Singletrack Q3 2026 Benchmark Insights: Navigating the AI Efficiency Paradox

What is the AI Efficiency Paradox?

The institutional capital markets industry is experiencing a profound transformation. While operational the Singletrack Quarterly Benchmark point towards a rapidly automating ecosystem—where research reports are growing text-heavy, delivery channels favour aggregators, and sales activity pivots to asynchronous messaging—the underlying driver of commercial value remains completely unchanged: human trust and actionable alpha.

This dynamic defines the AI Efficiency Paradox. As distribution, creation, and workflow channels scale through machine-driven efficiency, the parts of the business that machines cannot replicate—relationship-driven advisory, nuanced judgment, and differentiated perspective—become disproportionately valuable.

Key perspectives on this paradox are from:

• Katie Tomlinson Broder (KTB Advisory): Framed the paradox around the divergence between operational metrics and client pay-drivers. While efficiency metrics suggest a business rebuilding itself around machines, buy-side monetisation still relies on human trust and non-scalable alpha.
• Brijesh Malkan (Singletrack): Highlighted that AI raises the baseline of what is considered “commoditised” research. Efficiency allows lower-tier tasks to be automated, forcing firms to re-evaluate their unique value propositions.
• Julia Ashworth (Retail Research / Euro IRP): Noted that while AI provides operational flexibility, independent research providers (IRPs) and sell-side desks remain fundamental relationship-led service businesses where content serves as a gateway to broader adviser engagement.
• James Ferguson (Loop Capital): Emphasised that efficiency tools help sales desks manage wide coverage, but long-term client retention depends on historical context and high-touch execution.
• Vineet Jobanputra (Singletrack): Pointed out that the Singletrack Quarterly Benchmark data validates both sides of the paradox—higher engagement correlates with structured, long-form content, yet delivery is rapidly fragmenting across digital touchpoints.

Themes

The AI Efficiency Paradox was examined through the lens of three advisory business areas:

• Research Production vs Consumption: The AI Format Shift
• Client Engagement: Asynchronous and Targeted Servicing
• Corporate Access & Commercial Safeguards

1. Research Production vs Consumption: The AI Format Shift

Q1 Benchmark trends on report composition, engagement, and delivery channels

• Vineet Jobanputra: Content length increased by 15% from early 2024 to mid-2025, maintaining sustained growth through Q3 2026. The Singletrack Quarterly Benchmarkdata shows a moderate positive correlation between report length and engagement, as well as higher engagement for reports with structured tables and figures. Aggregators and portals now account for 35% of research consumption (aggregators and portals combined reach 62% of downloads), while direct email consumption fell from 44% to 37%.
• Katie Tomlinson Broder: Text now occupies 59% of report pages (up from 51%), replacing standalone charts and images. Creation-to-submission speed dropped to 7.1 hours (a two-year low), while average company coverage per analyst rose 12% to 12.6 companies.

Q2 Are research heads intentionally formatting for machine ingestion?

• Brijesh Malkan: The notion that research is being written solely for Large Language Models (LLMs) or transformed into “clickbait” should be dismissed. Instead, structuring and componentising research improves discoverability for human readers using AI search tools. Componentised framework models enable investment decision-makers to interrogate research content effectively across aggregators, emails, and LLM interfaces.
• Julia Ashworth: Research is still written primarily to be read as part of a holistic advisory service. However, providers must remain agile, delivering text, CSVs, and structured component files so buy-side clients can ingest research using their preferred analytical tools.
• James Ferguson: Buy-side models will naturally adjust algorithms over time—much like search engines—to surface only high-quality, componentised content, pushing the desk away from superficial formatting hacks.

Q3 Beyond AI, what structural shifts are driving report composition?

• Julia Ashworth: There is a pivot towards thematic, data-driven, and repeatable macro research. Single-stock notes are increasingly contextualised within broader sector trends, satisfying buy-side demand for comprehensive industry overviews alongside regulatory and payment unbundling pressures.
• Brijesh Malkan: The industry is moving to connecting macro, sector, and single-stock models into unified narrative threads. Additionally, natural language capabilities allow firms to unlock value from their multi-decade archive tail, comparing current economic indicators against historical market cycles.
• James Ferguson: Longitudinal survey and primary research data are vitally important. Buy-side clients extract value from trend inflection points across historical datasets rather than isolated single-point snapshots.

Q4 Is the AI adoption gap between large and small firms narrowing or widening?

• Julia Ashworth: Smaller independent research providers (IRPs) possess organisational agility, allowing them to rapidly pilot new platforms and infrastructure without legacy friction. However, commercial hurdles around access and pricing remain key drivers alongside AI implementation.
• Brijesh Malkan: Enterprise AI strategy is unifying across firm sizes. Almost all desks have moved past unapproved desktop tools to foundational enterprise models. The distinction now lies in strategy: large global banks tend to build proprietary AI teams, whereas mid-sized and boutique firms leverage specialised software vendors.

2. Client Engagement: Asynchronous and Targeted Servicing

Q1 Engagement channels: Changed behaviour vs. improved data capture

• Vineet Jobanputra: Asynchronous communication (email and instant messaging) comprises 46% of total sales interactions. Instant messaging (IM) accounts for 40% of these asynchronous touchpoints—dominated by Bloomberg. Crucially, 33% of IM interactions are now captured automatically via system integrations rather than manual logging. Direct phone calls still represent 42% of interactions.
• Brijesh Malkan & Julia Ashworth: The uptick in IM statistics is heavily driven by automated capture capabilities (such as Singletrack’s Bloomberg integration). Ambient capture gives data higher internal utility for sales desks without adding administrative friction.
• James Ferguson: Capturing data is only beneficial if it improves team-wide visibility—such as keeping regional sales desks or product specialists aligned during active deal workflows or client calls.

Q2 Is the traditional cold-call-and-broadcast model dead?

• James Ferguson: Active prospecting remains mandatory. With hedge fund launches, portfolio manager turnover, and capital shifts, failing to actively prospect leaves sales desks vulnerable to account attrition.
• Julia Ashworth: While mass cold calling is ineffective, targeted outreach using relevant, data-backed research to prospective accounts remains a core pillar of relationship-led institutional sales.

Q3 Balancing regulatory mass distribution with targeted follow-ups

• Julia Ashworth & Katie Tomlinson Broder: Regulatory frameworks dictate simultaneous broadcast of research to all entitled clients. However, the commercial difference lies in post-distribution engagement—using consumption data to drive tailored sales follow-ups and high-touch interactions.
• Brijesh Malkan: Leading desks use email bodies to surface high-value insights directly, utilising ambient analytics to guide sales workflows towards clients demonstrating high intent.

3. Corporate Access & Commercial Safeguards

Q1 Meeting volumes and regional benchmarks (US vs. Europe)

• Vineet Jobanputra & Katie Tomlinson Broder: Singletrack Quarterly Benchmark data indicates corporate access desks are running larger events to maximise scale. While overall participant volume per event has expanded, access to scarce one-to-one corporate management slots remains highly constrained.
• Julia Ashworth: European market dynamics continue to be shaped by unbundling rules and explicit corporate access pricing, requiring tight attribution between corporate interaction volumes and buy-side commission allocations.

Q2 Managing scarce 1-to-1 slots and AI allocation workflows

• Brijesh Malkan: Desks are leveraging intelligent allocation engines to score client relationships based on historical commission, research engagement, and trading velocity. AI models help prioritise high-value client entitlement without manual bias.
• James Ferguson: While algorithms assist slot allocation, human intervention remains crucial to balance long-term institutional relationships against short-term payment metrics.

Q3 Critical risks: IP protection, content attribution, and commercial safeguards

As buy-side institutions deploy internal AI engines to ingest sell-side and independent research, significant operational, legal, and commercial risks emerge:

Risk Area	Participant Perspective & Analysis
Content Attribution & Value Leakage	Brijesh Malkan: If an LLM ingests research and outputs a synthesised summary without attribution, the originator loses brand visibility and monetisation entitlement. Research must be componentised with metadata headers to guarantee attribution across buy-side models.
Regulatory & Compliance Auditability	Brijesh Malkan & Julia Ashworth: Regulators are increasing scrutiny on how investment recommendations are derived. Desks must retain audit trails proving whether a thesis originated from human analyst research or machine-generated synthesis, especially as emails and chats get ingested into third-party tools.
IP Theft vs. Multi-Channel Monetisation	Julia Ashworth & Katie Tomlinson Broder: Protecting IP in open aggregator environments requires robust entitlement permissioning. Providers must ensure that automated ingestion feeds are tied directly to commercial agreements and subscription tiers.

 

Conclusion and summary

The Singletrack Quarterly Benchmark discussion underscores that while AI and automation provide powerful efficiency across research formatting, distribution tracking, and interaction logging, they do not replace the primary engine of capital markets value: trusted adviser relationships.

Winning capital markets teams are adapting by:

1. Componentising Content: Structuring research so it is discoverable by AI models while delivering immediate, actionable depth to human investors.
2. Executing Multi-Channel Distribution: Meeting buy-side consumption preferences simultaneously across email, portals, aggregators, and LLM feeds.
3. Maximising Data Capture for High-Touch Action: Utilising ambient capture tools (e.g. Bloomberg integration) to remove logging friction, allowing sales desks to spend more time

Ready to dive deeper into the data?

The AI Efficiency Paradox is reshaping how capital markets operate. Uncover the full data sets, regional variations, and strategic panel insights to benchmark your own firm’s performance.

 Watch the full webinar recording

Download The Singletrack Quarterly Benchmark Report Q3 2026