Ares Management, Blackstone Inc and Blue Owl Capital have moved to reassure investors that artificial intelligence is not materially threatening the performance of their software lending portfolios, despite rising market concerns over disruption risks, according to a report by Bloomberg.
Across recent investor communications and disclosures, the three firms have deployed internal models and external assessments to evaluate AI exposure within their private credit books, with results broadly indicating limited near-term risk.
In several cases, the firms characterised portfolio vulnerability as “low,” “medium” or “minimal,” and emphasised that most senior loan exposures remain structurally protected even in scenarios of business model disruption.
Blackstone Inc said it used an internal AI risk scoring framework to review its flagship private credit portfolio, finding that fewer than 5% of holdings showed meaningful exposure to AI-related headwinds. The firm also noted that a portion of its software investments could benefit from AI adoption rather than be negatively affected.
Similarly, Ares Management reported that the vast majority of its software-linked investments were assessed as low risk, with only a small fraction classified as high risk following an external review. The firm said the exercise also identified areas where AI could enhance growth rather than disrupt business models.
Executives at Ares have argued that software borrowers are not uniformly exposed to disruption, noting that many companies are already integrating AI tools into their products and operations, supporting revenue expansion rather than contraction.
Blue Owl Capital conducted a similar portfolio review, concluding that exposure to AI-related disruption across its credit holdings is limited. Management indicated that certain companies within its portfolio are more likely to benefit from AI-driven efficiency gains than suffer from displacement risk.
The reassurances come amid increasing scrutiny of private credit exposure to software companies, as investors assess whether rapid advances in AI could weaken traditional subscription-based and enterprise software models. Market participants have struggled to quantify aggregate exposure, in part due to inconsistent classification of software-related lending across funds.
Analysts estimate that software represents a significant share of business development company lending portfolios, although actual exposure may be higher due to classification differences across strategies.
While firms acknowledged that some companies could face pressure from technological change, they broadly emphasised that most lending is positioned higher in the capital structure, limiting downside risk even in stressed scenarios.
