We have built custom AI agents that have cut our service delivery times in half, but the buyer's valuation model only values our historical EBITDA. How do we structure the deal to get paid for our future operating leverage and the scalability of our technology today?

Question

Tyler Smith · Accepted Answer

Traditional valuation models look backward at historical EBITDA, which often fails to capture the true value of your custom AI-driven operating leverage. If your systems allow you to scale capacity without hiring more employees, you must force the buyer to value this efficiency.

First, present the buyer with a unit economics model rather than just standard financial statements. Show them your customer acquisition cost, your delivery cost per client, and how your custom AI tools have steadily driven down your cost of goods sold over the last twelve months. This proves that your future margins will be significantly higher than your historical averages.

Second, map your automated workflows directly to your EOS Accountability Chart. Show the buyer how specific seats have been fully or partially automated, allowing your existing leadership team and staff to manage twice the volume of business with zero additional headcount.

Third, document your AI infrastructure as proprietary intellectual property. This transforms your business from a simple services firm into a technology-enabled platform.

My recommendation is to structure a portion of your purchase price as a high-yield performance payment or a structured earnout that triggers once your AI-driven margins hit specific scale milestones. By backing your operational claims with a performance-linked deal structure, you force the buyer to pay for the future capacity you have already built today.