AI agents are already moving into financial-market workflows, but when will they actually be trusted to execute trades?
In this conversation, David Rickard, Global Head of Fixed Income at LSEG, explains why AI-powered trade execution is closer than many people think, but still faces significant challenges.
We explore the three major barriers: the difficulty of processing real-time, low-latency data; governance and trust around automated execution; and the fragmented, deeply entrenched legacy systems that underpin many trading workflows.
David also explains why fixed income is particularly difficult to electronify, how AI is already being embedded into trading workflows, and what needs to change before AI agents can move from assisting traders to actually executing trades.
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