Software companies are having a challenge securing loan deals. What used to be a relatively easy process for many tech firms has become more costly, heavily scrutinised, and uncertain. The development has been blamed on the rise of AI which, though offers immense opportunities, is also reshaping lenders’ perception of risk across the software industry.
The immediate impact is most visible in the leveraged loan market, where mid-sized or highly leveraged software companies typically borrow money. Software firms make up roughly 17 per cent of all outstanding leveraged loans and dominate U.S. tech industry borrowing in this segment. As AI threatens to disrupt traditional software models, lenders are pricing in higher default risk and demanding greater returns to compensate.
Almost half of current software loans are rated “B‑” or lower, indicating a higher likelihood of default under stress scenarios. This combination of riskier debt and uncertainty about future cash flows has slowed the issuance of new loans. In fact, there are currently no major leveraged loan deals for software companies in the pipeline, as borrowers and banks wait for conditions to stabilise.
AI’s influence on lending comes in two ways. First, lenders are repricing credit risk. The potential for AI to replace or automate aspects of existing software services could reduce predictable revenue, raising the probability of default. UBS analysts suggest default rates for riskier borrowers could rise by 3–5 per cent if AI disruption accelerates, compared with previous forecasts of 1–2 per cent. Private credit markets, where underwriting standards are often looser, could face even greater uncertainty.
Meanwhile, market sentiment is shifting. Software equities have fallen roughly 20 per cent this year as per Reuters, eroding investor confidence and prompting higher yield demands. Banks arranging loans are encountering scepticism from institutional investors, leading to withdrawals or delays of financing packages that would have been routine in the past.
Some companies are already feeling the effects. Qualtrics, which is seeking $5.3 billion to fund its acquisition of Press Ganey Forsta, and Team.blue, a European digital services provider that postponed a planned loan extension, illustrate how even established firms are encountering tighter scrutiny and higher costs.
Lenders are responding with stricter covenants and legal protections. Future deals are expected to require companies to maintain lower debt-to-earnings ratios, and refinancing may involve deeper discounts for borrowers.
Looking ahead, this trend signals a broader transformation in tech finance. Software companies were long viewed as low-risk borrowers due to predictable revenues and strong margins. That assumption is now being questioned. Firms that cannot demonstrate AI readiness or maintain strong balance sheets may struggle to refinance debt or raise new capital without paying a premium. Those with weak financials or outdated products could face consolidation, forced pivots, or even exclusion from credit markets.
For the market overall, this repricing of risk may reshape the software landscape. Companies that successfully integrate AI into their offerings are likely to attract financing more easily, while smaller or legacy firms may see capital flight as lenders seek safer bets. In this way, AI is not only driving innovation but also redefining which companies are considered financially sustainable and creditworthy.
The coming years will reveal which software firms can adapt to this dual challenge: thriving in the AI era while meeting the stricter expectations of lenders. For investors, lenders, and tech companies alike, the message is clear: AI is no longer just an opportunity—it is a factor that determines access to capital and survival in an increasingly competitive market.
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