Asian AI Investments & Growth Strategies: AI Apex Capital Connect Forum’s Insights for AI Companies

I was honoured to be the host and moderator of AI Apex Capital Connect Forum 2024, where leading AI voices, investment, and governance come together to discuss the most pressing issues facing the AI industry today. 

Today, we’re here to give you insider insights from three key panel discussions, addressing themes such as:

• How investors can move beyond the hype and focus on sound business fundamentals.
• How can AI companies prepare for the growing regulatory scrutiny as they go public?
• Where the next big opportunities for AI innovation lie—particularly in Southeast Asia.

In this article, we break down: 

1. Rethinking AI funding and public listing strategies as investors become more selective and look for long-term financial performance.
2. Governance challenges for AI companies navigating IPOs, including data privacy, security, and intellectual property risks.
3. AI Growth strategies for startups, focusing on emerging technologies like Agentic AI and untapped opportunities in Southeast Asia.

Rethinking AI Funding and Listings in the New Era

AI Apex Capital Connect Forum 2024 brought together top venture capitalists, investment bankers, and AI industry experts to discuss Global listing options and AI funding strategies for AI companies.

Here are some of the core insights discussed on the theme:

1. Joy of Missing Out (JOMO):

Joyce NG of iGlobe Partners introduced the concept of “Joy of Missing Out” (JOMO) to the investment world, cautioning against the dangers of FOMO (Fear of Missing Out).

In an era where AI hype has led to inflated valuations and rushed deals, NG emphasized the importance of disciplined investing.

“We’ve seen the consequences of inflated valuations and rushed investments,” she explained. “It’s crucial for VCs to find joy in missing out on deals that don’t align with sound business fundamentals.”

2. The Communication Gap:

Peter Chen of Tikehau Capital posed a question that is relatable to every founder pondering about AI growth strategies:

“How can speculative AI technologies effectively communicate their long-term value proposition to investors, especially when commercialization is years away?”

AI startups need to figure out how to connect their technologies with financial performance metrics that actually matter to investors.

3. Financial Performance as the Ultimate Metric:

Expanding on the previous point, Allen Chng of Insignia Ventures gave a clear reminder that no matter how innovative an AI technology is, it must ultimately translate into financial success.

“Any AI innovation a company develops has to translate to the bottom line. If it doesn’t, the expanded multiples are worthless—it’s just hype and crash.”

4. Southeast Asia’s Emerging Role:

Southeast Asia emerged as a central point of discussion, with panelists noting the region’s growing prominence in the global AI landscape.

Ian Leong of Tiger Brokers said, “Southeast Asia is a promising market for AI companies. It has a young, tech-savvy population and high penetration rates.”

One thing is clear after this conversation: Southeast Asia can soon become a key player in AI development, thanks to a combination of:

• Expanding market potential.
• Talent migration from China.
• Speed of digital economy’s growth.

5. The Asia Angle of AI:

Prof. Inderjit Singh, former MP of Singapore, echoed this sentiment in his keynote speech:

“The global AI race is not just about who can develop the most advanced technology the fastest. It’s about who can harness that technology to create the most value for humanity. With our diversity, our dynamism, and our determination, Asia is uniquely positioned to do just that.”

6. Reinventing Listing Strategies:

The traditional paths to public listings came under scrutiny as well, with Xinhua Liu of Gaorong Capital encouraging AI founders to consider secondary listings in smaller, emerging markets, arguing that sometimes being a “big fish in a small pond” offers better visibility and valuation advantages than fighting for attention in larger markets.

Jerry Chua of Evolve Capital agrees while highlighting Singapore’s rising status as a tech listing venue. 

“Singapore offers a unique value proposition for companies looking to tap into Asian markets,” he noted, suggesting that companies should rethink their approach to public listings.

Governance Challenges for AI Companies Going Public

The Forum addressed one of the most pressing issues for AI companies aiming to go public—governance and regulatory challenges. 

Here are some of the core insights discussed on the theme:

1. Governance in an AI-Driven World:

As James Liu remarked, “AI doesn’t fit neatly into any one regulatory box—it touches everything from data privacy to intellectual property to national security.”

AI startups need to proactively engage with regulators and stakeholders to ensure they meet compliance requirements while continuing to innovate.

2. AI Security Risks and Solutions:

Prof. Liu Yang, Executive Director of CRPO and Co-founder of AgentLayer, highlighted a growing concern for AI companies—security risks related to Large Language Models (LLMs) and other AI technologies.

“We’ve seen breakthroughs in AI model jailbreaking, which can bypass current defensive mechanisms with alarming success rates,” he warned.

To address these threats, Prof. Liu proposed a solution: augmenting LLMs with purpose-built AI agents that act as verifiers and governors. These agents would oversee all interactions with LLMs, ensuring that even if the underlying models have vulnerabilities, the system as a whole remains secure.

3. Data Privacy and Intellectual Property:

As AI startups scale, they must navigate complex regulations surrounding data privacy, especially when dealing with cross-border data transfers.

Yang Jingwei, Director of Ant Digital Technologies, emphasized the importance of strong data governance. He outlined three critical actions for AI companies:

1. Build strict policies around data governance to ensure compliance.
2. Be cautious with cross-border data transfers and understand the local regulations in each market.
3. Prioritize intellectual property (IP) protections, seeking patents and securing clear contracts around IP ownership.

4. The Deepfake Challenge:

The panel also touched on one of the more alarming technological developments—deepfakes. With AI making it easier to create hyper-realistic but fraudulent content, the risks to identity protection and copyright have never been higher.

Yang Jingwei mentioned the EU AI Act as a potential solution, which calls for content labeling as a way to prevent deepfake abuse.

However, he acknowledged that implementing this solution requires significant investment and time. “For now, partnering with reliable vendors and using secondary confirmation methods for high-risk activities, like money transfers, are key to mitigating risks,” he advised.

5. The Role of Communication:

Hsu Li-Chuan, Partner at Dentons Rodyk, pointed out that AI companies need to be transparent about their data usage, IP protections, and potential security risks, particularly as they approach public markets. 

“The difficulty with AI is it covers so many different areas of regulation,” he explained. “Companies must be proactive and transparent to build trust with both investors and regulators.”

AI Growth Strategies for Startup Success—Founders and Investors Reveal Their Playbook

Some of the core insights discussed on the theme:

1. The Rise of Agentic AI:

Alex Ren of Fellows Fund opened the discussion by introducing the concept of Agentic AI, a new wave of AI innovation that focuses on enabling autonomous decision-making and task execution.

This year, Fellows Fund was also involved in the $12 million Series A funding round of Gamma, an SF-based AI-powered presentation platform.

Unlike generative AI, which is largely centered on content creation, Agentic AI is designed to take actions and make decisions in complex environments.

Ren explained that his fund is particularly focused on investing in startups developing “vertical AGI,” or AGI-like capabilities in specific sectors such as customer service, marketing, and accounting.

“We’re witnessing a paradigm shift from generative AI to Agentic AI, and it’s going to open up incredible opportunities for startups,” Ren predicted.

2. Product-Market Fit is Key:

Shou Dong of ADVANCE.AI shared his company’s approach to scaling: “We focus on practical applications of AI that enhance efficiency and reduce costs. Large language models are tools, but they must have a measurable impact on operations like customer service and collections.”

Advance.AI has now reached a valuation of over $2bn, making it one of the largest independent technology startups in Singapore.

Dong emphasized the importance of aligning AI applications with real-world business needs, rather than being swayed by trends.

3. Shifting Expectations of AI Investments:

Matthew Ma of Gaorong Capital spoke about investors’ changing expectations of AI investments.

“We’re seeing a shift towards more realistic valuations. Deep tech companies are being valued based on the rarity of their talent and technology, rather than on hype.”

Ma emphasized that investors are looking for clear paths to commercialization and sustainable business models. “It’s not enough to have cutting-edge tech. You need a business that can scale, and you need to show how your product will generate revenue.”

4. Opportunities in Southeast Asia:

Dong pointed out that AI-driven financial services, particularly for small and medium-sized enterprises (SMEs), represent a huge growth opportunity in Southeast Asia.

“There are over 60 million small businesses across Indonesia and the Philippines alone, and many of them are underserved by traditional financial institutions. AI-driven solutions can change that,” Dong noted.

5. Navigating a Challenging Investment Climate:

The panelists also discussed how AI founders can thrive in the current investment landscape, which has shifted to favor startups with clear commercialization strategies and newer business models.

Ma offered a key piece of advice: “Don’t be afraid to focus on niche markets. We avoid crowded spaces and look for companies that can dominate their vertical. Focus on solving tangible problems, and the investment will follow.”

That’s me, Leo @AI Business Asia

1. Selective Investing: Investors are becoming more disciplined, focusing on sustainable business models and financial fundamentals rather than chasing hype.
2. Bridging Innovation and Financial Performance: AI startups must clearly communicate how their innovations will lead to long-term financial success.
3. Southeast Asia as an AI Hub: The region’s youthful, tech-savvy population and high market penetration make it an emerging player in the global AI landscape.
4. Creative Listing Strategies: Entrepreneurs should consider smaller, more focused listing venues to gain visibility and secure better valuations.
5. Proactive Governance: AI companies absolutely need to engage early with regulators and create strong internal policies around data privacy, IP protection, and security.
6. Security Solutions: Augmenting LLMs with purpose-built AI agents offers a promising way to mitigate the growing security risks associated with AI technologies.
7. Deepfake Prevention: Regulatory frameworks like the EU AI Act provide a roadmap for addressing deepfake risks, but companies must invest in partnerships and security measures to protect their IP.
8. Transparent Communication: Clear communication with regulators and investors is essential for building trust and ensuring smooth IPO processes.
9. Agentic AI is the Future: The next wave of AI innovation will be driven by Agentic AI, enabling autonomous decision-making in specific verticals.
10. Focus on Product-Market Fit: AI startups must prioritize aligning their innovations with real-world business needs to achieve sustainable growth.
11. Realistic Valuations: Investors are now looking for startups with clear paths to commercialization and are moving away from hype-driven AI investments.
12. Opportunities in Southeast Asia: The region remains ripe for AI-driven innovation, particularly in fintech and SME financial services.