Is it Time to Take the AI Exit Window?

Artificial Intelligence (AI) is transforming industry. From healthcare, to financial services, to manufacturing, to retail, AI is being used to make better and faster decisions, improve efficiency, boost productivity, reduce costs, and improve customer experiences. AI is no longer an optional element of an organization’s operations. It is crucial for maintaining competitiveness. According to Bain & Company's Q1 2024 global survey, 87% of companies reported they were already developing, piloting, or had deployed generative AI in some capacity, reflecting widespread recognition of AI as a competitive imperative. 

AI is also a significant factor in tech M&A. Buyers are actively and aggressively looking for AI companies and are offering high valuations. Corum Senior Vice President Dr. Ivan Ruzic, an AI advocate and advisor, says that typically a legacy SaaS company may get a four- to-six times annual recurring revenue valuation premium from a buyer. But for companies that are AI-enabled, companies that embed AI into their products and operations, the premium goes up by about 50%. And for AI- native companies, companies that have AI as their core foundational technology, the premium doubles again. However, current market data shows significant variation depending on company profile, sector, retention metrics, and capital efficiency. Traditional performance metrics are still relevant.

But this M&A premium divide leads to a serious decision that some companies ‒ particularly those that are neither AI-enabled or AI-native ‒ need to make. And that question is whether to exit and take advantage of their current metrics, or pivot to AI and secure the higher valuation premium at a future time.

Most companies are not AI companies

Ruzic says that most companies today are not full-fledged AI companies. He notes that almost half of the companies are AI-adaptive. This means they're using AI tools internally in a tactical way. For example, these companies may use ChatGPT to create content or Claude to generate code. Ruzic considers this type of AI use essentially experimental. 

Based on Corum Group's deal flow and client advisory experience, approximately a third of companies are AI-ready. These are companies that have an infrastructure that is a good foundation for AI enablement, but they still don’t have AI-enabled products. 

By comparison, AI-enabled companies, which represent about 15% or 16% of companies, already have or are in the process of providing products that are AI-enabled. Ruzic says this level represents the first strategic use of AI. 

Only about 3% or 4% of companies are AI-native.  These are companies whose very essence is based on AI. Their products or services would not exist without AI. Ruzic stresses that it's really just  the AI-native and AI-enabled companies that are in a position to build what he terms a "competitive moat" that gives them the opportunity to maximize their valuation in the M&A market.

Factors to consider 

There are a number of factors to consider is deciding whether to exit or transition to becoming an AI company. Ruzic lists the following as primary considerations:

• Data readiness: To be effective, AI requires a sufficient amount of high quality, relevant data. The data needs to be "clean.” This means it must be accurate, relevant, properly governed, and searchable. A company needs to ask itself, “Do we have enough clean historical data for AI to be able to build a context that does what we want it to do?”
• Infrastructure and Integration:  Although AI can run locally, the reality is that a company requires a cloud-ready infrastructure to provide the needed computing power, data accessibility, and agility that AI requires. In addition, to become a sustainable AI company, especially one that integrates AI into enterprise workflows, a company needs to have robust APIs. Furthermore, the company's AI system needs to be scalable to manage increasing data volumes, complex model training, and high-volume user demands without performance degradation. A company needs to ask, “Are we cloud ready? Do we have the appropriately robust APIs? Is our system scalable?
• Talent and skills: AI talent and skills are crucial in transforming into an AI company. While technology provides the necessary tools for the transformation, having skilled people available to implement, manage, and scale those tools ultimately determines the success of that transformation. Ruzic points out that major technology companies, hyperscalers, and well-capitalized AI labs — including Google DeepMind, OpenAI, Microsoft, Meta, and Amazon — are intensely competing for AI talent, creating a widely documented scarcity of qualified machine learning engineers, data scientists, and AI researchers. He notes that securing that talent is becoming a major gaiting factor in whether a company is going to undertake this kind of transformation or not .
• Process & Culture: Successfully transforming to an AI company requires the right culture, one that is adaptable and willing to experiment. Ruzic points out that a transformation like this inevitably involves some experimentation. He says there is no predefined blueprint for how to go about transforming a company to make it a successful AI company. And because of that, a company needs to have a culture that can handle failures that may crop up along the way.
• Capital resources: Transforming a company to becoming an AI company requires significant capital resources. It’s a major reengineering effort that involves high upfront investments in technology and data infrastructure, as well as the acquisition of specialized talent. Ruzic says the transition may take a year-to-18 months. Does your company have the capital resources required for this effort?

How buyers view each AI stage

How buyers view a company and the premium they're willing to pay for that company depend on what stage the company is along the AI path. Based on his experience, Ruzic says that some companies at the AI-adaptive stage are actually starting to see valuation drops from 5%-to 15% because buyers understand that when they acquire a company like this, they're going to have to undertake a major effort to turn the company into an AI company. Typically, companies at this stage will not see a premium added to their valuation. Instead, it will be based on standard metrics. For instance, a SaaS company using off-the-shelf AI tools internally can expect valuations between three and five times Annual Recurring Revenue (ARR). And an IT services company at this stage can expect to see a valuation of 0.7-to-1.2 times revenue.

Companies that are AI-ready already have an infrastructure for AI enablement, although they don’t yet have AI-enabled products. Buyers see these companies as having "good bones" that make it easier to integrate AI into the company's products after acquisition. As a result, buyers are willing to pay a premium for these companies. For instance, a construction SaaS company at this stage can expect to see a valuation between four and six times ARR, while an IT services company at this stage can see valuations of 0.8-to-1.5 times revenue.

As AI is more fully integrated into a company's products and business model, the premium buyers are willing to pay goes up. Buyers realize that AI-enabled companies ‒ companies that already incorporate AI into their products ‒ present a competitive advantage, and so they're prepared to pay a higher premium to acquire those companies. For instance, an HR SaaS company that offers AI-based recruiting features can expect a valuation of between six and nine times ARR. While an AI-enabled IT services provider can see a valuation of between 1.5-to-2.5 times revenue.

Companies that are AI-native can expect to see the highest valuation premiums. Because AI is the foundation of these companies, with AI fundamentally built in to their products and services, buyers see these companies as having the potential of experiencing exponential growth. Buyers are willing to pay very high premiums for these companies, typically in the range of ten-to twenty times ARR. However, high-growth or infrastructure-layer AI-native companies may command significantly higher multiples — 25 to 50 times ARR and beyond — particularly when backed by proprietary data moats or foundational technology.

Exit or transition?

The decision whether to exit or transition to become an AI company is a function of risk. Ruzic sees that level of risk as an interplay of AI-readiness and investment levels. He advises that if a company has low AI-readiness and doesn't have the funds to transition to becoming an AI company, the smartest route is to exit now and take advantage of a higher return on investment (ROI) than the company can expect later.

If a company has a higher level of AI readiness, perhaps at the AI-ready stage, and has any investment level, from low-to-medium-to high, it should consider AI enabling their technology. They may even consider becoming AI native. However, Ruzic says there's a caveat. Companies are currently facing compressed product life cycles of about five-to-seven months. This means a company that decides to transition to the AI-enabled or AI-native stage needs to be aware of the risk of technology obsolescence. AI products that are in competitive markets can face a meaningful obsolescence risk within months-to-two years, depending on their specificity and how quickly foundation model providers absorb their core functionality. This is illustrated by early ChatGPT plugin developers being superseded by native model capabilities.

If a company is already at the AI-enabled or AI-native stage, Ruzic advises to consider exiting now and take advantage of the very high premiums buyers are willing to pay.

In any case, this is a leadership team decision. Ruzic advises, "You need to decide with clarity and with urgency. Do you exit now or do you look very carefully and track the market to make sure you have enough runway to undergo a full transformation? Right now you have an optimal window for an exit. In any case, Corum advisors are available to discuss this with you if you're interested in exploring it further."