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Portfolio management is experiencing the strongest impact from artificial intelligence across the asset management industry, with 64% of firms reporting significant change, according to the Annual Survey of Asset Managers 2026 from Acuity Analytics.
The research gathered responses from approximately 80 senior professionals at asset management firms across the Americas, Europe and Asia-Pacific. It examines how automation and AI are influencing major operational, investment and client-facing functions.
Senior Industry Leaders Share Their Views
The survey included a broad range of decision-makers. Chief executives and heads of asset management accounted for 26% of respondents, followed by chief investment officers at 24% and chief operating officers at 19%.
Heads of research, portfolio managers and analysts represented 17% of the sample. Chief compliance officers accounted for 10%, while chief marketing officers made up the remaining 4%.
By assets under management, 36% of participating firms managed between $10 billion and $100 billion. A further 34% oversaw less than $10 billion, while 30% managed more than $100 billion.
The regional distribution was evenly divided between the Americas and Europe, each representing 45% of responses. Asia-Pacific contributed the remaining 10%.
Portfolio Management Records the Highest AI Impact
Portfolio management ranked as the area most affected by AI and automation. Nearly two-thirds of respondents, or 64%, said the function had experienced a significant impact. Only 1% reported limited or no change.
The findings suggest that AI has become a central part of portfolio management across firms of different sizes and investment approaches. Technology is increasingly being used to support data analysis, identify market patterns, improve decision-making and enhance portfolio construction.
Credit risk analysis was the second-most affected area, with 53% of respondents reporting a significant AI impact. This result highlights the rapid adoption of AI in functions that rely heavily on structured data, quantitative models and large-scale analysis.
ESG advisory services recorded a significant impact rating of 43%. However, half of respondents described the influence as moderate, indicating that AI is expanding within ESG processes without yet fundamentally changing the function.
Regulatory Compliance Sees the Slowest Transformation
Regulatory compliance recorded the lowest level of significant AI impact, at 26%. In addition, 14% of respondents said the function had experienced limited or no change.
The slower pace of adoption reflects the sensitive nature of compliance work. Strict regulatory requirements, accountability standards and the need for human oversight can make firms more cautious when introducing AI into compliance processes.
While AI can assist with monitoring, reporting and document analysis, many firms continue to rely on human review for decisions that carry legal or regulatory consequences.
Data-Driven Functions Are Changing Fastest
The survey shows a clear connection between AI adoption and the level of data intensity within each asset management function. Portfolio management and credit risk analysis are changing most rapidly because both depend on quantitative modelling, data processing and pattern recognition.
By comparison, areas that rely more heavily on personal judgement, relationship management and contextual understanding are progressing at a more measured pace. Customer service, sales, marketing and regulatory compliance are seeing AI used mainly to support existing teams and workflows.
The relatively high moderate-impact figures recorded in sales, marketing and compliance suggest that AI is already gaining ground in these areas. However, its primary role remains assistive rather than transformative, helping employees complete tasks more efficiently instead of replacing established processes.
AI Investment Could Shape Competitive Advantage
For asset managers, the research indicates that immediate efficiency gains are most accessible in portfolio management and credit risk analysis. Firms that invest in suitable infrastructure, high-quality data and effective governance may be able to improve productivity and strengthen investment processes.
The longer-term challenge will be extending AI into functions that involve more complex judgement and human interaction. Although progress may be slower in these areas, successful adoption could create significant advantages in client engagement, compliance operations and business development.
Overall, the findings show that AI adoption in asset management is advancing unevenly. Data-intensive investment functions are leading the transition, while human-focused and highly regulated activities are adopting the technology more cautiously.
Source: fintech.global