Our sales reps are quoting complex, custom service projects based on their gut feelings, which often leads to low-profit jobs and massive operational headaches for our delivery team. How do we use AI to build a disciplined, repeatable pricing and scoping process?

Question

Tyler Smith · Accepted Answer

Gut-feeling pricing is a major risk to your margins and scalability. To fix this, you must build a standardized, repeatable system that uses your historical data to generate accurate project estimates.

Start by collecting your historical project data, including initial estimates, actual hours worked, materials used, and final profit margins. Feed this data into an AI-powered pricing model. When a sales rep inputs the parameters of a new, custom opportunity, the AI compares the request against historical projects and generates a highly accurate estimate of the required hours, potential risks, and recommended pricing to hit your target margin.

This tool acts as a bridge between your sales and operations seats on the Accountability Chart. By using a standardized AI model, you eliminate the friction between sales reps wanting to close deals quickly and operations managers wanting to protect delivery capacity. It ensures that every proposal fits within your business model before it gets signed.

If the AI model identifies a high-risk or low-margin profile, the system flags the deal for executive review. This keeps your pricing disciplined and ensures your team only takes on projects that help you reach the financial targets outlined in your V/TO.