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20VC (20 Minute VC)

20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies

83 min episode · 2 min read
·
Matt Fitzpatrick

Episode

83 min

Read time

2 min

Topics

Productivity, Leadership, Sales & Revenue

AI-Generated Summary

Key Takeaways

  • Enterprise AI Gap: MIT reports only 5% of GenAI deployments work in enterprises, with Gartner predicting 40% of projects will be canceled by 2027. External builds prove 2x more effective than internal teams due to talent constraints and lack of disciplined ROI frameworks.
  • Forward-Deployed Engineers: Enterprise AI adoption requires forward-deployed engineering teams for customization and workflow integration. Invisible operates 450 people across eight offices, spending three months on customer implementations rather than charging for out-of-box software that fails without deep integration work.
  • Proof Before Payment: Invisible runs eight-week solution sprints at no cost to prove technology works before customers pay. This approach reduces sales costs while building trust, contrasting with traditional Accenture-style multi-year implementations that often fail to deliver working systems.
  • Human Data Superiority: Synthetic data works only for base truth tasks like math. Multi-step reasoning across 45 languages, multimodal contexts, and specialized domains requires PhD-level human feedback. Invisible manages 1.3 million experts annually, sourcing niche specialists within 24 hours for validation work.
  • Revenue Concentration Risk: AI training companies face customer concentration with two players comprising over 50% of revenues. Invisible diversifies through enterprise expansion, securing 12 enterprise deals in 45 days while maintaining AI training business that was majority of 2024 revenue.

What It Covers

Matt Fitzpatrick, CEO of Invisible Technologies, explains why enterprise AI adoption lags despite exponential model improvements, the critical role of forward-deployed engineers, and how human data labeling remains essential over synthetic alternatives.

Key Questions Answered

  • Enterprise AI Gap: MIT reports only 5% of GenAI deployments work in enterprises, with Gartner predicting 40% of projects will be canceled by 2027. External builds prove 2x more effective than internal teams due to talent constraints and lack of disciplined ROI frameworks.
  • Forward-Deployed Engineers: Enterprise AI adoption requires forward-deployed engineering teams for customization and workflow integration. Invisible operates 450 people across eight offices, spending three months on customer implementations rather than charging for out-of-box software that fails without deep integration work.
  • Proof Before Payment: Invisible runs eight-week solution sprints at no cost to prove technology works before customers pay. This approach reduces sales costs while building trust, contrasting with traditional Accenture-style multi-year implementations that often fail to deliver working systems.
  • Human Data Superiority: Synthetic data works only for base truth tasks like math. Multi-step reasoning across 45 languages, multimodal contexts, and specialized domains requires PhD-level human feedback. Invisible manages 1.3 million experts annually, sourcing niche specialists within 24 hours for validation work.
  • Revenue Concentration Risk: AI training companies face customer concentration with two players comprising over 50% of revenues. Invisible diversifies through enterprise expansion, securing 12 enterprise deals in 45 days while maintaining AI training business that was majority of 2024 revenue.

Notable Moment

Fitzpatrick describes meeting an ecommerce retailer that spent $25 million building a returns agent, only to discover their custom evaluation tool measured speed and sentiment but missed when agents hallucinated $2 million refunds, forcing them to shut down and revert to deterministic flows.

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Episode Transcript

This is 20 VC with me, Harry Stebbings, and this is the last episode of twenty twenty five. Now if you're wondering why I sound like Mick Jagger, no. It is not because I have been partying like a maniac and lost my voice over the Christmas break. It's because I have been walking four marathons in four days with my mother to raise money for multiple cirrhosis sufferers. We've raised $50,000, in the last three days. I would love your support if you wanna donate to MS sufferers, but that is why I sound like Mick Jagger. But to the show today, and data is everything in the world of model performance. Turing, McCaw, and today's guest, Invisible, are one of a few who have reached several $100,000,000 in revenue. And as I said, I'm thrilled to be joined today by Matt Fitzpatrick, CEO of Invisible Technologies. Now since joining as CEO in January 2025, he's achieved some incredible milestones. Most significantly, he's raised over a $100,000,000 for the company. This was an incredible show recorded in person in London, and I cannot wait to hear your feedback. But before we dive into the show today, are you drowning in AI tools, ChatGPT for writing, Notion for docs, Gmail for email, Slack for comms, and you're constantly copy pasting between them all losing context and losing time. This is the AI productivity tax, and it's killing your output. At twenty VC, we're all about speed of execution, and Superhuman is the AI productivity suite that gives you superpowers everywhere you work. With the intelligence of Grammarly, mail, and coder built in, you can get things done faster and collaborate seamlessly. Finally, AI that works where you work, however you work. Superhuman gets you from day one with zero learning curve and it's personalized to sound like you at your best, not like everyone else using generic AI. Get AI that works where you work, unlock your superhuman potential. Learn more at superhuman.com/podcast. That's superhuman.com/podcast. And speaking of tools that give you an edge, that's exactly what Alpha Sense does for decision making. As an investor, I'm always on the lookout for tools that really transform how I work, tools that don't just save time but fundamentally change how I uncover insights. That's exactly what Alpha Sense does. With the acquisition of Tagus, AlphaSense is now the ultimate research platform built for professionals who need insights they can trust fast. I've used Tagus before for company deep dives right here on the podcast. It's been an incredible resource for expert insights. But now with AlphaSense leading the way, it combines those insights with premium content, top broker research, and cutting edge generative AI. The result, a platform that works like a supercharged junior analyst delivering trusted insights and analysis on demand. AlphaSense has completely reimagined fundamental research, helping you uncover opportunities from perspectives you didn't even know how they existed. It's faster, it's smarter, and it's built to give you …

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  • Matt Fitzpatrick, CEO of Invisible Technologies, explains why enterprise AI adoption lags despite exponential model improvements, the critical role of forward-deployed engineers, and how human data labeling remains essential over synthetic alternatives.

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