Published by Global Banking & Finance Review®
Posted on February 23, 2026
5 min readLast updated: April 2, 2026
Add as preferred source on GoogleSoftware companies are putting debt deals on hold as AI amplifies credit risk and lenders tighten terms. Spreads are widening, private credit jitters are growing, and upcoming financings will test appetite for leveraged software issuers.
By Matt Tracy and Saeed Azhar
Feb 23 (Reuters) - Software companies are delaying debt deals as higher borrowing costs and tougher scrutiny from lenders weigh on the sector, at a time when mounting pressure from artificial intelligence threatens their business models, industry sources said.
Software firms both in the U.S. and elsewhere have already paused or postponed fundraising efforts as lenders and investors expect AI to upend the industry. These concerns have been underscored in loan markets, where spreads for risky companies have started to price in more defaults. AI jitters also affected private capital manager Blue Owl, whose shares slid after its latest move to sell $1.4 billion in assets to return money to investors.
"We expect AI disruption risk to be increasingly reflected over 2026 to early 2027, particularly for lower‑quality credit sectors with elevated refinancing needs — and more so in the U.S. than in Europe," said Matthew Mish, UBS' head of credit strategy.
Leveraged loans, especially for U.S. tech companies, have begun to price modestly higher defaults. UBS expects defaults to rise 3% to 5% in a scenario of quicker market disruptions, compared with market expectations for an increase of 1% to 2%.
"The disruption is going to play out over two years," Mish said. "We ultimately think that the market will price in a majority, but not all of the defaults that we're forecasting."
Even those companies whose debt is deemed higher quality and less vulnerable to the impact of AI have held off on tapping markets until trading levels recover, one banker said.
The market will closely watch investor reception to Qualtrics, a well-established software maker whose lenders will be in the market next month to raise a $5.3 billion acquisition financing package for its purchase of rival Press Ganey Forsta, a source familiar with the matter said.
Qualtrics declined to comment. Press Ganey did not immediately respond to a Reuters request for comment.
LEVERAGED LOANS
The potential disruption from AI is having a bigger impact on more leveraged loan deals than high-yield bond deals, according to two bankers who declined to be identified discussing transactions.
Technology industry borrowers, of which 60% are in software, account for the largest portion of leveraged loans, according to Brendan Hoelmer, head of U.S. default research at Fitch Ratings.
Tech loans represent 17% of outstanding loans in the leveraged market, valued at $260 billion.
Meanwhile, tech borrowers make up just 6% of outstanding high-yield bonds totaling $60 billion, Hoelmer noted. Of those, 70% are to software borrowers.
A majority of the software sector's exposure is tied to lower credit ratings - with 50% of the loans holding a "B- or lower" credit rating - loans which typically denote a higher risk of default, Morgan Stanley estimates.
Private credit software and services exposure is about 20%, BNP Paribas analysts estimate.
U.S. stocks have also been roiled by AI, starting with investors dumping shares of software companies, then companies in sectors vulnerable to automation. The software index is down 20% so far this year.
Only 0.5% of outstanding software sector loans are due this year, while 6% are due in 2027, Fitch's Hoelmer said. On the high-yield side, only 0.7% of software debt is due this year and 8% in 2027, he added.
Still, companies in the sector that have tried to tap U.S. debt markets have faced significantly higher borrowing costs from banks to underwrite the debt. Banks marketing the loans also are facing more skepticism from potential investors, according to the two bankers.
Banks likely will ask for higher yields on new debt and deeper discounts on earlier debt, said the first banker, who declined to be named discussing specific deals.
Companies will come off the sidelines when prices improve, the first banker said.
Future deals are also likely to include stricter covenants, or legal protections for investors, to get done, the second banker noted. These include maintenance covenants, which force borrowers to keep their debt-to-earnings ratios below specific levels, the banker added.
Several planned deals in the tech sector have been pulled or delayed since late January. European digital service provider Team.blue postponed an extension of its 1.353 billion euro ($1.60 billion) term loan from September 2029 and a repricing of its $771 million term loan, according to the first banker. Team.blue declined to comment.
There are currently no leveraged loan deals for software companies, as companies and banks wait for trading levels on existing debt in the sector to recover from their losses since late January, when AI disruption fears rose.
Meanwhile lower-rated companies with upcoming maturities "are likely to face greater refinancing and default risk in 2026," according to a Moody's Ratings report published in January.
"I don't really see software and business services as being hot sectors for issuance over the next year," said Jeremy Burton, portfolio manager on the leveraged finance team of asset manager PineBridge Investments. "The technology is changing so quickly that you've really got to be confident."
($1 = 0.8482 euros)
(Reporting by Matt Tracy and Saeed Azhar, editing by Lananh Nguyen and Diane Craft)
The piece examines how AI-driven disruption and tighter lender scrutiny are pushing up borrowing costs for software firms, leading many to delay debt deals and face stricter covenants.
Lenders are pricing in greater default risk from rapid AI adoption and weaker credits, demanding higher yields, deeper discounts on loans, and tougher investor protections.
Exposure is heavier in leveraged loans for tech and software borrowers, so AI-related disruption and refinancing risks are being reflected more in loans than in high-yield bonds.
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