# AI Threatens Leveraged Software Buyouts _AI advancements and rising interest rates are creating significant risks for highly leveraged software companies, potentially leading to a wave of restructurings._ **Updated:** 2026-08-22 **Published:** 2026-08-13 **Source:** https://www.startuphub.ai/ai-news/technology/2026/ai-threatens-leveraged-software-buyouts --- The burgeoning capabilities of artificial intelligence are casting a long shadow over the software industry, particularly concerning the leveraged buyout (LBO) model that has fueled significant growth in the sector. Paula Seligson, a Senior Reporter at Bloomberg News, discussed the potential "SaaS Apocalypse" and its implications for private equity firms and their heavily indebted software holdings. AI AdvancementsDriver AI's burgeoning capabilities casting a long shadow over the software industryFrom the articleThe primary concern driving the potential disruption is the rapid advancement of AI technologies.Rising Interest RatesDriverincreasing cost of debt for highly leveraged software companiesFrom the articleAs interest rates have risen, so have borrowing costs, squeezing liquidity for these companies.Leveraged Buyout ModelContextprivate equity acquires companies by loading them with significant debtFrom the articleThe burgeoning capabilities of artificial intelligence are casting a long shadow over the software industry, particularly concerning the leveraged buyout (LBO) model that has fueled significant growth in the sector.causesSoftware Revenue FaltersEffectAI's disruptive potential makes it harder for software companies to growFrom the article 2 mentionsThis model, while profitable when companies perform well, becomes precarious when revenue growth falters.leads toDebt Service RiskOutcomecompanies struggle to service debt when revenue growth faltersresults inSaaS ApocalypseOutcomeFrom the article 2 mentionsPaula Seligson, a Senior Reporter at Bloomberg News, discussed the potential "SaaS Apocalypse" and its implications for private equity firms and their heavily indebted software holdings.impactsPrivate Equity FirmsCorefacing significant risks with their heavily indebted software holdingsFrom the article 5 mentionsSeligson explained the fundamental private equity strategy: acquiring companies by loading them with debt, which is then serviced by the target company itself, not the acquiring firm. ## The Mechanics of Private Equity Leverage Seligson explained the fundamental private equity strategy: acquiring companies by loading them with debt, which is then serviced by the target company itself, not the acquiring firm. This model, while profitable when companies perform well, becomes precarious when revenue growth falters. "The better the margins, the more debt you can load it up with," Seligson stated. "The whole basically private equity business model is to use that to lever up a company when they buy it. The debt is not borrowed by the private equity firm. The debt is borrowed by the target company being acquired." The full discussion can be found on **Bloomberg Podcast**'s YouTube channel. ![‘SaaSpocalypse’ Risk From AI Reaches Beyond Private Equity - Bloomberg Podcast](https://img.youtube.com/vi/b23UlBRSI7w/maxresdefault.jpg) ‘SaaSpocalypse’ Risk From AI Reaches Beyond Private Equity, from Bloomberg Podcast ## AI's Disruptive Potential The primary concern driving the potential disruption is the rapid advancement of AI technologies. Seligson highlighted that while software providing core infrastructure might be relatively safe, companies focused on data visualization or tasks that can be replicated by AI models like Gemini or ChatGPT are particularly vulnerable. The fear is that "you'll have certain types of software companies especially affected," Seligson noted. "If you are providing software that's like the infrastructure layer of a company, probably okay. If you're doing data visualization and that's your main product, you can just plug that into Gemini or ChatGPT. And those business models could be especially at risk." The potential for internal teams to use AI tools to replicate existing software functionalities on a per-seat basis could erode revenue streams, even if not fully replacing them. ## The Medallia Case Study Seligson pointed to the example of Medallia, a software company taken private by Thomas Bravo. Despite its previous success, Medallia faced significant financial difficulties, leading to a $5 billion loss for its investors. Seligson noted that Medallia's issues predated the current AI concerns but served as a stark reminder of the risks involved. "Toma Bravo took Medallia private," Seligson recounted. "It seemed like a very smart investment at the time. They used a $1.8 billion private credit loan to finance it, and specifically a recurring revenue loan... and it also had a special feature called pick or payment in kind, where you could basically defer some of the interest by adding it to the principal payment of the debt later. And so basically this company tried to increase earnings. It couldn't. But because it was picking the debt, the actual total debt size kept increasing." This ultimately led to an unfortunate restructuring. ## Debt, Rates, and Refinancing Risks The conversation then shifted to the broader financial implications. Seligson explained that many LBOs were structured with floating-rate debt during the 2020-2022 period. As interest rates have risen, so have borrowing costs, squeezing liquidity for these companies. Furthermore, the difficulty in selling companies or taking them public due to falling valuations means many PE-backed software firms are "stuck." The critical test, Seligson emphasized, lies in refinancing debt that is maturing in the coming years, with an estimated $150 billion in such debt across various markets. ## The Future Outlook Seligson cautioned that the full impact of the potential "SaaS Apocalypse" is yet to unfold, with the debt market likely to reveal the extent of the crisis on a case-by-case basis over the next few years. The trend of private equity funds reducing their share of software deals, as indicated by PitchBook data showing a decline from 19.8% in 2022 to an estimated 10.7% in 2026, suggests a growing wariness in the market. "Lender confidence is key because if you lose access to debt capital markets, at the very least your borrowing costs will go up even more. In a worst-case scenario, you might not be able to refinance at all, and either of those can cause a restructuring," Seligson concluded. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory.