Industry data shows cautious progress, with only 18% deploying AI in core operations
Thursday, 15th January 2026 – New research in Carne Group’s Supermodel II report reveals the asset management industry’s adoption of artificial intelligence (AI) is limited and uneven, despite widespread discussion of its transformative potential. This leaves firms less likely to achieve the momentum required to remain competitive, with McKinsey recently identifying a critical 600-day window for companies to become AI-centric or risk failure in the world of generative AI.
Carne’s survey of 200 senior asset management executives found that fewer than one in five firms have deployed AI in core operations, with most applications restricted to marketing (42%), risk management (36%), and RFP processes (34%).
The report highlights that:
- 60% of asset managers admit to underinvesting in AI for fund launches, citing poor data quality and tight capital expenditure budgets as major barriers.
- 38% of firms rate themselves as highly effective at speed to market, but
- 60% believe they must accelerate fund launches to remain competitive.
Siobhan Noble, Chief Data and AI officer at Carne Group, commented: “The Supermodel II data is a wake-up call. Asset managers are talking a big game on AI, but the sector is still waiting for true transformation. Digitising a broken process just digitises inefficiency. The imperative is to first understand the problem statement, fix the process, and then apply technology, including AI.”
“Executive-level sponsorship is no longer a luxury, it’s a necessity. Without leadership setting the direction and committing resources, even the most promising AI initiatives risk stagnation. The next 600 days will draw a sharp line between leaders and laggards.”
Recommendations for asset managers
- Invest in clean, centralised data and process foundations now.
- Secure board-level sponsorship and set clear priorities.
- Adopt a hybrid approach: combine bottom-up experimentation with top-down strategic programmes.
- Partner for scale, especially for smaller managers.
- Focus on ROI, not hype: build a business case, set KPIs and measure impact.
“The countdown is on. With just 18–24 months to move from proof-of-concept pilots to enterprise-scale AI, asset managers face a defining moment. In a market where speed, personalisation, and data-driven insights are fast becoming the price of entry, the next two years will determine who leads, and who risks irrelevance”, Noble continued.
Carne is currently finalising its programme to make the fund launch lifecycle more efficient, where AI is central to reducing fund launch timelines by nearly 50%. This is driven by automating legal reviews and orchestrating complex workflows.
About the research
Carne Group partnered with CoreData to survey 200 senior executives from global asset management firms between Q2 and Q3 2025, gaining insights into their firm’s growth priorities and operational transformation strategies. Respondents represented both traditional and alternative managers, with roles across operations, finance, risk, and distribution. The findings were complemented by in-depth qualitative interviews with operations leaders from global fund houses. Data tracking the proportion of Europe-domiciled funds overseen by third-party ManCos was provided by Monterey Insight.
