Vishal Harnal, Global Managing Partner, 500 Global
At the sidelines of the recent SuperAI 2024 event in Singapore, Vishal Harnal, Global Managing Partner at 500 Global, revealed the challenges businesses in Southeast Asia (SEA) face in adopting new technology, including Artificial Intelligence (AI).
According to him, businesses in the region tend to move slower in this matter.
“Traditional businesses in SEA are generally slower in adopting technology, but that is changing as the first wave of successful tech startups has emerged. Prior to 2012/2013, the idea of a small company selling a technological solution to a large enterprise is new behaviour,” he told e27.
“In the last five years, this has changed as established companies witness their competitors adopting new innovations and becoming more technologically proficient.”
In general, there are two hurdles that businesses are facing when it comes to new technology adoption.
“The first hurdle is that, for traditional enterprises adopting AI often requires significant changes to processes, skills, and culture. Many established companies lack the technological fluency to implement AI solutions,” he said, adding that changes are now more apparent as the next generation of leaders make technology purchasing and acquisition decisions.
“The second hurdle is that AI applications are still in their nascent stages, and the suite of enterprise-ready products and services are still being built.”
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In this interview, Harnal explains in more detail how 500 Global approaches investing in AI, which has gained a significant surge in popularity recently.
The following is an edited excerpt of the conversation:
What is your investment strategy in Asia, particularly regarding AI?
500 Global is a multi-stage venture capital firm. We invest worldwide and have backed 3,000+ companies operating in 80+ countries in various sectors. The volume of our investments over the last 14 years has allowed us to build our expertise and sharpen our long-term investment theses in Asia and globally.
We think about where the world will be in the next five to ten years, the main drivers of value, what consumers will want, and the way we live, work and play. We identify and invest in technological trends that are hard for the mind to comprehend today but that we believe will drive the global economy in the future.
One of the trends we identified well ahead of the curve in SEA is agritech. In 2015, we started building a thesis around agriculture. SEA is home to large agrarian communities, with eight out of 10 countries in ASEAN dependent on agriculture and its production. Yet, farming practices were primitive, and farmers were disconnected from technology.
So, we invested in a company called eFishery, a full-stack fish and shrimp farming management system (app, IoT devices, and SaaS) supporting more than 200,000 fish and shrimp farmers across 280 cities in Indonesia, and has also launched in India with plans to expand its footprint to five new states by the end of 2024.
eFishery is boosting aquafarm productivity and sustainability by equipping farmers with an AI co-pilot that understands their language (Bahasa Indonesia, Javanese, and English). This allows farmers to actually use the data collected to get answers on how to optimise their farms.
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500 Global has been looking into what we’re now calling AI for about eight or nine years now, so it is one of our long-term investment thesis. Back then, we thought about AI more from the perspective of machine learning and automation before it became mainstream in the minds of the public with ChatGPT in 2022.
We see AI opportunities in three main areas: infrastructure/model building, tooling, and applications. The area we invest in depends on the strength of the markets.
Infrastructure/model-building startups that we invest in are based in the US, Canada, and Europe, and even researchers who move to Japan. For instance, we invested in a company called Sakana AI, an AI research lab at the forefront of exploring alternatives to foundation models that are more adaptive and resilient.
In Singapore, we recently invested in a photonics company focused on supporting data centres in achieving higher computing power for AI.
Tooling is often an overlooked category in general; opportunities in this area are generally in more mature AI markets like the US. In 2009, we invested in Twilio, an AI-powered SaaS company that strengthens businesses’ customer engagement by unifying their data to build insightful customer journey maps.
Applications impact all of us, and this is where we see investment opportunities globally. Startups are using AI to build products and services that solve real problems and create value for their customers.
So, when you look at companies across these three different layers, are there any specific criteria that you use to decide that “this is the company that I invest in”?
It really depends on what area you are targeting in the AI ecosystem.
With infrastructure/model building, we look for subject matter experts with a deep knowledge of AI. As a generalist, you are unlikely to understand the opportunities meaningfully without understanding the core technology and developments. The people in our team who are investing actively in AI are conversant in the scientific research and papers that post-docs are publishing in this space.
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With applications, we look for companies that use AI non-trivially to significantly optimise how they run their business, such as lowering costs or increasing productivity. With AI, what you need to scale changes phenomenally. Even for companies in SEA, AI can allow early-stage founders to punch above their weight.
As for the team, we look for exceptional founding teams with a strong mix of technical expertise in AI/ML and deep domain knowledge in their target industry. They should have a clear vision of how AI can create value for their customers.
What is the big plan when it comes to AI for this year? Apart from all the companies that you have already invested in, is there anything else that you are looking at?
The thinking needs to shift from “Are you looking for AI companies?” to thinking about AI as a technology layer that everyone will adopt somehow.
From an investment perspective, we are focusing on two broad areas:
Companies building core AI hardware. For instance, we’re bullish on the chip space as SEA has been a semiconductor manufacturing hub for the rest of the world, especially in Malaysia.
Companies building vertical AI applications. We are doubling down on startups building specialized AI applications for specific industry verticals such as agriculture, healthcare, finance, and more. These solutions are tailored to each sector’s unique challenges and data environments, enabling faster adoption and value creation.
One thing I have noticed that has not reached its full potential in SEA is the integration of AI into the startup stack—how startups are utilising AI tools to significantly lower costs and increase their efficiency. It is not happening at the scale it is in the US, so I hope that changes and global teams like ours can help accelerate it.
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