Dagmara Michalczuk, Creditflux, July 2026

Despite the aphorism that “investors have short memories”, financial markets rarely reassess a company’s prospects dramatically over a short time horizon. Rackspace’s USD 1.6bn May 2028 first-lien second-out term loan is one such rare example, rallying approximately 67 points from a February 2026 low of 24 to 91 by the end of June. Rackspace’s equity re-rated even more sharply, surging 573% year-to-date through 30 June, although it remains below its 2020 IPO price. This remarkable turnaround provides an early case study of how the AI capex cycle is reshaping credit markets and what it may mean for CLO portfolio management.

What changed investor sentiment?

Prior to its recovery, Rackspace’s legacy managed cloud services business faced slowing revenue growth and margin compression from hyperscalers, specialised consultancies, regional managed service providers and increasing automation of cloud management tools. The company also carried a substantial debt burden despite its March 2024 restructuring, which reduced debt, injected new capital and extended maturities. As recently as March 2026, Moody’s downgraded Rackspace to Caa2 with a negative outlook and S&P lowered its rating to CCC+ with a negative outlook, citing declining revenues and rising leverage.

However, beginning in late 2025, a new CEO launched an “AI-first multi-cloud strategy” aimed at repositioning Rackspace as a provider of governed AI infrastructure for regulated industries, such as healthcare, financial services and defence. The thesis was simple: many enterprises would be reluctant to run sensitive AI workloads entirely on public cloud platforms and would instead require dedicated GPU infrastructure, secure environments and operational governance. These were capabilities Rackspace had and could combine into a fully managed AI infrastructure offering.

The company began to assemble a new ecosystem. In February 2026, Rackspace and Palantir announced a strategic partnership to deploy Palantir software on Rackspace’s private and sovereign cloud infrastructure. A month later, Rackspace partnered with Uniphore to deliver “infrastructure-to-agents” AI solutions for regulated enterprises. Yet the loan market remained sceptical.

The first meaningful catalyst arrived in May 2026 when Rackspace signed a memorandum of understanding with AMD to deploy an initial 30MW of AI computing capacity across its data centres between late 2026 and 2028. The loan rallied from the low 50s into the low 80s on this news. Confidence strengthened further in June when the companies announced a definitive agreement. On the same day, Rackspace announced a 15% workforce reduction expected to generate USD 75–85m in annual savings. The term loan reached a high of 93.6 on 17 June.

Nonetheless, significant execution risks remain. These include financing the planned GPU deployment and demonstrating sustainable demand for its AI infrastructure platform. Nevertheless, the loan market appears to have begun valuing Rackspace less as a mature IT services provider facing secular decline, and more as a potential beneficiary of enterprise AI investment. While it is too early to judge whether that transformation will ultimately succeed, the repricing has already been meaningful and tradeable. Rackspace may prove to be one of the earliest examples of AI positively impacting valuations in the loan market.

An opportunity for alpha in credit

For CLO managers, the implications extend beyond this single issuer. First, AI is beginning to influence credit markets much as it has equities, with investors increasingly repricing future enterprise value based on strategic narratives before improvements appear in financial results. Second, as AI creates dispersion between winners and losers, accurately assessing whether a company can successfully reposition its business model may become an important source of credit alpha.

At the same time, active managers will need the discipline to determine when a successful re-rating has largely been reflected in market prices and portfolio risk should be reduced. In this environment, CLO managers that combine rigorous credit analysis with an understanding of technological disruption may be best positioned to identify tomorrow’s outperformers and underperformers.