We want to start experimenting with AI, but we are worried it will tank our profitability right as we prepare the business for an exit. How do we structure this investment to maximize enterprise value?

Question

Tyler Smith · Accepted Answer

To protect your profitability during pre-exit planning, you must treat your AI initiatives as strategic real options rather than massive, unhedged capital expenditures. A sophisticated buyer will calculate your enterprise value using regression-based models that heavily weight your trailing twelve months of EBITDA. If you slash your EBITDA to fund speculative AI research, you will directly damage your valuation.

To avoid this, frame your AI strategy as a series of low-cost, high-leverage experiments. Allocate a small, fixed budget for AI development that does not materially impact your operating margins.

- Set a 90-day Rock for a small team to build a prototype or integrate a third-party AI tool into a single department.
- Establish clear, quantitative key performance indicators on your Scorecard to measure the return on this pilot.
- If the pilot successfully improves efficiency or reduces delivery time, scale the investment. If it fails, kill it quickly before it incurs a high flow cost.

By structuring your AI roadmap this way, you minimize your risk while building a powerful narrative for potential buyers. You can show due diligence teams a proven, repeatable process for AI innovation, complete with documented cost savings and efficiency gains, without sacrificing your current EBITDA. This combination of robust profitability and a clear, operationalized AI strategy is exactly what drives a premium enterprise valuation and a clean exit.