AI in Your Product = 130% Higher Valuation. Here's Why.

Does using AI internally actually increase what your business is worth?

Not as much as you think. A business using AI to write emails, summarize meetings, or speed up operations is more efficient, sure. But new data reported by Forbes puts a hard number on the difference: companies that build AI into their products or services are priced at a 130% premium over those that only use AI internally. That is not a rounding error. That is the difference between a 3x and a 7x multiple on your exit.

This is the frame that should be running every AI conversation you have in 2025 and into 2026.

What does "AI in the product" actually mean for a small business?

For a software company, this is obvious: your product does something with AI that it could not do before. But most SMBs are not software companies, and the concept still applies.

Consider a marketing agency that builds a proprietary AI reporting layer its clients log into every week. Or an accounting firm that delivers an AI-generated cash flow forecast as part of every monthly close. Or a home services company that uses an AI dispatch and scheduling tool it licenses to other operators in its region. In each case, the AI is not just making internal work faster. It is part of the delivered value. Clients can see it, touch it, and would notice if it disappeared.

That is the test: if you removed the AI component, would your clients notice and complain? If yes, you have AI in the product. If no, you have AI in the workflow, which is good but not the same thing.

What were the five biggest AI stories from June 2025?

The Forbes piece by Jodie Cook covers June's major AI developments in context. Here is what matters operationally for SMB owners:

1. Valuation data is starting to quantify the AI premium. The 130% figure is the headline, and it is backed by acquisition and funding data. Buyers are paying dramatically more for businesses where AI is a defensible, customer-facing capability rather than a back-office tool anyone could replicate.

2. Agentic AI is moving from demo to deployment. Agents that take multi-step actions autonomously (think: researching a lead, drafting an outreach, scheduling a call, logging the result) are being used in production at small businesses now, not just at enterprise. The cost and complexity of building these has dropped significantly in the past 12 months.

3. AI is compressing specialist labor costs. Tasks that required a specialist contractor 18 months ago (basic legal drafting, financial modeling, market research, ad creative) are being handled in-house with AI by teams that have no prior background in those disciplines. The businesses doing this well are reinvesting the savings into product and growth.

4. AI literacy is becoming a hiring filter. Business owners are reporting that candidates who cannot demonstrate basic AI fluency are being passed over, even for non-technical roles. This is accelerating fast.

5. The compliance and governance gap is widening. As AI use scales, the businesses without any policy or governance structure are accumulating risk they do not see yet. Data handling, output review, and liability exposure are real concerns that most SMBs have not addressed.

How do you move from "AI in the workflow" to "AI in the product"?

This shift does not require a software engineering team. It requires a clear decision and a structured build process. Here is a simple way to think about the progression:

| Stage | What it looks like | Valuation impact | |---|---|---| | No AI | Manual processes throughout | Baseline | | AI in workflow | Internal tools, ChatGPT, automation | Modest efficiency gain | | AI in delivery | AI improves what clients receive, but invisibly | Some premium | | AI in product | AI is a named, visible, client-facing capability | 130%+ premium |

Most SMBs reading this are at stage 2 or early stage 3. The move to stage 4 is not as far as it looks, but it requires intentional design rather than just stacking more tools.

The question to ask your leadership team: what AI capability, if we productized it and put it in front of clients, would make us meaningfully harder to replace?

Does this only matter if you're planning to sell?

No. The valuation premium is a useful proxy for something more fundamental: defensibility. A business where AI is embedded in the client experience is harder to compete against, harder to commoditize, and more likely to retain clients through pricing pressure. The 130% exit premium is a symptom of those advantages, not the only reason to pursue this.

For business owners with no exit plans in the next five years, the more immediate benefit is margin. When AI is part of what you deliver, you can charge for it. When it is only in your back office, you capture it as cost savings but cannot price for it directly.

The businesses getting the most out of AI right now are not the ones using the most tools. They are the ones who decided what they were building and built it deliberately.

What we'd actually do

• Audit your current AI use and categorize it honestly. List every AI tool or workflow your business uses. Mark each one: is this internal only, or does it touch client deliverables? If everything is internal, you have your answer on where to focus.
• Identify one client-facing AI capability to build in the next 90 days. It does not have to be technically complex. A branded AI report, an AI-powered client dashboard, or an AI-assisted deliverable your clients interact with directly all qualify. Pick one and spec it out.
• Join the conversation at skool.com/aiforbusiness where SMB operators are working through exactly this kind of strategic build, with people who have done it across multiple industries.