Learn AI for Investment Management Firms: equitably.ai in partnership with the Investment Association
AI offers powerful ways for investment management firms to improve investment outcomes at lower costs and risks, but how do investment management professionals learn AI for investment management to apply AI to their roles and in their firms? in a practical, return on investment (ROI) and risk-assumed way?
They come to their industry body, the Investment Association and equitably.ai, who are partnering to bring deep industry insights -including expert input of the Investment Association’s policy/innovation teams – and AI skills together for practical AI learning that investment professionals can apply when back at their desk.
In case you are still unsure about the benefits of AI learning. A reminder that the percentage of UK business leaders planning to redirect investment from staff to AI stands at 51% according to research from Boston Consulting Group as reported by the Financial Times. Have a look at our latest and past learning delivered below and note how the AI learning continues to evolve every month to keep pace with the latest in AI.
Latest: October Training
In October, we delivered another of our successful Fundamentals of Practical AI for Investment Managers, coming to our 3rd year of delivery for our partners, IA Training at The Investment Association.
For the training, we had a major revamp on our presentation and discussed the following:
Agentic AI & Autonomous Multi-Agent BAU Workflows, Shifting from Dispersed AI Adoption to Systematic Enterprise Deployment Governance, Unlocking Measurable ROI: What Does a Best-In-Class AI Deployment Look Like?, Automating End-to-End Workflows & Client Reporting, AI for Investment Research, Market Intelligence & Synthesis, Mitigating Cyber & InfoSec Vulnerabilities in LLM Deployments, Streamlining Fund Audits, Financial Reporting & Regulatory Filings, Navigating Regulations for AI, Practical AI Quality Frameworks Moving Beyond Pure Governance, Future Direction of AI and How to Plan for It and so much more.
AI is not stopping – even after frontier model companies asked governments to slow it – so it’s best to be in the know rather than fall behind.
June Training
In June we held another successful AI training with a good mix of investment management professionals from investment operations, performance reporting, analytics, marketing, sustainability and responsible investments, strategy, innovation and non-executive directors.
New AI learning delivered by John Paul included: how to objectively benchmark AI models, frameworks for assessing AI competency, guardrails and governance for the growing agentic AI use, AI marketing use cases using latest models, demos of taking existing video to generate new video content – showed investment product explainer videos (including compliance elements) – using AI for coding for better quality AI, updates from equitably.ai discussions across London Tech Week, the AI Summit in London, and the Investment Association’s annual conference.
All reinforce a clear message: successful AI adoption is not only about access to better AI models but about a quality AI deployment.
April Training
A core theme during our April training was a shift in perspective, rather than asking what AI can do for us, we explored what investment products actually look like once AI becomes an engine. The session provided essential AI case studies and use cases to help investment managers bridge the gap between theoretical potential and practical applications of AI.
Participants discussed the governance paradox, where the lack of confidence in outcomes often leads to investment management firms getting stuck. To address this, equitably.ai works with firms to move past general concepts and focus on specific Investment Management AI use cases and AI outcomes, such as the preparation of investment memos or automating ESG data workflows.
We were pleased to have a member of the IA policy team, Lawrence Baker, join the training session with a great discussion about taking a risk adjusted approach to AI similar to what the investor sector uses for their investment management. Our experts highlighted that if an organisation is unable to quantify the return on a deployment, they cannot effectively quantify the risk management required for it.
In the section covering the direction of AI, we shared the latest research on the impact of AI on roles in investment management. We discussed how AI is predicted to reshape teams into more “diamond-shaped” organisations, where experienced professionals, AI-enabled workflows, and specialist oversight become more important than traditional pyramids of junior execution.
The training benefited from a vibrant mix of peer-learning perspectives, with attendees representing a broad spectrum of professionals from various asset classes and functions in investment management including Pictet Asset Management, Allianz Global Investors, Ruffer, Nomura Asset Management, De Lisle Partners, and TwentyFour Asset Management, and many more.
March Training
In March we held an training session focused on the evolving landscape of AI within the financial sector.
During the session Dr. Idir Ouahes, provided an update on Cybersecurity and AI Risk Management. Including a case study of a recent AI security risk illustrating what can happen when AI agent delegation goes wrong. It related to Summer Yue, an executive at Meta, using OpenClaw, an open-source AI agent running on a local Macbook and controlled via WhatsApp. Despite her explicit instructions not to take action without approval, the agent experienced context compaction, a process where it deleted its own safety constraints to save memory. This technical failure led the agent to begin a mass-deletion of Ms. Yue’s email inbox, ignoring STOP commands sent from her phone. The incident served attendees as a stark reminder of the critical need for robust AI governance when it comes to AI agents in investment management, including hard-coded kill switches rather than relying solely on natural language instructions.
February Training
equitably.ai returned to the Investment Association to deliver our flagship Fundamentals of Practical AI programme, ensuring all investment professionals are equipped to a basic level in AI literacy and to start the parth of harnessing potential of AI in a risk-managed way.
While the core and proven learning aims remain constant, with the speed in AI the course is reviewed every time and iteratively updated to reflect the rapid deployment of AI in investment management.
To help attendees better learn AI for investment management, in each session we aim to invite guest speakers specialised in a particular AI domain.
AI guest speakers have included: Simon Bollans of Stephenson Harwood with the latest in the shifting AI regulatory landscape globally. Dr Aneesh Banerjee from Bayes Business School sharring the latest research in value-based method of AI business case development, Rashid Adam, COO of Findlay Park Investment Management, sharring their enterprise AI deployment experience journey from generative AI to agentic AI and importantly key lessons such as a process based approach, leveraging talent from universities, managing data suppliers and much more.
January Training
We were delighted to host an immersive training session dedicated to helping investment management firms navigate the practical uses of AI.
We worked with attendees learn AI for investment management by finding AI applications in their daily operations.
In this session we felt there was fantastic peer-learning, where participants from a wide range of investment management firms, asset classes and functions (finance, risk, distribution etc.) shared their AI challenges in the context of their function sparking a vibrant dialogue about methods discussed for maximising potential and managing risks of AI.
The session concluded with a good drive for attendees wanting to apply and build their AI learning in their decision-making and processes.
As part of equitably.ai committment to practical learning, we introduce Investment Management AI case studies. In this and other sessions we have covered investment processes for ESG investing and AI thematic investment.
Testimonials and Feedback
‘A really enjoyable and informative session … it was great to hear from others in the cohort about their experiences…very knowledgeable and an excellent presenter’
‘It provided valuable insights into how AI can be applied effectively within my role, and helped generate a number of ideas on how I can use AI to support and enhance some tasks.’
‘a comprehensive overview of the rapidly evolving AI landscape, combining informative presentations with interactive group discussions. I found it highly beneficial.’
‘Really enjoyed the (practical) exercise to feel more engaged during the session as otherwise people are scared to participate.’
‘A fascinating and interactive session. John Paul really knew his stuff. Truly top notch.’
‘Really useful session and content. It was also great to have a variety of speakers across different industries and experiences. ‘
‘Good informative course, really enjoyed it. The case study was very interesting and wrapped it together.’
What makes our AI learning different?
When investment professionals come to learn AI for investment management firms, we aim to deliver practical AI learning that is customised for the investment management sector. We also ensure a balanced view of AI through professional quality AI principles to deliver return on investment (ROI) from AI, with minimised risks. Our AI learning is different to many in that it is:
- Customised to Investment Management Context: We deliver our learning together with your industry body, the Investment Association, collaborating with IA policy and other teams. You will work on case studies and solve investment management challenges.
- Quality AI at Core: Investment management is a regulated sector. We help you learn to use proven professional quality competencies and other frameworks aligned to regulations to manage risks of AI while maximising ROI.
- Practical Tools and Methods: Hands-on practice using AI tools and frameworks during the training.
- AI Use Case and AI Case Studies: We work hard to share with you AI use cases, share case studies – including special guest speakers from your industry – from investment management.
- 1:1 Expert Clinics: Work directly with AI experts to address your unique challenges and identify impactful solutions.
- Peer-based learning: You get the opportunity to network and learn from fellow investment management professionals.
See below for some of the many learnings we have delivered together with the Investment Association.
Do you or firm want to learn about AI for investment management?
Firstly don’t forget that your current and target AI competencies are key. Contact us for a copy of our AI competency framework.
We deliver the long established Fundamentals of Practical AI for Investment Management Firms along with advanced practical AI customised to various support functions and agentic AI. Both as public courses and inhouse. Contact us or the Investment Association Training Hub for a quick chat.