Beyond the hype: AI's quiet payoff in 'boring' businesses

The opportunity

Most of the AI conversation in markets centres on the builders: chipmakers, hyperscalers and model developers, and the valuations that come with them. We think an often-overlooked opportunity for private markets investors sits one step removed. It lies in established, cash-generative businesses that use AI to do what they already do, at lower cost and with higher quality, while retaining pricing power and improving their margins.

This shapes how we build the private equity component of the WAM Alternative Assets (ASX: WMA) portfolio. Our team has previously written about how we deliberately favour resilient, ‘boring’ businesses that are not exposed to significant technology displacement. For these companies, the risk of AI replicating their product or service is low, but there are significant opportunities to use AI to drive efficiencies in their processes.

The businesses where AI drives improvements tend to share four traits:

• They carry high volumes of repetitive, rules-based work;
• A skilled workforce's time is the binding constraint on growth;
• Their data is structured and already digitised; and
• A regulatory requirement or professional standard requires a human to own the final judgement.

That last trait is important, and one we focus on when thinking about a business's moat. Where a qualified person must sign off, AI rarely replaces the role. Instead, it expands how much each person can do.

The founder-led, lower-mid-market businesses I wrote about recently are often furthest behind in implementing these efficiencies. That is exactly why the uplift under private equity ownership can be significant.

What does this look like? ASF Audits

Every SMSF must be audited each year by an independent approved auditor. It is a large, recurring, regulated workload, and fees are competitive. The question that matters most for businesses in this field is how auditors can efficiently complete an audit to a high standard.

ASF Audits, backed by Fortitude Investment Partners, has more than 130 specialist auditors reviewing over 59,000 SMSFs a year. Its in-house platform, HubX, connects with BGL 360, SuperMate and Class with one click to transfer fund data automatically, and uses its proprietary technology and AI so that auditors can focus less on data handling and more on judgement and client relationships.

Two points are crucial when it comes to our conviction in the opportunity for ASF Audits. First, the approved auditor still forms and signs the opinion; the system runs the process, and a qualified person makes the judgments, ensuring quality is protected. Second, ASF’s in-house platform capability strengthens the consolidation strategy. In a fragmented market, each smaller practice ASF acquires can be moved onto HubX and quickly began operating under the upgraded, best in market processes implemented by Fortitude and the ASF team. That makes every bolt-on more profitable than it was as a standalone business.

Where else we see these traits

Audit is one example, but the same four traits show up across many everyday industries. A few areas where we see the opportunity most clearly:

• Fire and building safety - Buildings must be inspected and certified on a regular schedule. AI can draft inspection reports from a technician's notes and photos, while a licensed technician still signs off on compliance. AI can help optimise routes, enabling technicians to see more workplaces in a given day thereby increasing revenue.
• Insurance broking - Brokers spend much of their day comparing policies and processing renewals and claims paperwork. AI can do that first pass, leaving the licensed broker to advise the client.

• Medical and allied health clinics - Clinicians spend a lot of time writing consultation notes and referral letters. AI can draft these from the consultation for the clinician to review and approve, freeing up more time for patients. AI can also be used to make booking systems more efficient.

In each case, the business isn't selling AI. It's using it to get more from the qualified people it already has, who still own the final call.

How we manage the risks

There are a few key ways we manage the risk associated with AI implementation in our portfolio:

• Disciplined on pricing - The investment thesis must rest on more than just AI-driven savings, so that any efficiencies are additional upside, and entry valuations must be tied to current earnings rather than future earnings.
• Efficiency vs displacement - "Can AI make this business cheaper to run?" is a different question from "can AI make its service unnecessary, or push its prices down?" Where savings are simply competed away to customers, margins don't improve and can in some cases deteriorate. The winners we have seen so far are businesses with enough scale and pricing power to retain part of the benefit driven by AI implementation, such as those where a professional is required to sign off.
• Focus on data and cyber risk - These risks inherently rise with AI integration. This is especially true for businesses holding sensitive financial records, so we look for best practice governance that keeps pace with adoption.

Finally, it comes back to manager selection. A manager's ability to drive operational change now includes technology execution, and we assess that capability directly.

The businesses in the private equity component of our portfolio are not AI companies, and we like it that way. What we look for are managers who can put these tools to work in businesses with durable demand and turn them into better margins, faster growth and higher exit values.

For more information, visit: WAM Alternative Assets.