Broker Research Licensing Emerges as AI’s Biggest Buy-Side Bottleneck

Buy-side firms have largely solved the AI deployment problem. Their next bottleneck is broker research licensing, which often prevents firms from feeding one of their most valuable information sources into internal AI systems.

Enterprise AI Is Already in Place

The survey by Substantive Research and Aiera of 35 of the world’s largest asset managers suggests the industry has moved beyond experimentation with generative AI.

Seventy-seven percent of respondents said their firms have already deployed enterprise-wide AI platforms such as ChatGPT or Claude. More than a third said deployment took four to six months, while another 20% spent more than six months on approval, compliance and onboarding.

Alongside general-purpose LLMs, just over a quarter of respondents are evaluating or have already adopted AI platforms built specifically for investment research.

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Broker Research Remains Outside AI Systems

Despite widespread AI adoption, firms still cannot use the content they value most inside those systems. Seventy-seven percent of respondents identified broker research as the most valuable source to receive through machine-readable feeds, ahead of earnings transcripts at 57% and market data at 42%.

However, broker research has largely been designed for consumption by human analysts through PDF reports or proprietary portals, rather than for automatic ingestion by enterprise AI systems.

Existing licensing and entitlement frameworks often do not accommodate machine-readable AI workflows, making it difficult for asset managers to integrate research into internal LLMs.

The issue ranked as the biggest barrier to wider adoption of direct research and data feeds, cited by 69% of respondents. Compliance and entitlement requirements followed at 54%.

Machine-Readable Research Becomes a Commercial Issue

“Buy-side firms overwhelmingly want broker research inside their AI workflows, but today’s licensing, entitlement and compliance frameworks weren’t designed for machine-readable, AI-driven environments,” said Gavin Skinner, COO of Aiera.

“Modernising how premium content is governed and delivered is essential to unlocking AI’s full potential while protecting the intellectual property, transparency and commercial value that underpin the research ecosystem.”

For brokers, the survey points to demand both for the research itself, and for new ways of licensing and delivering it. As asset managers build internal AI infrastructure, machine-readable distribution could become an increasingly important part of the sell side’s research offering.

The issue is also attracting regulatory attention: this week, the UK’s Financial Conduct Authority published its first comprehensive review of AI in retail financial services, highlighting AI governance as an emerging supervisory priority.