In this episode, Mehmet Gonullu sits down with Nat Natarajan, Chief Operating Officer and Chief Product Officer at Globalization Partners, to explore what it really takes to deploy AI in highly regulated environments.

From labor laws and compliance across dozens of countries to human-in-the-loop AI systems, Nat shares how Globalization Partners built explainable, trustworthy AI that enterprises can actually rely on. This is a grounded, operator-level conversation on moving beyond AI hype toward real productivity and trust.

⸻

👤 About the Guest

Nat Natarajan is the Chief Operating Officer and Chief Product Officer at Globalization Partners, a pioneer in global employment solutions. He previously held senior leadership roles at companies including TurboTax (Acquired by Intuit), PayPal, RingCentral, Ancestry.com, and Travelocity. Nat brings decades of experience at the intersection of technology, regulation, and large-scale enterprise systems.

https://www.linkedin.com/in/natrajeshnatarajan/

⸻

🧠 Key Takeaways

• Why black-box AI fails in regulated industries

• How human-in-the-loop design builds trust and adoption

• The role of proprietary, vetted data in enterprise AI

• Where general-purpose LLMs fall short for compliance-heavy use cases

• Why AI should augment humans, not replace them

• How CHROs and boards are rethinking AI as a “digital workforce”

⸻

🎯 What You’ll Learn

• How to design AI systems that can explain their decisions

• When to keep humans in the loop and when automation works best

• How enterprises can deploy AI responsibly without slowing innovation

• What makes AI adoption succeed inside large, global organizations

• Why regulated complexity is an advantage, not a blocker, for AI

⸻

⏱️ Episode Highlights & Timestamps

• 00:00 – Introduction and Nat’s background

• 02:00 – Why regulated environments are ideal for AI, not hostile to it

• 05:00 – Lessons from TurboTax and encoding legal reasoning into systems

• 08:00 – Designing AI that avoids the black-box problem

• 12:00 – Human-in-the-loop systems and guardrails

• 16:00 – Why proprietary data beats generic models

• 19:00 – Enterprise vs startup AI adoption dynamics

• 23:00 – AI as a collaborator inside HR teams

• 27:00 – Explainability, trust, and employee-facing AI

• 32:00 – The CHRO’s role in an AI-powered workforce

• 36:00 – From hype to real productivity with agentic AI

• 40:00 – Final thoughts and advice for leaders adopting AI

⸻

📚 Resources Mentioned

• Globalization Partners : https://www.globalization-partners.com/

• GIA: http://www.g-p.com/gia

• Prediction Machines (Updated & Expanded Edition) – referenced by Mehmet

AI models are becoming commoditized, but deploying AI systems that deliver real ROI remains hard. In this episode, Mehmet sits down with Bryan Wood, Principal Architect at Snorkel AI, to unpack why data-centric AI, evaluation, and domain expertise are now the true differentiators.

Bryan shares lessons from working with frontier AI labs and highly regulated enterprises, explains why most AI projects stall before production, and breaks down what it actually takes to deploy AI safely and at scale.

⸻

👤 About the Guest

Bryan Wood is a Principal Architect at Snorkel AI, where he works closely with frontier AI labs and enterprises to design high-quality, AI-ready datasets and evaluation frameworks.

He brings over 20 years of experience in financial services, with a unique background spanning banking, engineering, and fine art. Bryan specializes in data-centric AI, programmatic labeling, AI evaluation, and deploying AI systems in high-compliance environments.

https://www.linkedin.com/in/bryanmwood/

⸻

🧠 Key Takeaways

• Why AI success is less about models and more about data and evaluation

• How enterprises misunderstand ROI and why most projects stall before production

• The difference between benchmark performance and real-world trust

• Why evaluation must be bespoke, not off-the-shelf

• How frontier labs approach data as true R&D

• Why partnering beats building AI entirely in-house today

• What’s realistic (and unrealistic) about autonomous agents in the near term

⸻

🎯 What You’ll Learn

• How to move from AI experimentation to production deployment

• How to design data that reflects real enterprise workflows

• How to identify where AI systems actually fail, and why

• Why regulated industries are proving grounds, not laggards

• How startups can overcome data and talent constraints

• Where AI is heading beyond today’s LLM plateau

⸻

⏱️ Episode Highlights & Timestamps

00:00 – Introduction & Bryan’s background

02:30 – Why data is now the real AI bottleneck

05:00 – Models are commoditized. So what actually matters?

07:45 – Why AI evaluation is harder than building AI

11:30 – Enterprise misconceptions about AI readiness

15:10 – Hallucinations, RAG failures, and finding the real problem

18:40 – Why most AI projects fail to show ROI

22:30 – Partnering vs building AI in-house

26:00 – AI in regulated industries: myth vs reality

30:10 – Startups, cold start problems, and data moats

33:40 – Scaling data operations with small teams

36:00 – What’s next: agents, data complexity, and AI timelines

39:00 – Final thoughts and where AI is really heading

⸻

📌 Resources Mentioned

• Snorkel AI – Data-centric AI and programmatic labeling: https://snorkel.ai/

• Enterprise AI evaluation frameworks

• Frontier AI lab research practices

• MIT studies on AI ROI and enterprise adoption

Live events generate massive attention, yet most venues have no idea who is actually attending. In this episode, Mehmet Gonullu sits down with Matt Zarracina, CEO and Co-Founder of True Tickets, to unpack the hidden infrastructure problem behind ticketing, identity, and audience ownership.

Matt shares how legacy ticketing systems optimized for transactions, not relationships, and why “shadow audiences” have become one of the biggest blind spots in live event tech. The conversation spans SaaS innovation in legacy industries, blockchain learnings, AI-driven personalization, and what it truly takes to build mission-critical infrastructure at scale.

⸻

About the Guest

Matt Zarracina is the CEO and Co-Founder of True Tickets, a ticket custody and identity platform helping venues understand who is actually attending their events.

His background spans the U.S. Naval Academy, helicopter aviation, systems engineering, an MBA, M&A consulting at Deloitte, and corporate innovation leadership before founding True Tickets full-time in 2018.

https://www.linkedin.com/in/zarracina/

⸻

Key Takeaways

• Why most venues only know 30–40% of their real audience

• How “ticket custody” differs fundamentally from ticket sales

• Why legacy ticketing systems were never designed for identity or post-sale visibility

• The real reason ticket resale abuse and bots persist

• How data unlocks personalization, donor growth, and long-term audience relationships

• Why mission-critical SaaS cannot “move fast and break things”

• Where AI fits next: fraud detection, pricing intelligence, and behavioral patterns

⸻

What You’ll Learn

• What the “shadow audience” really is and why it matters

• How True Tickets integrates into legacy ticketing systems without replacing them

• Why frictionless UX is not always the goal and what “optimal friction” means

• How venues can reclaim ownership from secondary markets

• Lessons from building SaaS inside conservative, legacy industries

• Why consultants and operators can become strong founders

⸻

Episode Highlights & Timestamps

(Approximate, optimized for Spotify & YouTube chapters)

• 00:00 – Introduction and Matt’s unconventional journey

• 03:45 – The origin of True Tickets and discovering ticketing’s blind spot

• 07:30 – Defining the “Shadow Audience” problem

• 10:45 – Bots, resale markets, and why legislation alone fails

• 14:00 – Real-world example: turning attendees into donors

• 17:45 – What True Tickets actually does under the hood

• 21:30 – SaaS in legacy industries and mission-critical systems

• 26:00 – Balancing security, friction, and user experience

• 30:45 – The future of ticketing: data, AI, and personalization

• 35:00 – Global expansion and market opportunity

• 38:30 – Founder lessons from consulting to scale-up CEO

• 43:30 – Final reflections and where to learn more

⸻

Resources Mentioned

• True Tickets Website: https://www.true-tickets.com/

• ROI Calculator and Product Demo (available on True Tickets’ site)

• Super Founders by Ali Tamaseb