Yesterday’s FundsTech 2026 panel, ‘Tech & Talent – Building the Workforce of the Future’, tackled the challenge facing the asset management industry: how to embed innovation and retain top talent as automation and AI reshape job functions.
Panellists Siobhan Clarke, chief investment operations officer at Royal London Asset Management, and Deepshika Hariparsad, head of technology strategy at Ninety One, shared that the new technological paradigm requires continuous reskilling, adaptability, and most importantly, human oversight.
The discussion focused on how roles, such as that of a research analyst, are evolving. They still have the responsibility to analyse the AI’s output and understand whether it’s correct and to make sure that they make the right decision, said the panellists.
Deepshika Hariparsad said that AI signals “role evolution”, and while retraining is not an alien concept—drawing an analogy to the shift from manual counting to using a calculator—the current “magnitude of change is huge and the skill gap bigger.” According to Hariprasad, retraining and reskilling, as opposed to deskilling, is the only option.
Siobhan Clarke concurred on the need for adaptability, stating that the “old guards” in the industry should aim to reinvent themselves to successfully navigate organisational shifts. She highlighted the opportunities AI presents, saying it could even allow a new asset management company to be built from scratch, but cautioned that professionals still need to understand different instruments and fundamental concepts to make it happen.
One point of convergence was the need for guardrails against the risk of AI hallucination in a highly regulated industry like asset management. Hariparsad pointed out that large language models often sound convincing in what they are saying, but hallucinate, necessitating a need for guardrails for accuracy and continued human presence.
“Even if the technology is better, the element of human trust must be earned,” said Clarke.
Despite the risks, AI’s utility was acknowledged. Clarke highlighted AI’s use in high-volume tasks, citing reading deal documents in the private assets and the preparation of investment committee papers for trade approval “a great use case for AI.”
However, this output still requires human expertise. “Investment committees should use AI to critique
the paper written by humans,” said Clarke.
In conclusion, building the workforce of the future means equipping skilled professionals to manage powerful but fallible tools, ensuring human expertise acts as the final check on AI-driven insights.
