Part Two
Innovation : From Insights to Impacts
AI in Action: Productivity Gains and Practical Applications
AI's transformative potential captivated InvestOps USA attendees, filling the room with those eager to explore its practical applications in investment operations
Panellists emphasised that AI, particularly generative AI, is primarily a tool for productivity enhancement, not job replacement.
As one stated, "AI improves how we work, increasing capacity. We can now get a Gen AI summary of key points, rather than reading countless documents."
This shift significantly reduces task completion times, with some tasks now taking three days instead of twelve.
AI is being applied across various areas of investment operations, including document processing, data cleaning and analysis, predictive analytics, compliance checks, and portfolio commentary. Its ability to summarise large text volumes, generate presentations, and streamline RFP responses demonstrates its efficiency. Key areas where AI adds value include:
- Document-Heavy Processes: Efficiently summarising texts and creating presentations.
- Data Analysis: Cleaning data and identifying behavioural patterns.
- Predictive Analytics: Forecasting potential issues like transaction failures.
- Compliance and Portfolio Commentary: Streamlining compliance and reducing portfolio commentary time.
Audience poll: Are you using AI in your firm beyond personal productivity tools like Microsoft co-pilot?
Yes
No
Don't Know
However, implementing AI presents challenges, notably data security and ethical standards.
Organisations must control data flow, avoiding sensitive uploads to external platforms like ChatGPT.
A problem-focused approach is essential; AI should address specific challenges and be validated against existing processes.
Organisations are adopting diverse AI implementation strategies.
Some develop in-house solutions for control, while others establish dedicated AI teams for oversight and alignment with business objectives.This centralised approach facilitates rapid identification of improvement areas and strategic adaptation.
AI is poised to transform investment operations, offering efficiency gains, enhanced analysis, and improved decision-making.
Successful adoption requires careful planning and validation in this evolving sector."
Audience poll: Do you feel your firm is ready to support the use of AI beyond tools like Microsoft co-pilot?
Yes
No
Don't Know
Audience poll: What is the top challenge with data that you are facing with implementing AI or ML at your firm?
A: No Challenges at all - Data is a Strategic Asset
B: Data Quality (Timeliness, Coverage, Errors)
C: Trying to Link Datasets Together (Identifiers Across Providers Don't Match)
D: We Don't Have Enough Historical Data
E: We have Challenges in B, C and D
