these changes, but the blocking and tackling the implementation is very challenging and it’s going to take a while for it to all work, but the opportunity set’s very large.
NS: Thanks. I heard you speak about, what is the Cambrian Explosion of artificial general intelligence?
JM: You know, that’s a big word. You know, when I was a young man I went to Cambridge and I used to use big words, and as I’m getting older I’m simplifying my vocabulary. But about 500 million years ago the Cambrian Explosion occurred and in a short period of time, about 10 million years, much of the current mammal and plant life took its current form. So the question is, is this a similar moment? Are we seeing new types of companies emerge? And, on one hand, it sounds a bit like hyperbole, a little bit like hyperbole as an exaggeration. But, on the other hand, you look at the role of, you know, a group of entrepreneurs, Ashish Vaswani and Niki Parma are two of our entrepreneurs. They introduced a transformer neural network architecture, general purpose transformer, GPT, in a seminal paper in 2017, not that long ago, which unleashed a new realm of possibilities.
And many say their work, this paper defined this generation, if not society. I mean that’s incredible in seven years. Now, tens if not hundreds of billions of dollars are being invested into hardware and software at public and private companies and in governments at both commercial and research projects in pursuit of a system level reasoning which is comparable if not rival to humans to make AGI, artificial general intelligence, real. And each country wants to have their own sovereign AGI.
So, you know, as a breakthrough in this architecture, cost reduction and now just this incredible explosion. So, yeah, I guess. But then, you know, I was looking the other day at an ammonite which dated back 100 million years and you realise that nothing survives forever, and so we all must constantly evolve. And, you know, Sumant and I have continued to evolve with the businesses that we thought were state of the art 20 years ago look pretty outdated now. And I think, you know, this business will just continue to evolve. And, you know, it just takes longer for companies to adopt AI and get it to work throughout the system. So this is a long road ahead of us. And, sure, it's a big, massive trend but it’s going to take a while for it to play out.
I hope I answered your question, Narayan, but, it’s huge but, you know, the Cambrian Explosion, you know, it took 10 million years to form. You know, this will take, you know, a couple of decades to really be implemented throughout industry.
NS: Absolutely. And that’s why we are discussing these topics, Jamie. But are there enough businesses that have pivoted to offer high quality compounding growth opportunities at this stage?
JM: Well, that’s the question. And, you know, we just look for a handful and so, we’ve managed to find a handful and, I think your wording is very interesting, Narayan, about compounding, and that’s the secret here. And what does compound, and, you know, it’s really about the data and running models over the data and gaining insights from the data. That’s why CloudStrike did so well in cyber and Forter did so well in fraud. What business models, you know, can compound to be more valuable over time as they learn more and ingest more data? And, you know, I’ll think you’ll see that more and more. So I think, yes, the answer is there will be many. You know, will it be hundreds? Yes. Will it be thousands? I don't know. You know, we’ll see.
NS: Thanks, Jamie. Yeah, hi, Sumant. Thanks again for joining the call.
Sumant Mandal (SM): Great. Thanks for having me on, and great to have this conversation. It’s nice listening to you and Jamie talk.
NS: Thanks. So what has been the biggest winning attribute for AI businesses in the B2B enterprise solution space? Is it customisation, seamless integration, servicing, or continuous upgradation?
SM: You know, actually, it’s a very interesting question because about six months or nine months ago there was a lot of talk in large enterprise customers about how these LLMs, the open source models that have been launched by people like OpenAI and others are going to solve a lot of problems through it. And they may solve some, but they’ve come to realise that most businesses run on processes, run on workflows, run on systems of records that all need to be considered before you can start using these AI driven technologies to drive either intelligence or automation on top of it.
And what does that mean? That means that enterprise companies don’t buy technology, they don’t consume technology. They consume products and they’re looking for outcomes. And I think that’s where the opportunity set lies for most enterprise AI companies. So in our portfolio, what do we look at? We look at, hey, does this entrepreneur really understand their customer’s problem? What are they trying to solve? Not just the fact that they have some incredible innovation or intellectual property or credibility or passion for start doing, building a business. And then the second layer of that is, is this problem a big enough problem to pay the company worth tens of billions of dollars which means hundreds of millions of dollars of revenue? And I think those are far and few in between.
I don't know if that answers your question, but I think that is the most critical element around thinking about AI that is applied to an enterprise’s problem.
NS: Got it. It does. So, Sumant, you know, which sectors over the next three to five years do you see benefiting the most by AI, ML, automation? And which ones face the biggest threat or disruption?
SM: Yeah, look, I mean first of all, you know, I was looking at, just thinking back in time and thinking how the world of venture capital or technology investing has evolved so dramatically over the last two and a half decades that I’ve been involved in it. And it used to be that IT was a vertical. You invested in IT because your company needed to buy servers and they needed to buy computers and they needed to get them running etc. Now, technology is basically everything. It’s how you work, how you play, how you live, how you travel, how you make decisions. Everything is driven by technology.
So when you say which kind of things are going to be impacted by it, I think pretty much everything’s going to be impacted. Now, the question is in what stage and in what way, what meaningful way does this sort of start showing itself? And I’d say wherever there are repeatable processes that are being done by humans, those are going to be replaced by machines. That’s the easy answer.
Jamie mentioned this, you know, service as a software, or software as a service which kind now we turn these words around against each other or with each other. So a lot of services that were being delivered by humans could now be automated by these new AI techniques, whether it’s, you know, using a mix of machine learning, natural language processing, image recognition, emotional AI, and now, of course, the big transformation into the world of gen AI where you can create or generate content. You know, those industries are at the biggest risk of being commoditised.
And I can give you, you know, we have companies operating in the world of call centres where you have more than about $400 billion is spent on human capital the world over and no-one’s actually happy with their call centre expertise. So that’s a perfect example of where you can use AI to make that process more automated and actually give better service to your customer. But there’s many processes such as these as we’re going to see get sort of automated away, but that doesn’t mean that those jobs will go away. It may make those workers more productive. It may make them do higher levels of work, more creative work. So I think there’s an evolution that we’re in the middle of, but wherever you have repeatable processes and a lot of human services, those can be automated using these machines.
NS: Sure. So, yeah, stuff like legal and the healthcare space…
SM: Legal, dental, healthcare, lots of travel, you know, you don’t need to speak to an agent to book a ticket now. You have natural services, customer care, sales, marketing. There’s a lot of different types of innovation happening in almost every horizontal and every vertical.
NS: Got it. Do you see exits happening more through strategic sale and consolidation or via public markets? Will the industry be dominated by market category leaders, I mean eventually? I mean what’s the end state?
SM: Look, I mean in every vertical in every market and sometimes new markets you probably have one category leader that captures about 70% of the equity value that’s created in that market. You may have a second and it’s probably, you know, one fourth of the value of the first. And maybe a third, maybe not. In the rest you see consolidation, right? And that’s the nature of how you think of our business.
Now 70%, 80% of companies will probably see an exit through an acquisition. That’s been slow. Actually, liquidity has been constrained over the last year and a half or so, two years. We expect it to start opening up a little bit now and more in the next year.
Large corporates are sitting on a lot of cash. They’re going to use that to reinvent their businesses to make their businesses more relevant going forward. But, as investors, we’re always looking for that category leader that we can be part of, like Jamie mentioned CrowdStrike, that can be a standalone public company.
NS: So where do you see VR on the fintech graph or the eCommerce space? I mean is that fizzling out or is that priced out, or do you see interesting opportunities where the new age technology, the generative AI, you know, automation is coming in play to create newer, larger compounding stories?
SM: Yeah, I think that opportunity set does exist. It’s ahead of us. Fintech has been depressed the last 18, 24 months. But it’s an important part of how the world works and I think that, you know, with these new technologies there’ll be new products and services, more efficiency that will be driven into the world, fintech being part of that. eCommerce is another. I would say it’s, you know, depending on which part of the world you’re in, it’s still quite underpenetrated, right? There’s still a lot of growth ahead of us, you know, including countries like India where we have companies that actually operate in both fintech and in eCommerce. You see them growing very well. So I think the opportunity set is still ahead of us. Finding what will be relevant in the future versus what was relevant in the past is what our job is.
NS: Great. So, Sumant, what role do you see India and Indian entrepreneurs playing in your focused investment themes? You know, what, according to you, are sweet sauce, as in India’s sweet sauce, and what role does VCs like March Capital play in scaling these businesses?
SM: That’s a very big question, Narayan, I think. So I think the world of technology that we operate in sometimes it’s quite hard to find companies where you don’t have at least one member of the team who is of Indian descent. And I think that’s the, I would say importance or relevance of what the Indian diaspora and now the Indian next generation of entrepreneurs/technology workers are doing to create these companies, to create these technologies.
You know, Jamie mentioned some numbers. Those numbers are, you know, obviously staggering in themselves, but on a day to day level it’s quite apparent on how important this community has become to the world of technology. Now what’s changed again is we are seeing more and more interesting opportunities, interesting investment opportunities, world class companies, world class products that are being built out of India and approaching the world markets. That never used to happen. India was a leading technology service provider, it was a leading technology human capital provider. Today, it’s becoming a leading technology product provider. That’s exciting to see.
NS: Well, that’s really heartening to hear. With that, thank you so much Jamie and Sumant for joining us today and for sharing some wonderful insights on this ever evolving set of topics. With that, we come to an end of our podcast. Thank you for joining us. Have a great time ahead.
SM: Thank you.
JM: Thank you.
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