Insight
Positioning a business to a marketplace of acquirers has always first required turning focus inward and making an honest assessment of a business’s risks and opportunities. Most of the framework for the sources of these strengths and weaknesses is timeless: supplier concentration, customer concentration, threat of substitution, pricing power, key man risk—many of this representative sample of terms used to categorize common areas of investigation will be familiar to our readers. But almost overnight, an increasingly common element of this conversation considers the future effects of AI (colloquially referring to large language models and their uses), as both a source of risk and a source of opportunity.
For some businesses, the newfound disruption to company operations, business models, and competitive dynamics is staggering. New and old competitors are now able to provide the same service faster and cheaper. Sometimes the service is even higher quality than what the legacy offerings can provide. Barriers to entry in some industries have disappeared altogether.
Yet in other corners of the same organization, not much has changed. AI can’t hold a wrench, change out a part, read body language, or trust an old friend, nor is it likely to in the near future. Almost everyone we talk to can recognize places in their businesses that fit each of these profiles: some areas are changing rapidly (or are about to), and some areas seem fairly insulated from the commotion.
For business owners looking forward to the future and to an ultimate exit, the conversation typically ends with “I’d like to sell in the next five years. What should I do?”
We have written many times that value is in the eye of the beholder, and that a buyer’s perception of your business is what you will get paid for. If you believe AI is changing your industry, then likely so will the buyers. At the same time, there are limitations to new tool adoption, and not everything will change overnight. The key is to position the business over the next five years to be viewed as a “winner” (with some key assumptions about the new environment) rather than one who is going to be left behind. Let’s dive into how to diagnose which is which.
Demystifying AI: Let’s Define the Threat
It is important to remember that AI is an incredibly powerful tool, but it’s everybody’s incredibly powerful tool. AI tools allow for faster drafting, design, basic analysis, and research using publicly available information sources. But among competitors, these engines are like any other software; it’s all in how they are used (and what information is available for them to use).
It’s pretty impressive to ask Claude or Codex a detailed question and watch it compress three days of research into ten minutes. But there’s no magic in prompt writing; if my research time is cutting from days to minutes, so is everyone else’s. I shouldn’t expect my newfound time efficiency to drop to the bottom line, or at least not for long; for example, any professional services firm charging hourly for a process or service that is not truly unique is quickly going to experience strong pricing pressure.
The “not truly unique” in that last sentence is doing a lot of heavy lifting. How do we separate out what is unique and what is waiting to be commoditized?
What is Uniqueness?
A good way to think about “unique” is “difficult to acquire.” We’ll pick on ourselves for a moment: Zachary Scott has some unique data, structured as a private data set of 35 years of deal terms and outcomes that cannot be reproduced or reconstructed. It does not live in the public domain and cannot be searched or queried. The only way to acquire such a data set is to live it (the old-fashioned way) or through targeted M&A. This kind of data set is pretty unique; there are certainly other boutique investment banking firms with their own comparable data sets, but they are also unique, and the advent of more and more powerful AI tools can’t bring the private into the public to where it can be commoditized. The value of such a data set is dependent on its content and how we leverage its insights, but at least through an AI lens, it fits our definition of “unique.”
This is just one example, and the core takeaway is for any business to determine what component of its value chain is not easily reproduceable and to then own it. An accounting firm might see its lower-level bookkeeping services less important to value, while the CFO-level judgement and advice becomes more important. A law firm could see the drafting of boilerplate documents become a loss-leader, while the trust of a decades-long relationship and value alignment becomes irreplaceable.
In any acquisition assessment, buyers will pay a premium for revenue that sits in a defensible component of the value chain. For our illustrative business owner contemplating an eventual sale, it is important that this positioning can’t only start to occur in the year of a sale process. Buyers will judge the trend and not just the snapshot. Ensuring revenue is trending towards higher-value, AI resistant work over multiple years tells a more credible story than a last-minute pivot.
Turning AI Into an Asset
There might be business owners reading this article, coming to an uncomfortable conclusion that much of their business is squarely in the AI crosshairs. That doesn’t mean that the end is near; in a different light, it can be viewed as an opportunity. The compelling story for a buyer is a company that can turn the new technology into a source of advantage. Better exit opportunities will come to the owners who don’t resist the new wave of technology, but instead quickly adjust to lower their cost structure, expand capacity, and serve customers in a way their competitors have not yet figured out.
It is important to look like the company that thoroughly integrated the new technology (and can demonstrate the resulting margin improvements, quality gains, and capacity improvements) rather than the company that barely survived the changing dynamics. No business is completely commodifiable, and the first movers to uncovering true differentiation will be temporarily uncomfortable—but better to disintermediate yourself than for someone else to do it.
Magnifying Other Risks
Everything we have written over the years about preparing a business for sale still applies here and should be revisited. Enterprise value benefits to the extent future performance is predictable, and AI, in its rapid deployment, generally introduces a level of uncertainty that buyers will discount.
Think of the AI backdrop as a great magnifier: areas of risk become comparatively even riskier. For example, if a company has enjoyed an entrenched, stable, but heavy customer concentration with a single client, the barrier to that client one day bringing the work in-house with an AI-developed software tool just became meaningfully lower. In another scenario, businesses who are overly reliant on their owners are at greater risk when the owner’s relationships and judgement calls are what differentiate the company. Those truly unique assets could be walking out the door at closing and are a greater proportion of the company’s intrinsic value now than before.
Revisiting Timing
Returning to our illustrative business owner looking for an exit in the next few years, taking in all of the above may lead some to believe they are in the early innings of a long and difficult transition period in order to best position their businesses for a sale. That may not always be the case.
If there looks to be industry-wide competitive pressure mounting on the horizon, but the impact to margins has yet to manifest itself, there is still a window where this is more theory than practice. Going to market while the story is still a growth story, rather than a defense story, can benefit as buyers are still optimistic about the current trajectory.
In the process of self-evaluation, there may be a section or element of the business today that is more valuable to another party than it is to retain. For example, high growth AI startups may see value in a legacy book of business or unique data set in order to buy market share. If the business is worth more to someone else today than it is independently, it makes sense to explore that option immediately rather than contemplate a multi-year transformation.
Our intent is not to cause panic, but to instead provide a framework to demystify the effect that AI tools are having on today’s businesses and how they are valued. AI is not magic, but it is a powerful analytical tool that is rapidly changing some business processes and won’t change others for years (if ever). Understanding where the elements of a particular business sit between those two extremes and where value is generated is key to assessing the necessary next steps for remaining competitive and ultimately preparing to have an optimal set of recapitalization alternatives.