BNY's AI Strategy & Enterprise Adoption
BNY has made a bold, large-scale commitment to artificial intelligence, investing over $4 billion in technology in 2025, with a significant proportion directed toward AI integration and organisational adoption.
Insight Investment, a specialist asset-management firm within the BNY Investments division, operates within this enterprise-wide AI transformation.
At the core of BNY's AI strategy is Eliza, an internal AI platform available to all employees. Eliza provides access to multiple large language models (including ChatGPT and Claude) and enables employees to create personalised AI agents tailored to their individual workflows. To date, the organisation has deployed approximately 140 “digital employees”, automating routine and repetitive tasks that were previously performed by human staff.
In parallel, BNY's Microsoft-based technology stack enables deep integration of Microsoft Copilot across everyday tools. Copilot is embedded throughout Microsoft applications and can securely surface insights from enterprise data sources including SharePoint, Azure, Atlassian Confluence and Jira, as well as emails and Microsoft Teams conversations—making it particularly effective for cross-system information retrieval and synthesis.
As part of the firm's mandatory AI enablement programme—totalling approximately 80 hours of formal AI training per employee — I designed and built a personal AI agent to support discovery and design activities within the UX and product design process, applying AI directly to real-world design workflows rather than theoretical use cases.
Press releases & case studies
- BNY Press release - Unlocking Value with BNY's Enterprise AI Platform - 20-Oct-2025
- OpenAI case study - BNY builds "AI for everyone, everywhere" with OpenAI - 12-Dec-2025
News reports
AI Education and training
Mandatory basic and advanced training in the form of a mix of internal and external-training provider courses covering AI in general, and AI-specifics for BNY's internal Eliza platform.
Some key topics covered:
- Introduction to AI Agents (course via DataCamp)
- Understanding Prompt Engineering (course via DataCamp)
- AI Ethics (course via DataCamp)
- AI Guardrails (Input, Tool-based, Output)
- BNY Classical ML (Machine Learning) Applications in Action
- BNY Generative AI Applications in Action
Some certificates of accomplishment:
HCI (Human Computer Interaction) for AI Systems Design from the University of Cambridge
Covering the design of innovative systems that blend automation, intuitive user experiences, ethics and risk management — to help shape the future of Human-AI Interaction.
Some key topics covered:
- Enabling Human-AI Interaction
- Function Modelling
- Function Structures
- Function Analysis Systems Technique (FAST) Diagrams
- Concept Generation & Evaluation
- Automation
- Mixed-Initiative Systems, Teaming & Partnerships
- Understanding and Interpreting AI
- Decision-making in a Dynamical System
- Heuristics and Cognitive Biases
- Interpretable AI for Decision-making
- Managing Control and Agency
- Measuring Agency
- Control
- Human-in-the-Loop
- Interactive Machine Learning and Machine Teaching
- Governance of Human-AI Systems
- Defining Risks and Hazards
- Hazard Identification and Risk Assessment Methods
- System Boundaries and Mapping
- Alignment
- Principles for Safe and Ethical AI Systems
- Evaluating Human-AI Systems
- Guidelines for Human-AI Interaction
- Deployment Studies
Final Scoring
Passed with a final project assignment score of 86.7%, with an overall final course score of 94%.
