Key Takeaways
- • Nickel Digital Asset Management's global survey of institutional investors and wealth managers found 96% expect AI to have a positive impact on digital assets, with 26% expecting a very positive impact.
- • Nearly two-thirds of respondents say AI is either fully integrated (21%) or broadly deployed (43%) across investment research and risk management.
- • Investors' top expected AI contribution is risk management and stress testing (33%), followed by trading execution and market-making (31%).
- • Data quality and access (78%) is the leading barrier to AI adoption in digital assets, ahead of model explainability and governance (70%).
- • The surveyed firms collectively manage around $14 trillion in assets across the US, UK, Germany, Switzerland, Singapore, Brazil and the UAE.
Summary
AI will play a central role in the development and continuing growth of the digital assets sector, according to new global research from Nickel Digital Asset Management (Nickel), a London-based digital assets hedge fund manager founded by alumni of Bankers Trust, Goldman Sachs and JPMorgan. The study, conducted with institutional investors and wealth managers, found near-unanimous support for the view that AI will shape the asset class's evolution. Some 96% of respondents believe AI will have a positive impact on digital assets, including 26% who expect a very positive impact, and 94% believe AI will be important in shaping future market development, with 29% describing it as very important.
The research, which surveyed executives at firms in the US, UK, Germany, Switzerland, Singapore, Brazil and the United Arab Emirates managing around $14 trillion collectively, indicates AI is already embedded in core investment processes. Nearly two-thirds of respondents said AI is either fully integrated (21%) or broadly deployed (43%) across investment research and risk management. Investors view AI's primary value as helping manage complexity and market volatility: 33% said it will have the greatest impact on risk management and stress testing, and 31% pointed to trading execution and market-making, where speed and systematic data processing can influence liquidity and pricing efficiency. Only 9% expect the greatest impact on operational efficiency and 6% on idea generation, which the report suggests reflects institutions prioritising control, resilience and market integrity over operational automation alone.
The findings also identify constraints on adoption. Data quality and access were cited as the primary barrier by 78% of professional investors, ahead of model explainability and governance at 70%. Lack of internal expertise concerned 40%, regulatory issues 39%, and cost 36%. Nickel concluded that AI's effectiveness in digital assets will depend on regulatory clarity, data frameworks and governance. Anatoly Crachilov, CEO and Founding Partner at Nickel Digital, said the firm has seen a material increase in AI use within its quant strategies across its multi-strategy portfolio, adding that AI is "enhancing" rather than replacing trader discipline and can help managers identify more nuanced signals, process information at greater scale and execute with higher precision.
The research, which surveyed executives at firms in the US, UK, Germany, Switzerland, Singapore, Brazil and the United Arab Emirates managing around $14 trillion collectively, indicates AI is already embedded in core investment processes. Nearly two-thirds of respondents said AI is either fully integrated (21%) or broadly deployed (43%) across investment research and risk management. Investors view AI's primary value as helping manage complexity and market volatility: 33% said it will have the greatest impact on risk management and stress testing, and 31% pointed to trading execution and market-making, where speed and systematic data processing can influence liquidity and pricing efficiency. Only 9% expect the greatest impact on operational efficiency and 6% on idea generation, which the report suggests reflects institutions prioritising control, resilience and market integrity over operational automation alone.
The findings also identify constraints on adoption. Data quality and access were cited as the primary barrier by 78% of professional investors, ahead of model explainability and governance at 70%. Lack of internal expertise concerned 40%, regulatory issues 39%, and cost 36%. Nickel concluded that AI's effectiveness in digital assets will depend on regulatory clarity, data frameworks and governance. Anatoly Crachilov, CEO and Founding Partner at Nickel Digital, said the firm has seen a material increase in AI use within its quant strategies across its multi-strategy portfolio, adding that AI is "enhancing" rather than replacing trader discipline and can help managers identify more nuanced signals, process information at greater scale and execute with higher precision.
Go deeper than the headline
Research every firm in this story, track the ones that matter and get the daily briefing — free for 7 days.