FIS Toronto 2024

Turning AI loose inside asset-owner organisations

(L-R) David Bell (top1000funds.com), Ari Shaanan, Jacky Chen, Peter Strikwerda (on screen)

The rise of artificial intelligence as an actually useful business tool presents multiple issues for asset owners. They must take stock of the impact of AI on the businesses they invest in on the one hand, while at the same time assessing the implications of AI for their own businesses, including making investment decisions. 

The Fiduciary Investors Symposium in Toronto earlier heard from Geoffrey Taber Chair in Entrepreneurship and Innovation and Professor of Strategic Management, University of Toronto, Rotman School of Management Ajay Agrawal that at its current stage of development, AI is typically applied in one of two ways. 

The first is a short-term, specific use-case approach that enhances productivity by improving an existing process, but otherwise leaves the process largely unchanged; and the second is more systems focused, where entire workflows are reimagined and re-engineered with AI at their core. 

APG Asset Management global head of digitalisation and innovation, Peter Strikwerda, said that “the true answer is it’s a bit of a mix”. 

“In practice, what you see is sometimes just very small problems in a process on automation, on specific information gathering or analysis or whatever we’re trying to fix, that typically fits the use-case driven approach,” he said. 

“We take small areas, but I think increasingly you see that bigger areas, and maybe that you could call that a system-type of approach, are being addressed. 

“One example…is the whole process of information gathering, organising, standardising analysing, predicting [and] decision making in private markets, because it’s very different from public markets in terms of data availability, standardisation, quality, et cetera. I’m not really sure if you could call that ‘systematic’, but what I see there is that the width of the usages is broader.” 

Jacky Chen

OPTrust director of total fund completion portfolio strategies Jacky Chen said there are “a few things that I would recommend people to think about” about applying AI to systems and processes in the short term. 

“One is how to get started,” Chen said. 

“If you don’t get started, you’re never going to be able to accumulate the knowledge to discover what are some of the key workflows. Inaction at this point is not an action because you really have to think about what are some of the early wins. You have to get started in order to accumulate the knowledge, get some skin in the game, in the short term.  

“There are already some low hanging fruits that you can really do for you to improve the operational efficiency standpoint. 

“You need to get your hands dirty in order to start doing that.” 

Chen said that when considering the long-term applications of AI, it is important for asset owners to consider carefully who they’re working with. He said that it is unlikely asset owners will have “a whole division that just building this type of technology”. 

“A lot of time you’re going to be buying, and who are the partner[s] that you’re going to work with?” Chen said. 

“There’s a bit of competition going on, and once there’s established a first mover advantage, we need to think about who’s going to be the second and the third mover. A lot of time, you have to find a proven winner who has the ability to continue to pivot.  

“Internally, you have to remain very nimble and agile in your approach, and externally, if you’re working with a partner on this, you have to remain very cautious about who you’re working with, and continue to pick the right the people that you believe that as it’s continued to evolve…they will be the provider that can help you to reach there.” 

PSP Investments managing director digital of innovation and private market solutions, Ari Shaanan, said that PSP, like other asset owners, is currently focused on short-term applications of AI but, echoing what APG’s Strikwerda suggested, is finding the application of AI becoming broader. 

Ari Shaanan

“The applications are growing both in breadth and in what you’re able to do”. 

“And also in size and scope, it just feels like it’s more and more accessible now,” Shaanan said, which is in part a function of more readily available data. 

“Clearly there’s just more data available just being, practically speaking, sold by third parties, vendors that we could all now leverage,” he said. “[It’s] much more practical, easier to get in the door these days.” 

Shaanan said there’s a second aspect of AI applications relevant to asset owners focused on generative AI and both large and small language models.  

Small language models manifest as agents that can carry our specific tasks, while large language models can be developed to undertake tasks such as research on specific industries, sectors or geographies. 

“You can build in an LLM internally to do something like that, and…then run an analysis on fundamentals. And you could run an analysis on how that fits in the portfolio. And you could actually stitch together now four or five or six different agents, and have those working together. 

“And I think that’s more and more the world we’re going to head in where it’s not just one answer for everything in one model running, call it portfolios, but it’s many agents that can be stitched together that can be leveraged by analysts and our PMs.” 

APG’s Strikwerda said the starting point for the organisation’s adoption of AI is its broader business strategy, and while it’s willing to test AI applications internally it’s also fully prepared to kill off a test if it does not achieve the expected result. 

“We look at the application of AI as a means, we judge it, as a means to these ends,” Strikwerda said. 

“If you’re an alpha strategy, we look at AI as an opportunity to generate alpha, always combined with data.  

“When you look at running index products, it’s maybe not about alpha, it’s about having a more efficient operation to support that.” 

“We never approach it from the AI, we approach it from what we are for, our purposes company, and then see how we can apply it…and then try to be able to gather proof points, support that and expand from that,” Strikwerda said. 

“Or kill it, if it goes south. That’s also what’s happened.” 

Strikwerda said APG’s strategy also includes being leaders in responsible investing, and there are obvious opportunities there for the application of AI because of the state of available data. 

“That’s where I see a lot of growth potential, and not yet a level playing field,” Strikwerda said. 

“And so the commoditisation…in capital markets, you see that data is very much commoditised to a large extent, [but] in responsible investing that’s still growing.” 

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