2025 Trends and Outlook: Increasing Automation for Data Access and Operational Efficiency

Laura Jesson

Senior Research Analyst

Laura Jesson has more than 25 years of experience in the financial services industry as a project manager, business analyst, and consultant. She joined Cutter Associates in 2013. Prior to Cutter, Laura spent eight years at Wells Capital Management and Evergreen Investments, where she managed investment operations projects, including those focused on outsourcing, client reporting, and trade management. She previously worked at Omgeo as a member of the Central Trade Manager (CTM) product design team. Laura started her career at Andersen Consulting (now Accenture) as a process consultant supporting a variety of projects for clients in the financial services industry. Laura earned her bachelor of arts in economics and psychology from Amherst College. She holds the Project Manager Professional (PMP) certification.

Recent research assignments and publications include the following:

AI Use Cases in Investment Management: Infinite Possibilities 
Business Intelligence Tools
Cutter Benchmarking: Client Reporting
Cutter Benchmarking: Firmwide ESG Capabilities
Cutter Benchmarking: Managing Vendors and Service Providers 
DataOps: In Theory and Practice
Enabling Data Analytics
ESG Data Management 
ESG: It’s a Jungle Out There ─ A Look at the Data Provider Landscape
ESG Investing: One Vision, Many Lenses 
Execution Management Systems
Hybrid Work Arrangements and Their Impact on Firm Culture
Using RPA to Automate Business Processes
The Role of the CRM for Asset Managers

Feb 06, 2025

Investment management firms setting annual goals for increasing operational efficiency is about as predictable as a middle-aged person setting a New Year’s resolution to adopt a healthier lifestyle. Yet in 2025, we predict that firms will stick to their plans by prioritizing automation as a pathway to greater operational efficiency and risk control.

2024 was a year of AI and GenAI exploration, with firms identifying use cases across all functional areas. Investment managers are inspired by using the technology to automate and improve data access. Some commonly discussed opportunities to leverage AI for data include the following:

Accessing information, especially from voluminous PDF documents

Improving data management through data tagging and identification of meta data

Applying semantic search against data sets

By improving data access, firms will find more opportunities to use that data to automate downstream processes to soothe or solve common pain points in cumbersome, complex, and manual processing, as these are the most costly and risky. Two commonly discussed scenarios are automating workflows for onboarding and alternative investment processes.

When firms onboard new accounts, it’s common for the manager and their clients to exchange pertinent information in the form of documents, contracts, and agreements. The manager must access relevant data in these documents to properly set up the account across systems and service providers and establish compliance rules and trade restrictions. Having access to the client account data and contract terms allows for greater automation of well-established onboarding workflows. Although teams may still opt to have a human involved in onboarding processes especially to perform approval tasks, firms will benefit from using trusted data to automate even the initial steps of the workflow to yield time-savings and reduce human-error risk in processing.

Teams are also examining opportunities to improve support for alternative investments by automating data acquisition. Because firms have historically relied on manual efforts and patchy data from documents and other unstructured sources for these processes, they have a huge opportunity for improvements in investment decision-making, ESG and other risk analysis, and valuations. Of course, not all processes will be automated and optimized immediately, but it’s on the horizon, as both investment managers and the vendor community work toward AI-based advancements.

These are just two example scenarios. Many more opportunities exist for managers to automate, including trade processes, derivatives and collateral management, reconciliation, and corporate actions processes. In 2025, we expect firms to implement AI-based technology to improve their access to data and automate workflows. We also predict that demonstrable gains from automation will fuel further investment in AI-based use cases.