Mohamed El-Erian, a Cambridge economist, highlights the dual impact of generative AI on asset management, predicting job creation and displacement, and emphasizes the need for companies to adapt.
Mohamed El-Erian, advisor to Allianz and Gramercy, as well as president of Queens’ College, Cambridge, highlights the transformative impact that generative AI (Gen AI) is expected to have on the asset management industry. Through detailed research, he explains how Gen AI drives both elimination and job creation, and provides a detailed perspective on its ability to innovate asset management practices.
Gen AI is at the heart of technological progress and is driven by increasing computing power, massive data collections, growing expertise and significant investments. These elements pave the way for unparalleled disruption and opportunity in asset management and other areas. Early adopters of Gen AI are already witnessing improvements in operational efficiency, customer interaction, and cybersecurity measures.
The effect on the workforce in the sector is significant. Gen AI improves employee performance, allowing them to focus on higher-value tasks by automating everyday activities and strengthening cybersecurity. This transformation requires a workforce skilled in AI technology, increasing the need for technical skills and changing the landscape of job requirements.
El-Erian expects Gen AI to extend to complex operations such as asset allocation, model portfolio construction, security selection and risk management. Such advancements are expected to leverage untapped data within the industry, leading to the creation of new asset classes and tailored investment approaches.
Yet this journey is not without hurdles, including technological shortcomings, gaps in expertise and unfamiliar regulations. The different technological environments between China and the US increase complexity and pose challenges for those in between.
El-Erian suggests that the asset management industry will undergo significant transformation, with the trend moving towards a mix of large entities and specialist firms. Midsize companies and those that are slow to adopt Gen AI may face critical challenges, potentially leading to mergers or becoming irrelevant. This shift highlights the critical role of Gen AI in defining the future landscape of the industry.
He calls on companies and regulators alike to recognize and address the impactful potential of Gen AI. Today’s experiences within asset management are indicative of the broader implications for finance, healthcare and beyond, making Gen AI a key driver in the evolution of the economic environment.
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