Artisan Credit Opportunities Fund | Software and AI: Volatility Creates Opportunity
- Jul 1
- 4 min read
Artificial intelligence is reshaping the software landscape, but not all software businesses face the same risks. In this discussion, Bryan Krug explores how the team evaluates software companies, where opportunities remain, and why disciplined underwriting continues to be the key to navigating an evolving market.
Transcript:
Meaghan Mahoney:
We've spoken previously about the concerns surrounding software assets and the excesses that were building in the sector. Medallia is one example you've highlighted for several years.
What's interesting is that software has historically been an area where we've had meaningful exposure. However, heading into what many have called the 'SaaS-pocalypse' earlier this year, we were notably underweight.
Given your long-held views on the sector, I'd be interested in your perspective today. How do you assess software assets now? How do you identify business quality, which I know is your most important underwriting pillar, and what is your current outlook for software?
Bryan Krug:
Software is a nuanced sector, and I think it's helpful to separate it into two broad categories.
The first is traditional software businesses—companies generating EBITDA margins of around 40% with relatively modest growth. The second is the recurring revenue or high-growth software model, where businesses are often EBITDA negative and rely on future growth to achieve profitability.
Each group faces different challenges. For traditional software businesses, the key issue is the durability of the business model. Many of these companies were considered so defensive that they were acquired at valuations of 20–25 times EBITDA. Those valuations supported debt financing of 40–50% of the purchase price, equating to leverage of around eight to ten times EBITDA. As confidence in the durability of these businesses has declined, those valuation multiples no longer provide the same margin of safety.
Where companies have continued to perform well, grown cash flow and reduced leverage towards five to seven times EBITDA, we're comfortable providing financing. We believe established software incumbents retain meaningful competitive advantages, provided they continue investing in their products and embedding AI capabilities, even if that results in lower margins.
Software has always been a business where acquiring customers is the hardest part. Businesses with strong proprietary data, core infrastructure or regulatory advantages remain particularly attractive to us.
The greatest challenges have emerged in the recurring revenue software segment. During COVID, technology spending accelerated dramatically, pulling forward demand by several years. Many companies expected that growth to continue, but it hasn't. That's where we've seen the greatest stress and losses, particularly within private markets.
As a result, we've selectively added exposure to software businesses with strong infrastructure, regulatory or data advantages where valuations have become much more reasonable.
Meaghan Mahoney:
There's been a lot of discussion about whether AI represents a genuine risk to software businesses, or whether the market is overstating that risk. What's your view?
Bryan Krug:
To date, I believe the issues we've seen have primarily been the result of poor underwriting decisions made several years ago, rather than AI itself.None of the recent software defaults have occurred because AI has displaced those businesses. The practical impact of AI will take years to develop as solutions mature and customers adopt them.For the types of businesses we're focused on, I find it difficult to imagine large organisations replacing core infrastructure systems simply to save a relatively small amount of money while putting mission-critical operations at risk.Within syndicated credit markets, we're finding selective opportunities. That doesn't mean the entire sector is attractive—it means we've identified a small number of high-conviction investments where we believe the risk is well understood and appropriately compensated.Looking ahead, the biggest challenge for software companies will be determining how they invest in AI capabilities while managing profitability. There's a useful parallel with the retail industry during the rise of e-commerce. Many retailers resisted investing online because it diluted margins, but those that failed to adapt ultimately lost market share.AI presents a similar challenge today. Companies will likely need to accept lower margins in the short term to embed AI into their products and remain competitive over the long term.
Disclosure:
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