Technology sector analyst, Brad Lewis unpacks how AI is impacting the outlook for credit markets across software and other sectors. He provides insight into the Barings' team's framework for parsing winners from losers, and talks about what's next for AI.

Episode Segments:
(01:22) – Brad’s background & tech’s historical development in high yield
(04:39) – Why AI became THE story in late-25/early-26: new models, agents & an equity sell-off
(09:01) – AI fears bleed into credit markets: Leveraged loans, BDCs, CLO selling, lower terminal values
(11:21) – SaaS-pocalypse or hyperbolic headlines?
(15:03) – Parsing winners from losers / core vs. non-core software
(16:34) – 3 ways to identify if a company really has a “moat” or defensible business model
(21:06) – AI-related risks and opportunities in sectors outside of software
(23:50) – How AI exposures compare between public and private credit markets
(29:35) – What Brad is watching next for AI (and where investors may not be focusing yet)
(38:44) – Why process matters more than ever amid relentless AI headlines
(40:22) – More optimistic or pessimistic on AI’s credit market impact in the years ahead?

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IMPORTANT INFORMATION

Any forecasts in this podcast are based upon Barings’ opinion of the market at the date of preparation and are subject to change without notice, dependent upon many factors. Any prediction, projection or forecast is not necessarily indicative of the future or likely performance. Investment involves risk. The value of any investments and any income generated may go down as well as up and is not guaranteed. PAST PERFORMANCE IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS. Any examples set forth in this podcast are provided for illustrative purposes only and are not indicative of any future investment results or investments. The composition, size of, and risks associated with an investment may differ substantially from any examples set forth in this podcast. No representation is made that an investment will be profitable or will not incur losses.

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Managing AI Risk in Credit Portfolios