Part 3: The wrong funding structure can cost you 30% of your AI company, which you won’t notice until it’s too late.
Valuation is a substantial challenge for AI startup founders, particularly when the technology is evolving rapidly. Capital needs are urgent and significant when training AI systems.
Valuation is a substantial challenge for AI startup founders, particularly when the technology is evolving rapidly. Capital needs are urgent and significant when training AI systems. To address these challenges, founders and investors often use flexible funding structures, primarily convertible notes and direct equity, to balance speed, flexibility, and control[1][2][4].
Why is this Important for AI Startups
AI startups typically require significant capital before generating revenue, as funds are needed for model training, hiring, infrastructure, and data acquisition[3]. Traditional equity rounds can be slow and risky, particularly when a startup’s valuation is complex and difficult to determine early on. Convertible loan notes (CLNs) and Simple Agreements for Future Equity (SAFEs) are popular because they allow founders to raise capital without immediately setting a valuation or giving up too much equity[3][7].
Convertible Notes: The Fast Track
Convertible notes are short-term loans that convert into equity during a future priced round, such as the next major funding event[1][2][4][5]. Key features include:
Deferred valuation: The company’s value is set in the next round, not at the time of the note[1][2][4].
Discount or valuation cap: Investors receive a lower price per share when converting as a reward for early risk[1][4][5][8].
Maturity date: If no qualifying round occurs, the note may demand repayment or renegotiation. [1][4][5]
Interest: Some notes accrue interest (typically 5–8%), which also converts into equity[1][4][5].
Convertible notes can work well. However, multiple required investment rounds can result in significant dilution.
Direct Equity: Setting the Price Early
Equity rounds involve setting a fixed valuation and issuing shares immediately. This process provides a transparent ownership structure and more substantial investor commitment. Still, it is slower and riskier for pre-traction startups, as it requires more due diligence and legal documentation[6]. Founders often avoid priced rounds before achieving product-market fit or accumulating proprietary data. Still, equity becomes more strategic as the company matures[6].
Why Valuation Is Harder in AI
Raising capital for AI startups is uniquely challenging because:
Investor fatigue: Many similar AI pitches make differentiation difficult[3].
Data as a differentiator: Startups using open models and public APIs are judged more on go-to-market execution than technical novelty[3].
No clear benchmarks: Enterprise AI sales cycles are long, and consumer AI retention is uncertain, making it hard to define “traction”[3].
Founders should focus on demonstrating market demand, early usage, and a defensible data strategy rather than overselling technical capabilities[3].
Protecting Your Runway in the Term Sheet
Long-term risks are embedded in the term sheet regardless of the financing structure. Key clauses to watch include:
1. Conversion triggers: Ensure founder(s)./ control when notes convert, especially in bridge rounds[1][4].
2. Discount stacking: Limit cumulative discounts to avoid excessive dilution[2][4][5].
3. Valuation cap negotiations: A low cap can lead to significant dilution if the company’s value increases rapidly[1][4][5][8].
4. Redemption rights: Avoid clauses that could force repayment or liquidity events[1].
5. Warranties & founder liability: Clearly define what constitutes a forecast versus a binding promise, which can be ambiguous in AI[1].
Building a capital stack model to visualise different outcomes can help founders negotiate from a position of clarity.
-Adam Ryan
Final Thoughts
In AI, speed is essential, but so is survivability. Founders who treat financing as a strategic tool—not just a source of capital—are better positioned to build resilient businesses. The choice between convertible notes and equity should align with your company’s momentum, risk profile, and team strengths. Ultimately, your most significant leverage lies not just in your technology but in how you structure your business around it[1][2][4][5][7].
I hope you enjoyed this article.
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References and Further Reading
[1] Convertible Notes: Understanding the Debt and Equity Hybrid https://www.biztechlawyers.com/legal-articles/guide-to-convertible-notes
[2] Convertible Notes Explained: Should You Use Them for Funding https://nextround.ai/2024/12/09/convertible-notes-explained-should-you-use-them-for-funding/
[3] Day 9: Alternative Funding Strategies for AI Startups - LinkedIn https://www.linkedin.com/pulse/day-9-alternative-funding-strategies-ai-startups-more-olojede-zcn0f
[4] Convertible Notes: The Complete Guide for Startups - Cake Equity https://www.cakeequity.com/guides/convertible-notes
[5] https://breakingintowallstreet.com/kb/venture-capital/convertible-notes/
[6] Funding Strategies for AI Startups: Tips from the Pros - SkyNet AI https://skynetai.dev/blog/funding-strategies-for-ai-startups--tips-from-the-pros
[7] How Can Convertible Notes Help My Startup? - LegalVision https://legalvision.com.au/startup-lawyer-series-convertible-note-work/
[8] How Do Convertible Notes Work? - HelloData https://www.hellodata.ai/help-articles/how-do-convertible-notes-work
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