AI Integration in Investment Management: A 2025 Global Survey

Jan. 14, 2025 /Mpelembe Media/ —   A SimCorp-commissioned report, based on a survey of 200 global buy-side executives, highlights the need for better AI integration in investment processes. The majority of respondents recognise AI’s potential benefits but lack sufficient information for effective implementation across investment analysis, decision-making, risk management, and client engagement. Addressing data infrastructure challenges, particularly through data standardisation and system consolidation, is a key priority. Improving operational efficiency and gaining a holistic firm-wide view of investments are also significant strategic goals. ESG investing presents a particularly strong opportunity for technological innovation.

Several key challenges hinder the integration of AI in investment management, according to the sources:

Lack of information: A significant majority (75%) of buy-side operations leaders understand the potential benefits of AI but require more information on how to integrate it effectively into their investment processes. This includes areas such as investment analysis, decision-making, risk management, data management, and client engagement.

Data infrastructure issues: Many firms struggle with fragmented and inconsistent data sources. Nearly half (47%) of respondents have a data infrastructure that combines in-house and third-party solutions, leading to data challenges. Specifically, firms are challenged by data siloes and a lack of a unified data layer. The inability to manage multi-assets in one view is a main challenge for front office teams.

Need for standardized data: To overcome data infrastructure challenges, buy-side organizations are prioritizing building more standardized data models (67%) and consolidating systems for a common data layer (65%).

Lack of preparedness: A notable percentage of firms feel unprepared to leverage AI, with 16% reporting feeling unprepared compared to only 9% feeling very prepared.

Difficulty in measuring AI success: While there is recognition of the need for AI, firms need help in measuring the success of AI tools. They prioritize increased efficiency in data cleaning (46%), enhanced data visualization (42%), and accelerated time to insights (41%) as measures of success.

Inability to get a total firm-wide view: Buy-side firms struggle with the inability to get a total firm-wide view of investments, risk and performance.

Need for Real Time Data: Firms need a unified data layer that provides a total portfolio view in real time. Firms are also planning to consolidate systems for a real time total portfolio view (64%). In summary, the integration of AI in investment management is hindered by a lack of information, data infrastructure issues, lack of standardization, lack of preparedness, difficulty measuring success, and the need for real time information and a unified view of the firm’s investments and risks.

According to the survey, 16% of respondents felt unprepared to leverage AI. In contrast, only 9% of respondents reported feeling very prepared to use AI. The survey also indicated that a significant majority of respondents (75%) understand the potential benefits of AI, but they still need more information on how to effectively integrate it into their investment processes. This suggests that while there is an awareness of AI’s potential, many firms lack the confidence and knowledge to implement it successfully.

The key challenge hindering buy-side firms’ current investment models is the inability to get a total firm-wide view of investments, risk and performance. This is compounded by the fact that many firms are working with fragmented and inconsistent data sources. Here are some details regarding these challenges:

Fragmented data: Many firms struggle with data that is not unified, with nearly half (47%) using a combination of in-house and third-party solutions. This leads to data silos and inconsistencies, making it difficult to have a clear, overall picture of the firm’s investments.

Lack of a unified data layer: The absence of a unified data layer means that firms cannot easily see a total portfolio view in real time, which is necessary for effective decision-making. This lack of a single view hinders their ability to manage multi-asset portfolios.

Difficulty managing multi-assets: Front office teams find it challenging to manage multi-assets in one view (60%). This inability to view all assets together impedes their ability to make informed decisions and manage risk.

Need for real time information: Firms need to be able to view their investments in real time, with any changes reflected instantly across the entire investment lifecycle. The lack of a real time view contributes to the challenge of managing multi-asset portfolios.

Impact on scaling: The fragmented data landscape slows the velocity of information and impacts the ability to scale. This means firms face challenges growing and adapting to changes in the market.

The challenges faced by buy-side firms are rooted in data management issues such as data siloes, a lack of unified real-time data, and the inability to manage multi-asset portfolios effectively. These issues make it difficult for firms to get a comprehensive view of their investments, risks, and performance.

The top strategic priority guiding technology and operations investments for buy-side firms in 2025 is improving operational efficiency. This is a key finding from the 2025 Global InvestOps report.

Here are some additional points related to this priority:

The report highlights that buy-side organisations are looking to address challenges such as the inability to get a total firm-wide view of investments, risk, and performance, and also the difficulty in launching new products in a timely manner. These issues likely contribute to operational inefficiencies.

The need for improved data management is also closely linked to the goal of improving operational efficiency. Firms are focusing on standardizing data models, consolidating systems for a common data layer, and utilising AI tools for better insights and data predictability.

Firms also recognise the need for a system architecture with a unified data layer to provide a total portfolio view in real time. This would allow changes in one area of the business to be instantly reflected throughout the entire investment lifecycle for both public and private markets.

The survey indicates that firms want to enhance their operating models with greater transparency in outsourced operations data. This transparency would likely support improvements in operational efficiency.

Furthermore, a focus on core business by using external service providers for non-core business processes is a desired outcome for buy-side firms. This move would also allow them to focus on their core operational efficiencies.

In summary, the drive to improve operational efficiency is the main driver for technology and operations investments for buy-side firms in 2025. This goal is closely tied to addressing data management challenges, improving transparency, and streamlining business processes.