Artificial intelligence has become impossible to ignore in business conversations. For owners, executives, and investors in privately held companies, however, the debate around AI often leads to the same question: Is this real, measurable, and economically meaningful, or just another wave of tech hype?
That question misses what matters most. The real issue is not whether AI will “change everything,” but whether it can improve EBITDA and business value. Increasingly, the answer for privately held companies is yes, and the companies acting on it now are creating a widening gap between themselves and competitors who are standing still.
The AI Conversation Has Matured, But the Stakes Are Higher
For years, AI lived safely in the realm of experimentation: proofs of concept, innovation committees, and vendor demos. Today, that phase is ending. AI has rapidly shifted from novelty to operational leverage.
Many business leaders are already using AI in some form, often embedded in software platforms, analytics tools, or automation workflows. What’s changing is how directly AI is touching labor, decision‑making, and execution. Even modest improvements in efficiency, pricing discipline, or throughput can flow directly to the bottom line. In an M&A context, that matters. Increases in EBITDA (especially when they are durable and repeatable) compound into higher enterprise value.
EBITDA, Not Abstraction, Is the Right Lens
Much of the public debate about AI focuses on whether it will disrupt the entire economy or eliminate broad categories of jobs. That framing is interesting, but it’s not especially useful for business owners. The more practical question is this: Can AI improve operating performance inside a real company with real constraints?
When viewed through that lens, the opportunities become clearer:
- Labor leverage: AI tools increasingly augment or replace routine cognitive work in finance, sales support, customer service, marketing, and reporting.
- Speed of execution: Faster analysis and decision cycles reduce friction and improve responsiveness.
- Consistency and accuracy: Automated workflows reduce rework, errors, and hidden operational costs.
None of these require a science‑fiction leap; they require intentional deployment.
The Competitive Gap Is Opening Quietly
One of the most important insights for owners and boards is that AI-driven margin improvement doesn’t arrive all at once. It compounds quietly. Two otherwise similar companies can look identical today. Over the next 24–36 months, the one that embeds AI into core workflows may:
- Require fewer incremental hires to grow
- Maintain cleaner, more actionable data
- Respond faster to customers and market shifts
- Produce more predictable financial performance
If you wait until you’re already in a sale process to consider how AI could improve your bottom line, it’s likely too late to “catch up” and realize value from AI. From a buyer’s perspective, operational sophistication increasingly signals scalability and risk reduction. AI-enabled processes are becoming part of that evaluation, whether explicitly discussed or not.
Not Using AI Is Becoming a Strategic Decision, Whether You Intend It or Not
Choosing not to engage with AI is no longer a neutral stance. It is, implicitly, a choice to let competitors experiment first, learn faster, and refine processes while you wait. That doesn’t mean every company needs a sweeping overhaul of the business based on AI. In fact, the highest returns often come from narrow, well-chosen use cases that:
- Reduce manual effort in finance or operations
- Improve pricing, forecasting, or demand planning
- Streamline customer-facing processes
- Remove bottlenecks in reporting and analysis
The risk is not moving too fast, but of discovering in due diligence that peers have already built these advantages into their EBITDA.
What This Means for Owners Considering a Transaction
For owners thinking about a future sale, AI should be viewed through the same lens as any other operational initiative: Does it improve earnings quality and sustainability? Companies that can demonstrate:
- Clear operational leverage
- Documented efficiency gains
- Scalable, repeatable processes
tend to command stronger buyer interest and withstand scrutiny more effectively.
For business owners evaluating a future transaction, these operational improvements tie directly into broader deal considerations including how value is structured and realized at closing. For more on that topic, see our prior article “Letter of Intent Negotiation: Payment Terms That Matter and Which Are Negotiable”. AI readiness is increasingly becoming part of that preparation.
The Bottom Line
The AI debate is no longer theoretical. The companies that treat AI as an EBITDA lever, rather than a curiosity, are positioning themselves ahead of the curve. If your competitors are using AI to expand margins and accelerate execution, staying on the sidelines means falling behind, even if the impact isn’t obvious yet.
If you’d like to discuss how operational improvement, technology adoption, and EBITDA positioning affect transaction outcomes, contact us today.