What AI Adoption Is Doing to Private Company Valuations | Ted Wolf, Guidewise.ai

Is AI increasing your company’s value—or putting it at risk of falling behind?

In this episode of The Agent of Wealth Podcast, co-host John Williams is joined by Ted Wolf, CEO and Founder of Guidewise.ai and author of The Intelligent Business Equation. Ted shares why artificial intelligence is becoming a key driver of private company value, how business owners should approach AI implementation, and what buyers and investors will be looking for in the years ahead.

In this episode, you will learn:

Why AI adoption is quickly becoming a factor in private company valuations—and what happens if businesses fail to adapt.
The three foundational steps every business should take before implementing AI.
How AI can reduce operational risk, improve productivity, and make a business more attractive to buyers.
Why the future of work will depend as much on critical thinking and emotional intelligence as it does on technical skills.
And more!

Tune in for an insightful conversation on how business owners can use AI strategically—not just to improve efficiency today, but to build a more valuable, resilient, and future-ready company.

Resources:

Disclosure: The transcript below has been edited for clarity and content. It is not a direct transcription of the full episode, which can be listened to above.

Welcome back to The Agent of Wealth Podcast, this is your co-host John Williams.

Artificial intelligence is changing nearly every industry — but beyond productivity gains and automation, it’s also beginning to influence how private companies are valued.

Today, we’re joined by Ted Wolf, CEO and Founder of Guidewise.ai. Ted has built and led organizations from startup to hundreds of employees, and now helps businesses successfully implement AI by focusing not just on the technology, but on the people and processes that determine whether AI initiatives actually succeed.

In this episode, we’ll discuss how AI adoption is impacting private company valuations, why some businesses are becoming significantly more valuable while others risk falling behind, and what business owners should be doing today to prepare for the future…

Ted is also the author of a book he recently published, The Intelligent Business Equation.

Ted, welcome to the show.

Thank you very much, John. I’m looking forward to our conversation.

I’m really looking forward to today’s conversation because, as many of our listeners know, AI is everywhere. It’s changing how we think about nearly every aspect of our lives—from how we interact with others to how businesses operate.

When people think about AI, they often focus on the companies developing the technology. But the real value driver is going to be how businesses adopt AI to create value within their own organizations. I’m really excited to hear your perspective on that.

Before we get started, I want to mention that Bautis Financial is a wealth management and financial planning firm that’s currently accepting new clients. If you’d like to learn more about how we can help take the stress out of managing your money, you can schedule a complimentary call…

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With that, Ted, I’d love to start by learning a little more about your background. More specifically, how did you go from scaling businesses to founding Guidewise.ai?

Thanks, John.

When I graduated from college, I went to work for IBM. At the time, many midsize companies didn’t even have computers. We were at a major technology inflection point. Businesses that had been operating manually—what I’d call “analog businesses” today—were suddenly being introduced to computers.

People were scared. They wondered, “Am I going to lose my job? How am I going to learn all this new technology?” But we adapted, and most people didn’t lose their jobs.

Then, in 1999 and 2000, when the internet was taking off and the dot-com bubble burst, people thought the web was going to fail. But there were also companies that recognized the opportunity. They used the internet to build stronger businesses and communities around their brands, and they became incredibly successful because they stayed focused on the long-term opportunity instead of chasing quick wins.

What we’re seeing now with AI is another major technology inflection point—one that’s even bigger than anything we’ve experienced before.

While I was at IBM, my brother and I knew technology was going to continue reshaping business, so we left and started our own company with a combined investment of just $1,000. We knocked on a lot of doors and built a technology consulting and staffing firm that eventually grew to 650 billable employees across 13 offices nationwide.

Ultimately, the company was acquired by a billion-dollar organization, and I learned a tremendous amount from that experience.

The biggest lesson was that I didn’t prepare the business for an exit early enough. Like many business owners, I assumed that because we had a great company—with strong cash flow and healthy profits—buyers would naturally line up. What I didn’t realize was that only about 30% of businesses that want to be acquired actually get acquired.

The lesson for me was that technology is your friend, not your enemy. If you embrace it, learn it, and implement it thoughtfully, it can dramatically increase your business’s productivity.

At the same time, you have to remain people-focused. Personally, I don’t believe AI is going to eliminate most jobs. It may reduce the need for certain coding roles in the near term, but overall, I think it’s going to help people become more competent and more confident in the work they do.

To give our listeners a little more context, could you explain what Guidewise.ai does?

It sounds like you’re helping businesses understand and implement AI, but you’re also helping them prepare for an eventual sale. Are those separate businesses, or are they really part of the same process?

They’re actually the same thing—and that’s a great question, John.

When a business owner starts preparing for an exit, the first question is usually, “Why do I want to sell?” In many cases, it’s because most of their wealth is tied up in the business. The only way to unlock that value is through an exit.

What I’ve realized is that preparing a business for sale and preparing it for AI have now become the same journey.

Today, if your business doesn’t have a solid AI strategy and implementation plan, it’s going to be much harder to sell. And if AI is implemented poorly, that can actually reduce the business’s value because buyers won’t see a well-structured, transferable operation.

That’s one of the reasons I wrote my book.

Our firm helps businesses prepare for an exit using what I call the “Five Closes” framework. At the same time, we help them implement AI in practical ways that improve operations, increase transferability, and create what I call “optionality”—the financial flexibility to pursue new opportunities and weather future challenges.

Guidewise helps businesses become more valuable, more efficient, and more attractive to buyers by combining exit planning with AI implementation. Today, those are no longer separate paths—they’re one journey leading to the same outcome.

In short, we help companies finish what they start. Most companies struggle to do that.

There are a lot of successful businesses that simply aren’t sellable businesses, for any number of reasons.

And for many owners, this isn’t about selling next year. Preparing a company for sale can be a long-term process, especially if significant operational changes are needed.

When you work with a business, what timeline do you typically recommend? I imagine it’s never too early to start planning, but is there a sweet spot?

I recommend starting at least three years before you think you’ll want to sell.

The reason is that you need time to strengthen your EBITDA, clean up your financials, and demonstrate consistent operating performance. Buyers want to see that the business isn’t dependent on any one individual—that it’s driven by systems and processes.

You also need to show reliable financial results over a period of time. Then there’s the question of capital allocation: Do you invest more in capital expenditures and improvements, or do you maximize profits to improve your EBITDA and valuation multiple?

Three years gives you enough time to make those decisions strategically.

The same applies to AI. You can’t implement AI over six months, claim it’s transformed the business, and expect buyers to place a premium on that. Acquirers want to see proven results.

Today’s due diligence process moves much faster than it used to. Buyers can quickly review your data room, conduct a quality-of-earnings analysis, and evaluate your operations.

That means you need to be able to demonstrate not only that you’ve implemented AI, but also how it’s improved the business—and that you have the systems and processes in place to make the company transferable to its next owner.

Yeah, and it’s all happening so quickly. Many people remember what it felt like during the dot-com bubble. At the time, no one really realized we were in a bubble until things got out of hand and it burst. There’s a similar fear surrounding AI today. Obviously, there are fundamental differences, but there’s also a tremendous amount of pressure.

Even as a money manager analyzing this space, it sometimes feels like the cart is before the horse. We have this incredible technology, and in some cases it feels like it’s being forced on businesses with the message, “If you don’t implement AI, you’re going to get left behind.”

I’m even hearing CEOs of large public companies talk about the pressure to “do something with AI.”

In your opinion, are most businesses approaching AI the right way? And if not, what are some high-level principles business owners should be thinking about as they begin implementing AI?

John, your instincts are right. In many cases, people do have the cart before the horse.

Is there pressure to implement AI? Absolutely. If you don’t start now, you will fall behind because we’re living through a unique moment in business history. For the first time, small companies have an opportunity to leapfrog much larger competitors that are slow to adopt AI.

But implementing AI doesn’t mean using it to write better emails or create PowerPoint presentations faster. Those things may improve individual productivity, but they don’t have a meaningful impact on the bottom line. That’s not what makes a business more valuable to a buyer. In my view, that’s just the tip of the iceberg when it comes to AI.

So are most businesses implementing it correctly? From what I’ve seen, no.

Many organizations deploy individual tools like ChatGPT or Claude without an enterprise-wide strategy. They’re asking, “How can this help me be more productive?” on an individual basis rather than asking how AI can improve the business as a whole.

We all know silos don’t create innovation. They don’t drive productivity or long-term growth. You need cross-functional collaboration, and AI can actually help eliminate silos by breaking down tribal knowledge and disconnected information across the organization.

If you approach AI one user or one department at a time, you’re probably not going to see the results you’re hoping for.

I think about AI implementation in three layers.

First, you need documented workflows—and I don’t mean Excel spreadsheets. You need clearly defined business processes.

Second, your data has to be organized, consistent, and reliable so AI can interpret it accurately without making assumptions or introducing errors.

Third, you begin deploying AI agents. At that point, you’re thinking at the enterprise level. You’re orchestrating an AI workforce.

Initially, those agents may perform simple tasks that people used to handle manually. Over time, they can begin making recommendations and, if appropriately designed, even certain decisions. Just like an organization has different levels of employees and managers, your AI agents will eventually have different roles and responsibilities.

You have to orchestrate them the same way a conductor leads an orchestra.

So AI isn’t about experimenting with a single department or isolated use cases. It needs to support business objectives that improve the bottom line.

That means:

Your AI initiatives should be grounded in clear business goals.
You should be using enterprise-level technologies that support the entire organization, not just one function.
And most importantly, your people need to understand and adopt the technology. That requires training, change management, and helping employees understand why AI matters and how it benefits them.

If you implement an ERP system today, your odds of success are only about 30%. Unfortunately, that’s been true for decades with major organizational change initiatives.

So yes, I think many companies are approaching AI the wrong way.

That said, AI isn’t going away. Just like the internet in the late ’90s, some companies will jump in without a strategy and fail. Others will approach it thoughtfully, follow a structured process, and come out much stronger.

That’s one reason we named our company Guidewise. Businesses need guidance through this process. If they approach AI methodically and strategically, they’ll build much more intelligent organizations.

As I listen to you describe this, one thing that stands out to me is the amount of risk involved—especially for midsize businesses.

Essentially, you’re asking companies to invest in understanding how AI fits into their business before they even know what the return will be. This is unprecedented. There’s no playbook.

A company might spend significant time and money exploring AI, decide to move forward, implement it, and then discover the benefits don’t justify the investment.

For a large S&P 500 company, that’s one thing. They have the resources to absorb those costs. But for a midsize business, every investment matters.

How should those business owners think about making that decision?

I think that’s a very fair question.

A lot of companies are taking a risky approach to AI, and that can absolutely hurt the business and the workforce.

Ironically, though, if you implement AI correctly, you’re actually reducing risk.

The first risk is doing nothing. If you don’t embrace AI, one of your competitors will, and I believe you’ll start seeing smaller companies make dramatic gains over the next three to four years because they’re using AI effectively.

The second key is making sure every AI initiative is tied directly to a business objective that impacts the bottom line.

Every project should have a business case, a defined use case, and a measurable return on investment. Once you do that, you’re already reducing much of the uncertainty.

At Guidewise, we run what we call an AI Bootcamp. It’s typically a 12- to 16-week engagement where we evaluate the business and develop practical AI use cases in a low-risk environment. Companies aren’t making massive investments upfront. They’re learning where AI can create value before committing significant resources.

I’ve spent my career working with midsize businesses—from $20 million to $500 million in revenue. They have to manage risk carefully.

Done properly, AI reduces competitive risk. It helps businesses scale more effectively, but you also have to bring your people along. As the business grows, you still need people managing that growth. AI isn’t going to run the company by itself anytime soon.

So if you implement AI poorly, you’re increasing risk.

If you implement it strategically, you’re making your business more intelligent.

Intelligence by itself doesn’t create value. But if you apply that intelligence strategically—around clear business objectives with measurable ROI that you’re tracking every month—you gain control over your risk instead of increasing it.

I think that’s exactly the right question business owners should be asking.

Should I move now? Should I wait? What’s this going to cost? Will it be worth it?

Those are all valid concerns, and they can all be answered through a structured implementation process.

The technology exists today, and honestly, it’s not as expensive as many people assume. Costs continue to come down, token usage can be managed effectively, and enterprise platforms—such as IBM’s watsonx, which we prefer—can be implemented at a relatively modest cost.

When managed properly, AI can lower risk, increase productivity, and improve your bottom line.

So how does your process work? I’ll use marketing as an example because, from my own experience, there are so many different directions you can go. You can spend a lot of money on the latest marketing idea or have a company come to you and say, “We can do X, Y, and Z, and we’ll grow your business.” Sometimes, even sitting down to have that initial conversation is expensive.

For the business owners listening who may just want to dip their toe into AI and better understand what’s possible, what does that process look like? And what should they expect from a cost perspective?

First, anyone can contact me, and I’m happy to have a conversation about their business or answer any questions they have. There’s no charge for that.

More importantly, I encourage people to ease into AI. Learn what it is. Attend a workshop. We offer workshops that combine AI implementation with business exit planning, which is also the foundation of my book. We walk through what we call the “Five Closes”—or five principles—that business owners need to implement to prepare for the future.

From there, we offer our AI Bootcamp. It’s an affordable way to evaluate a business, identify opportunities, and determine where AI can create the greatest impact.

In my opinion, one of the biggest opportunities for any company is improving how it manages projects. Everything in business is a project.

Hitting a monthly sales quota is a project. Managing resources is a project. Running a manufacturing operation is a project. Construction projects are projects. Software development is a project.

Projects are at the heart of how a business operates.

Whether you’re following Six Sigma or another methodology, every project should have a clear start date, end date, milestones, and measurable objectives. You need to know where you’re headed and what the key milestones are along the way.

That’s also one of the best places to begin with AI.

Ask yourself: How am I running my business? Where are the bottlenecks?

Define the challenge as a project. Assemble a small team. Develop a use case. Understand the expected return on investment and how it will impact the bottom line.

Once you’ve had success with one project, you can replicate that process throughout the organization.

It’s a very low-cost, low-risk way to begin implementing AI—and to do it the right way.

I’d like to shift gears and talk about business valuations.

We’re already seeing investors assign significant value to AI capabilities in public companies. Private markets are obviously different because there’s less publicly available data, but what are you seeing?

As we’re still in the early stages of the AI boom, how is AI affecting private company valuations, and what factors are buyers paying attention to?

First, if you’re applying for an SBA loan, I’m told lenders are increasingly going to expect you to demonstrate an AI strategy—not just talk about AI, but show how you’re using it and how it’s improving your business.

I think commercial lenders will follow the same path.

They’re going to want to know what you’re doing with AI because history has shown us what happens when industries fail to adapt. Just look at what the internet did to the newspaper business.

When it comes to valuations, imagine two companies.

One is a well-run business with good people and healthy margins. Then a competitor adopts AI effectively and suddenly operates much more efficiently, allowing it to compete aggressively on price.

That’s what I call an intelligent business.

An intelligent business compounds what it learns by combining technology with human expertise.

If I can show that AI agents are improving productivity—and that the cost of building those agents generates an ongoing return—that creates a compounding effect. The business develops what I call an intelligence flywheel.

When buyers evaluate a company, they’re going to ask several questions.

First, what’s the EBITDA?

Second, is the business systems-dependent or people-dependent? Businesses that rely on documented systems are more valuable than businesses that rely on tribal knowledge.

Third, have you layered AI into those systems?

If you’ve eliminated tribal knowledge and reduced dependence on individual “heroes” who save the day every month, you’ve made the business much more transferable.

If one key employee leaves and the business falls apart, you’ve immediately lost value.

Once you’ve documented your workflows, organized your data, and implemented AI successfully, you’ve fundamentally changed the business.

You’re no longer just selling products or services. You’re selling intelligence.

Now you’re making decisions based on insights you never had before. You’re identifying patterns, spotting opportunities, and solving problems much faster—and I’m talking about midsize businesses, not Fortune 500 companies.

Technology that was once available only to the largest organizations is now accessible to companies generating $20 million or $50 million in revenue.

That changes everything.

If my brother and I started our business today, I believe we could build what took us 18 years in roughly half the time because AI dramatically increases productivity.

That increased productivity translates directly into a higher valuation multiple.

Finally, you still need strong people.

As AI removes many of the day-to-day fires—missed orders, supply chain surprises, communication breakdowns—your team has more time to focus on growth instead of constantly reacting to problems.

Those are the five principles I discuss in The Intelligent Business Equation, and together they can significantly increase the value of a business.

For example, let’s say a company has $1 million in EBITDA but relies heavily on people rather than systems and isn’t using AI. Maybe it sells for a 3x multiple, giving it a $3 million valuation.

Now imagine that same business improves its data, documents its workflows, implements AI correctly, and significantly increases productivity. Perhaps now it earns a 5x multiple. That’s a $5 million valuation.

The investment didn’t cost $2 million, but it created $2 million in additional enterprise value.

I’ll take that return every day.

That’s how AI is impacting the valuations of midsize businesses today. Generally, I’m talking about companies between $10 million and $500 million in revenue, with the sweet spot being roughly $20 million to $100 million.

That’s interesting.

You mentioned human capital earlier, and it reminded me of a T-shirt I saw recently. As a Philadelphia sports fan, I thought it was hilarious.

It said, “AI is coming for your job,” with a picture of Allen Iverson.

That’s really good. I’m a Philly sports fan myself, so I appreciate that.

Really? I love that. Then we’ll get along just fine.

But it does speak to a very real concern.

People worry that AI is going to replace jobs, much like people feared automation and robots years ago.

I’ve also heard the opposite argument from prominent CEOs who believe AI will actually increase hiring in many areas.

As the father of four boys—all nine years old or younger—I sometimes wonder what the world will look like for them.

Just a few years ago, everyone was telling kids to learn to code because they’d be set for life. Now that conversation has changed dramatically.

What are your thoughts? How should people think about AI’s impact on jobs?

I think you’re accurately describing what many people are feeling.

But let’s look at it differently.

If AI helps me become better at my job, and I help make the AI better over time, what happens?

First, many of the daily fires begin to disappear.

Instead of spending the day reacting to problems, people have time to think.

That’s incredibly valuable.

Without constant emergencies, people can focus on improving their work rather than simply surviving it.

AI also reduces tribal knowledge and eliminates situations where every department has different numbers or different versions of the truth.

That’s a risky way to run a business.

As those problems disappear, people have more time to think critically and develop emotional intelligence.

For your children, I’d say the opportunities ahead are incredible.

They should absolutely learn AI, but they should also learn how businesses work.

They need to understand systems, how technology and people work together, and how to solve problems.

That’s ultimately what capitalism rewards—solving problems that people are willing to pay to have solved.

As repetitive work declines, critical thinking becomes even more valuable. So does emotional intelligence.

Innovation happens when people have time to think.

If you have a crisis without critical thinking, you get catastrophe.

If you have critical thinking without emotional intelligence, you make decisions that benefit only yourself instead of everyone involved.

We need both.

Think back to the quality movement of the 1980s and 1990s—Deming, Juran, Six Sigma. Businesses improved because they improved their people and their processes. Then COVID arrived, and almost overnight everyone learned a new technology: Zoom. We adapted much faster than anyone expected.

AI will be similar. We’ll need to teach people how to process change because the pace of change is only increasing.

People experience change in three major areas: work, personal life, and health. The better we become at managing change, the better we’ll perform.

As AI removes the constant distractions, people gain time to think critically, develop stronger interpersonal skills, and create more innovative organizations. I honestly believe your children have extraordinary opportunities ahead of them. Knowing what I know today, I’d love to be starting my career again.

I actually agree with you. I think the opportunities are tremendous.

What feels different today is that there’s less room for error. Choosing the wrong educational path or career direction seems riskier because technology is evolving so quickly.

I think we’re actually going to see a return to a broader, liberal arts-style education. For years, businesses focused heavily on financial engineering, operational improvements, and digital transformation. There’s only so much value left to extract from those areas.

Now AI creates a new opportunity—but only if people have time to think. As AI eliminates repetitive work, people can focus on solving problems. That’s really what a liberal arts education teaches.

You’ll make mistakes. You’ll encounter obstacles. The important skill is learning how to identify the root cause and solve those problems.

Methods like the Five Whys and fishbone diagrams have existed for years.

Now AI can help us apply those methods much more effectively.

In many ways, I think we’re entering a second Renaissance.

We’ll continue developing ourselves alongside the technology instead of competing against it.

Throughout my career, I’ve never met someone who couldn’t become a better critical thinker or develop greater emotional intelligence when given the right guidance.

Those are exactly the skills we’ll need to work alongside AI, build better businesses, and create greater prosperity for everyone.

I’m genuinely excited about where we’re headed.

This has been a fascinating conversation. I feel like we should have you back in three years so we can compare notes and see how much of this came true.

AI is already changing much more than day-to-day operations. It’s changing how businesses are evaluated, bought, and sold.

Ted, thank you for helping us separate the hype from the real opportunities.

For listeners who’d like to learn more about Guidewise.ai, your book, or your work, where’s the best place to find you?

You can visit our website at guidewise.ai.

You can also email me at [email protected], connect with me on LinkedIn—just search for Ted Wolf—or check out my book, The Intelligent Business Equation, which is available on Amazon in Kindle format.

John, thank you for having me. I really enjoyed the conversation.

Great, we will include all of that information in the resources section of the show notes. Thanks again, Ted. And thank you to everyone who tuned into today’s episode – until next time.

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Episode 302 – What AI Adoption Is Doing to Private Company Valuations With Ted Wolf