Masters in Business with Songyee Yoon: Investing for the AI Shift

Host: Barry Ritholtz (Bloomberg)
Guest: Songyee Yoon, Founder & Managing Partner, Principal Ventures
Date: April 3, 2026

Episode Overview

Barry Ritholtz sits down with Songyee Yoon, a trailblazing AI investor, engineer, and gaming executive, to unpack the shifting landscape of artificial intelligence, venture capital, and business transformation. Yoon shares insights from her pioneering work in telecom and gaming, explores what it means to back “AI native” companies, and reflects on how education, work, and play must evolve in an AI-powered society. The discussion touches on identifying true value amidst AI hype, the evolution of roles in software development, durable investment strategies, and the societal implications of ubiquitous AI.

Songyee Yoon’s Journey: From Computational Neuroscience to AI Investing

Early Academic and Career Path

• Yoon’s fascination with engineering began in South Korea, where she felt "speaking to computers and programming was very natural" ([03:32]).
• She pursued an undergraduate degree at KAIST and then completed a PhD in computational neuroscience at MIT, seeking to bridge human perception and technology.

  “For some people, singing is natural, some people, dancing is natural... But like speaking to computers and programming was very natural to me.” – Songyee Yoon ([03:32])

• Early professional experience at McKinsey provided exposure to strategy and corporate finance. She later joined SK Telecom to help steer the transition from 2G (voice/text) to 3G (data/image/video), focusing on personalized content powered by AI.

Corporate Leadership and AI Adoption

• At NCSoft, a gaming company, Yoon pioneered data-driven approaches, such as churn prediction and player engagement analytics—often facing internal skepticism:

  “Even with a very clear data and the case presented, it was not an easy task to get everyone's buy in.” – Songyee Yoon ([10:02])

• Persistence led to the foundation of a centralized AI lab, gradually increasing adoption of data-centric processes.

Sifting Value from Hype: The AI Cycle

Hype Cycles, Overcapacity, and Real-World Value

• Yoon contextualizes today’s AI boom as a familiar technology cycle, comparing it to railway and broadband overbuilds:

  “In every platform shift there was overcapacity built... there’s always a kind of excess capacity that’s built.” ([12:01])

• Key for investors: Find applications where AI addresses concrete business problems, yielding tangible efficiency or unique insight.

Durability, Defensibility, and Business Transformation

• Yoon highlights two AI adoption paths:
  1. Augmentation: Using AI to boost productivity within existing workflows.
  2. Redesign: Rethinking processes from scratch ("clean sheet") to build genuinely AI-native organizations.

The Evolution of Work: AI’s Impact on Software Development & Creativity

AI Development and Human Roles

• Yoon reflects on tools like Claude automating code, streamlining tasks, and shifting human focus:

  “A lot of the coding is done using tools like Claude... which means that we need less people in the loop.” ([16:34])

• Still, critical roles remain for creative architectural decisions and innovative experiences.

The Future of Human Work

• Yoon underscores unpredictability—new careers will emerge as old skills are automated:

  “I don’t know what other jobs are going to be created in the world where the things that needed 100 people... can be done with a fraction.” ([18:06])

The Significance of Play: Leveraging Gaming and Innovation

Play as a Driver of Innovation

• Yoon’s book, “Push Play: Gaming for a Better World,” argues that play is essential for evolution and cultural adoption of new technologies:

  “My motto is like, we don’t live to work, we live to play... When we have a good understanding of the material... then you turn that into utility.” ([21:58])

• The gaming sector often pioneers tech first (AI, cloud infrastructure, freemium models) given its risk tolerance and early adopter user base.

AI and Education: Preparing Humans for the Future

Rethinking Education for an AI World

• Traditional education has focused on knowledge delivery, now commoditized by AI:

  “Knowledge delivery and memorization is rapidly being commoditized... what our next generation needs is more of the creativity and the problem-solving skills.” ([26:47])

• Yoon advocates building curricula around creativity, problem-solving, and leveraging uniquely human strengths.

Competition, Moats, and AI’s Economic Consequences

How AI Compresses Industry Moats

• As AI automates legal, tax, and accounting tasks, businesses must seek new differentiators—such as proprietary data, creativity, and adaptability.

Embracing Disruption

“There are so many other problems to solve that AI cannot address... we have to prepare to accept new type of roles and professions enabled by this technology advancement.” ([29:53])

Investing in AI: What Makes a Company “AI Native”?

Defining “AI Native”

• True AI native companies are architected "from the ground up" around the latest AI tech, with unique organizational design and fully integrated AI workflows:

  “If you are trying to sprinkle AI, can you do the same thing without AI? Why do you need it? Why is it indispensable?” ([40:46])

• Yoon leverages her gaming background as a predictive lens for AI adoption trends.

What’s Investable Now

• Durable infrastructure: Yoon prefers companies building foundational tech (Together AI, Cartesia) or those with strong data flywheels enabling defensible moats (Sesame).

  “I try to invest in companies that's going to be durable in the coming decades... building this data flywheel that over time builds very defensible moat.” ([34:22])

The Inflection Point: Comparing Today’s AI Shift to Past Tech Shifts

Why Now Is Different

• Current transformation parallels the railroad era; the crucial difference is scale—massive infrastructure enabling unpredictable new businesses:

  “AI shift is closer to the introduction of the railroad than introduction of the PC or Internet... the biggest breakthrough was actually the scale.” ([43:21])

• This foundational infrastructure sets the stage for unforeseen innovations, just as broadband enabled YouTube, AWS, and online gaming.

Regulation, Geopolitics, and the Unknowns Ahead

Navigating Risk

• Regulatory developments and copyright issues are now central in AI. Yoon stresses the importance of transparency and openness and warns investors to remain nimble and adaptable given the field’s rapid evolution.

“All this kind of the models and structures can change significantly... has to remain nimble and flexible.” ([52:13])

Advice & Big Takeaways

For Students and New Careers

• Don’t chase trends—pursue what you’re passionate about and expect a bumpy, disruptive path where flexibility is essential:

  “What I would like to remind them is... really have to stick to what you are... what you’re passionate about.” ([55:17])

• Be a generalist and stay adaptable ([56:25]).

For Investors

• Patience and compounding matter as much in human networks and tech as in finance:

  “It seems very slow today. But like if you're persistent and for 20 years, what you can achieve is really tremendous.” ([56:42])

Notable Quotes & Memorable Moments

• On the evolving nature of AI work:

  “Jobs like YouTubers, a podcast, these are the type of job that didn’t exist 10 years ago.” – Songyee Yoon ([18:06])

• On AI in gaming’s innovation cycle:

  “Gaming has been always the platform that was brave enough to incorporate [new tech] in our offering... it was okay in gaming because gaming is a very low risk environment.” ([21:58])

• On foundational change:

  “This AI shift is closer to the introduction of the railroad... it was scale, pouring a lot of resources... that allowed us to come here.” ([43:21])

Timestamps for Major Themes

• [03:32] – Yoon’s early passion for programming and education
• [05:33] – Transition from academia to McKinsey and corporate AI
• [09:49] – Early pushback and perseverance in AI-driven churn prediction
• [11:39] – Assessing hype vs real world AI value
• [12:48] – Durability, defensibility, and real world impact
• [14:38] – Augmenting vs. redesigning company workflows for AI
• [16:34] – AI-driven coding and shifting developer roles
• [18:06] – The unpredictable evolution of future jobs
• [21:58] – “Push Play”, gaming, and innovation adoption
• [26:47] – AI’s impact on education and human skills
• [29:53] – AI compressing business moats; the search for new value
• [38:38] – Defining and funding “AI native” companies
• [43:21] – The inflection: AI as foundational infrastructure, like the railroad
• [52:13] – Need for nimble, flexible investment strategies in early innings

Resources & Recommendations

• Book Recommendations:
  • Empire of AI
  • Power and Progress
• Streaming/Listening:
  • Spotify, Taylor Swift, Netflix K-dramas

Closing Advice

The AI revolution is only just beginning—embracing rapid change, investing in durable fundamentals, and leveraging uniquely human creativity are more important than ever for both entrepreneurs and investors.

Summary by AI, based on the April 3, 2026 interview on Masters in Business. Timestamps reflect content locations in the original episode. All quotes attributed as spoken.