At CES AI House 2025, a distinguished panel of investors and founders unpacked the key forces shaping the future of artificial intelligence. With AI revolutionizing industries and driving new investment opportunities, the discussion highlighted strategies, challenges, and trends for startups, enterprises, and investors alike.

Moderated by Denise K. Záles (CIO of Incrediwear), the panel included Tony Kim (BlackRock Fundamental Equities), Moyi Dang (Coinfeeds), Alex Yeh (GMI Cloud), Warren Packard (AI Fund), and Tien Wong (IronGate Capital). Their perspectives provided a roadmap for navigating AI’s complex but promising landscape. The panel session can be watched in its entirety here.

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Here are the key insights from the session.

The Evolving AI Investment Landscape

AI has become a horizontal technology, touching nearly every industry, but the investment strategies that underpin it remain rooted in scalability and differentiation.

• Tony Kim described AI’s dual role: “Labor accounts for the largest share of enterprise spending, and AI agents, co-pilots, and other tools are poised to transform this space by reducing costs while creating entirely new ways of working.”
• Warren Packard likened AI’s transformative potential to electricity: “We pair subject-matter experts with cutting-edge AI to build businesses that disrupt industries at scale.”
• Both panelists emphasized that vertical-specific applications represent the biggest opportunities for innovation and investment.

Enterprise AI: Overcoming Challenges to Unlock Potential

Enterprises are often held back by systemic barriers when deploying AI. Security, data silos, and scaling infrastructure are top concerns.

• Alex Yeh stressed the critical importance of security: “For enterprises, security is everything—especially for sensitive data still stored on-premise. Without robust systems, deploying AI at scale becomes a significant risk.”
• Enterprises often struggle with fragmented data across departments. “To extract insights, businesses must break down silos and adopt IAM systems that ensure only the right employees can access the right information,” Alex explained.
• Tien Wong noted the role of AI agents in enterprises: “These systems can increase productivity by automating repetitive tasks, but their deployment requires clear guidelines to avoid ethical or regulatory pitfalls.”

GMI Cloud plays a vital role in addressing these challenges by helping enterprises design scalable, secure solutions tailored to their needs.

Startups: Speed, Cost, and Usability Drive Success

Startups are moving at lightning speed to capitalize on AI’s potential, but success hinges on three key factors: speed, cost, and ease of use.

• Moyi Dang shared how Coinfeeds helps investment funds analyze massive datasets with AI: “Our tools allow startups and funds to uncover patterns in hours instead of weeks. Speed and scalability are game-changers.”
• Startups don’t have the time or resources to manage complex infrastructure. “They need tools that are simple to integrate and easy to deploy,” Moyi said.
• Alex Yeh echoed this, emphasizing the importance of agility: “Promising a product a year from now isn’t enough when your competitors are launching today. Scalable GPU usage and intuitive APIs are critical for startups to succeed.”

Data Diversity and Localized AI Models

The panel agreed that diverse datasets are crucial for developing impactful AI solutions. Without them, applications risk missing the mark in industries like healthcare or consumer products.

• Warren Packard underscored this point: “You can’t advance medicine with data that only represents a narrow segment of the population. AI must reflect the diversity of its users.”
• Alex Yeh added, “Localized LLMs are critical for accuracy. Ask a global AI model about the best ramen shop in Kyoto, and it might not know. Tailoring models for specific geographies ensures relevance.”

The future also lies in synthetic data, as Tony Kim pointed out: “The vast majority of human-created data has already been consumed. Advances will increasingly rely on synthetic datasets and reasoning models designed for specific domains.”

What Lies Ahead for AI Investment?

As the conversation turned to the future, the panelists outlined two major trends: consolidation at the infrastructure level and innovation at the application layer.

• Alex Yeh noted, “Infrastructure requires immense capital. The players are already set, and we’ll soon see a wave of mergers and acquisitions.”
• While large players dominate foundational infrastructure, Tony Kim highlighted opportunities for startups: “The application layer is ripe for innovation, with vertical-specific solutions redefining industries.”

AI’s dual focus on cost efficiency and breakthroughs will continue to drive the market. As Tony observed, “AI isn’t just about saving money—it’s about creating entirely new markets that didn’t exist before.”

Takeaways from CES AI House 2025

This panel revealed a wealth of insights into the rapidly evolving AI landscape:

• For enterprises: Address systemic challenges like security and data silos to unlock AI’s full potential.
• For startups: Focus on speed, cost, and usability to gain a competitive edge in crowded markets.
• For investors: Look for vertical-specific applications that address real-world problems and have clear paths to scalability.

As Alex Yeh concluded, “The future of AI lies in enabling businesses to harness its power securely and effectively. The real winners will be those who innovate while keeping an eye on practical adoption.”

Ready to navigate the next wave of AI innovation? Explore GMI Cloud to learn how we can help you scale.

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