250 senior executives working for asset managers in the US, Europe and APAC were surveyed. Those interviewed were equity, fixed income, multi-assets, private market (private equity, private credit, real estate and venture capital), hedge fund, and insurance asset managers
Eighty-three percent of 250 senior executives at fund managers across the U.S, Europe and the Asia-Pacific region say the use of artificial intelligence has been successful in improving investment strategies and portfolio construction, a comprehensive global study commissioned by Clearwater Analytics reveals.
But the firms using AI most heavily are also the ones running into a specific limit most often: data they can't rely on. The more decisions a firm runs through AI, the more it depends on the data behind those decisions, and the faster it finds where that data falls short.
Asset managers surveyed are particularly positive about generative AI's power to reduce portfolio volatility and speed up rebalancing cycles, both high-stakes, high-frequency decisions now running increasingly on AI. Nearly three-quarters (74%) expect generative AI to maintain its current 15% to 20% cut in portfolio volatility over the next three years, with 16% expecting it to cut volatility further still.
On rebalancing, which generative AI has already sped up by roughly 30%, 28% expect that pace to hold and three in five (60%) expect it to reach 30% to 35%. The more of this work moves to AI, the more a firm's results depend on the data feeding it.
Success elsewhere in the business follows the same pattern. Half of asset managers say they have been extremely successful in deploying AI and machine learning company operations, with a further 23% say it has been successfully implemented. In compliance and regulation, 39% say AI has been extremely successful and 41% successful. Across the board, AI is doing what firms hoped it would, which is exactly why the data underneath it is starting to matter more, not less.
