Navigating Agentic and other AI in Investment Management at the Investment Association Conference
When considering AI in investment management, the Investment Association’s (IA) Annual Conference is a must and a powerful reminder of our industry’s leadership in AI.
As the flagship event, the 2025 IA annual conference: Engine for Growth brought together more than 600 investment professionals spanning the pensions industry, investment management, government, and regulatory bodies, who manage over £9 trillion in assets.
equitably.ai, a member of the Investment Association’s Fintech Hub (The Engine), was delighted to exhibit at the conference and host a special session on AI in investment management to share AI learning equitably.ai delivers for the IA.
Key Insights from the IA Annual Conference 2025
Technology and AI in Investment Management
There was a shift of AI in investment management from AI for productivity (co-pilot licenses) to robust AI use cases (often agentic AI) that deliver clear business performance in processes.
Operational Excellence: Firms are prioritising AI for automation, compliance, and streamlining the preparation of investment memos.
AI Governance: Implementation strategies include human-in-the-loop systems and kill switches for agentic AI to manage risk without stifling innovation.
Global Strategy and Talent
The UK continues to refine its position as a global Investment Management and AI hub.
Private Markets: There was a strong consensus on expanding retail investor access to private market assets.
Future Workforce: Organisations are addressing the skills gap by upskilling staff for AI and starting to ask questions about the AI competencies in place and those needed.
Regulatory Evolution
The FCA is transitioning toward a predictable and purposeful regulatory philosophy.
Strategy: The 5-Year Strategy focuses on reducing unnecessary burdens and simplifying transparency.
Risk Appetite: Industry leaders advocate for a “regulatory reset” to move away from extreme risk aversion and restore market vibrancy.
The equitably.ai IA Training
equitably.ai has the privilege to lead a breakout session titled Beyond the AI Noise with extracts from AI learning we deliver for the Investment Association, with a focus on the direction of AI – in particular, agentic AI – and best practice when considering deploying AI.
The Shift Towards Agentic AI
equitably.ai shared research on a key direction of AI in investment management, Agentic AI. Unlike passive models, AI agents have agency, the ability to autonomously set goals, make decisions, execute multi-step workflows, and collaborate with other tools with minimal human intervention.
We demonstrated this through a live investment case study comparing an off-the-shelf generative AI model with an Agentic AI system. The task involved an equity valuation analysis for an LSE-listed drinks company, examining how alcohol duty increases impact pricing, consumer demand, EBITDA, and discounted cash flow (DCF) valuations.
Best-in-Class AI Governance
equitably.ai shared research that as AI use cases become more autonomous, adhering to regulatory frameworks is essential for risk reduction and maximising ROI. Success requires treating AI as a process improvement, at a minimum and ideally as a digital transformation rather than just a technological upgrade.
A robust AI programme must integrate robust AI governance, including four regulatory pillars:
- PRIN (Principles for Businesses): Ensuring integrity and diligence while adhering to Consumer Duty.
- SYSC (Systems and Controls): Demanding robust governance and operational processes.
- PROD (Product Governance): Managing AI-driven products to ensure they meet market needs.
- COBS (Conduct of Business): Mandating clear communications in the client’s best interests.
The Path to AI Impact
AI in investment management is putting UK investment management sector at a pivotal juncture. To capitalise on the transformative potential of AI, firms must actively invest in AI and AI literacy while ensuring return on investment (ROI) and robust governance for managing risks. These together will be the defining factor between firms that merely experiment and those that achieve a lasting competitive advantage.
Do you have questions like: where should you start with AI?, or how to assess your AI capability?, or how do you close internal AI competency gaps? or what is the right kind of AI learning? or how can you make sure you get risk-adjusted ROI from AI? Contact Us for a chat.