Generative AI is without a doubt a tremendously disruptive innovation that will both create and destroy jobs. Asset management is becoming more and more involved in the balance between the two, albeit unintentionally, as a “natural experiment.”
The way that the sector is implementing the generative AI revolution, or Gen AI, throws light on organizational and legal challenges that extend beyond the job argument and have an impact on the rest of finance and health.
The fact that the Gen AI revolution is still in its early stages is among its most remarkable features. Computing power, data, talent, and financing are its primary drivers, and they are compounding at a scale and speed that will highlight its disruptive forces. It makes sense that it has gone to the top of chief executives’ agendas in an expanding number of businesses and industries.
One area where Gen AI has the most promise is asset management, as it indicates several organizational and operational adjustments to the sector. The most agile businesses already use it to increase operational effectiveness, enhance communication, and strengthen defenses against cyberattacks. And this is only the beginning.
Teams that deal with clients and investments can now create presentational power points with remarkable ease to demonstrate skills and support novel trade concepts. It is completed more rapidly and precisely to fulfill the important and time-consuming duty of informing clients of returns and performance attribution. Additionally, the IT staff are equipped with more tools to counter the increasing volume of hacking attempts.
Gen AI improves labor in each of these scenarios. It enhances workers’ abilities and aids in their ascent along the value-added curve. Even though regular, low-skill jobs may be lost, overall labor demand will be positively impacted, particularly when more engineers are hired. Speaking with AI engines has become a crucial ability for most employees, new and old alike.
Look ahead now. It is not difficult to imagine a future in which all higher-skill jobs, including as risk mitigation, model portfolios, asset allocation, and securities selection, are completely automated by Gen AI engines. The massive data sets that are currently glaringly underutilized in the industry will be used to train these engines.
It is therefore not impossible to foresee Gen AI technologies, taught in this case by a combination of real and virtual data, assisting in the design and structure of new asset classes, given other technological advancements. The most innovative and fruitful aspects of asset management will eventually blend Gen AI-enabled technologies with fresh, crucially Gen AI-native skills. This entails the capacity to considerably more precisely tailor individual investment accounts to suit the risk tolerance and behavioral preferences of clients.
However, the journey ahead will also be rocky. Present capacities are far from ideal, and talent is not dispersed equally. There are biases in their application. The questions of who will oversee AI internally and what more comprehensive set of national and maybe worldwide legislation will control it remain unanswered. Furthermore, those who live in the transition zone are feeling especially uneasy due to the growing dispersion of the technology stack between China and the US, a phenomenon that will only become worse.
The industry’s structure will also see significant upheavals along this path. It will become more and more difficult for those who are behind in comprehending the disruptive force of AI and its possible applications, especially given the talent, managerial agility, and data organization involved. If they don’t seize the leapfrogging opportunities—which are probably limited to the early adopters—the gap will only widen.
When combined, these factors will accelerate industry trends toward a composition of a limited number of very large companies and many smaller specialty businesses. There will be pressure on mid-sized managers, those managing assets between $100 billion and $500 billion, and Gen AI-lagging organizations to either atrophy or consolidate. As a result, jobs are lost at this point.
The challenges faced by asset management will be replicated in other contexts across the financial and healthcare industries. Businesses would be foolish to disregard this occurrence. It will also put pressure on regulators who have already lagged in their knowledge of and oversight of non-banks as a result of their excessive focus on banks.
