Licensing restrictions and compliance hurdles are slowing the flow of broker research into asset managers’ AI systems, even as adoption accelerates, finds new Substantive Research and Aiera report.
While buy-side GenAI adoption has surged, the uptake remains hindered by broker research licensing restrictions, according to new research.
A new report from Substantive Research and Aiera has found that despite use cases rising to 77% among the buy-side, broker/data licensing restrictions are currently the biggest barrier preventing adoption of direct research/data feeds (69%).
This was followed by compliance and entitlements (54%). In terms of timeliness, over a third (37%) of respondents confirmed that approving, adopting and onboarding models takes between four and six months, while for 20% it took more than six months.
Only 17% responded more timely reactions of one to three months onboarding time.
The findings further highlighted that 77% of buy-side respondents consider broker research to be the most valuable input to receive as machine-readable feeds directly into their internal AI systems. This was followed by earnings transcripts (57%) and market data (42%).
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Speaking to The TRADE, Mike Carrodus, chief executive, Substantive Research highlighted another angle in light of these findings, specifically the impact of AI adoption on commercial relationships with the sell-side.
He explains: “The buy-side has mobilised to ensure that they remain competitive as the industry rapidly gears up from an AI perspective. What hasn’t been solved yet is how that affects their commercial relationships with the sell-side. The only easy conversations will be with research providers where they are viewed as top tier clients – with anyone else, content feeds into their LLMs will potentially come with a hefty price.”
“Buy-side research budgets are already under pressure, so it’s understandable that they wouldn’t welcome a new set of licensing accompanied by new costs. And they are banking on a fear from the sell-side that being frozen out of an asset manager’s LLM would be a very cold place to be in future. On the other hand, many on the sell-side feel that capitulation on this issue would be a step too far, especially after Mifid II’s enduring deflationary effects on research pricing.”
Off the back of recent – and highly publicised – advances in large language models (LLMs) asset managers are now focused on how AI can improve processes including: research discovery, insight generation and analyst productivity in a bespoke manner.
The report found that just over a quarter of buy-side firms are either evaluating – or already have implemented – vertically integrated AI platforms that specialise in finance/investment research.
While 44% view specialised platforms as “potentially strategic long-term partners”, another 44% remain in the evaluation stage but are as yet undecided.
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Elsewhere, Substantive Research and Aiera pointed to how adoption is taking different forms across firms – influenced by factors such as how ambitious they are and how long implementation takes from compliance and onboarding perspectives.
Additionally, the question of whether an enterprise-wide approach or investment-research focused AI platforms are most effective remains unanswered for some.
Gavin Skinner, chief operating officer, Aiera, tells The TRADE that the findings have unquestionably highlighted a key shift across the market.
“Buy-side firms aren’t asking whether AI belongs in the research process. They’re asking how to bring their most trusted information sources into AI workflows securely and compliantly. The future of investment research depends on creating an ecosystem where premium content can be accessed intelligently while fully respecting the rights and commercial interests of content owners.”
The report by Substantive Research and Aiera surveyed 35 of the largest global asset managers.