BlackRock Q2 2026 Earnings Show Aladdin and Preqin Synergies Drive AI-Enabled Platform Growth

BlackRock: Trends in Aladdin & Preqin, synergy progress, demand drivers tied to transparency, and the role of AI

1) What trends are being seen in and around Aladdin and Preqin?

Aladdin: technology-led growth and client acceleration

Management characterized the most recent quarter as strong, with 13% revenue growth and 15% ACV growth in Aladdin, while emphasizing that the technology and subscription revenue line is the primary growth engine. ¹ They also stated that technology is the main engine for investment performance, operating leverage, and client experience, and that clients are investing more in technology and accelerating tech spend. ¹

A second key trend is consolidation of vendors/providers: management said clients are consolidating to leverage fewer providers with deep integrations across fintech and data ecosystems, and they want to work with BlackRock because it can span public and private markets across a broader portfolio of services. ¹

Preqin (and eFront): value proposition strengthened by regulatory and private-markets volatility

For Preqin/eFront, management linked stronger momentum to market/regulatory “accelerants”:

• Regulatory landscape moves and “gyrations in the private markets” were described as real accelerants for Preqin, eFront, and Aladdin more broadly. ¹
• Management specifically cited the Department of Labor’s proposed Safe Harbor rule as “clear” that fiduciary standards will require rigorous data performance benchmarking for private assets in 401(k), positioning Preqin as a transparency-enabler. ¹

They also argued that investor scrutiny is shifting toward what the underlying exposure really is (e.g., whether holdings are “software-like,” “healthcare IT,” etc.), and said this need for more transparency is a key accelerant for Preqin. ¹

2) How are synergies progressing?

Cross-platform integration and client expansion

While the excerpts do not provide a quantified “synergies” table (e.g., cost savings and incremental revenue totals), management described the synergy thesis and progress in operational terms:

• They described the combination of Preqin with Aladdin and eFront as complementary and said it is delivering more value for clients and BlackRock. ¹
• They said BlackRock is executing on opportunities to bring the benefits of Aladdin to new clients and expand relationships with existing clients. ¹
• Management also framed a multi-year integration destination: BlackRock aims to be the technology provider for a seamless blending of public and private markets, and said they are not 100% there yet but see demand and pending demand for such cross-market analytics on a single common platform as “very, very important.” ²

In short: the excerpts emphasize product/platform integration and commercial cross-sell rather than a specific synergy realization figure. ¹²

3) How is demand progressing given calls for more transparency in private markets?

Management’s view is that transparency initiatives are supporting demand—especially for Preqin:

• They said regulatory and market gyrations are accelerants for Preqin, eFront and Aladdin. ¹
• They argued Safe Harbor-style requirements will increase the need for rigorous private-asset data performance benchmarking. ¹
• They stated that recent movements in non-traded BDCs and private credit have pushed investors to ask broader “exposure classification” questions (including distinguishing true software exposure and similar “underlying truth” issues), and that the ability to bring more transparency is a real accelerant for Preqin. ¹

Additionally, management expressed confidence that demand exists for the “destination” of seamless cross-public/private analytics, saying this pending demand is very important and is a key priority over the coming year. ²

4) How is AI impacting the area now—and how might it impact the future?

Current: AI discussed as part of broader tech investment balance

The excerpts include discussion of margins and investments, including the need to balance margin expansion with continued investment (including AI and technology broadly)—but they do not describe specific AI features or measurable AI-driven revenue effects for Aladdin/Preqin in the provided text. ³ Therefore, the most defensible conclusion from these excerpts is that AI is part of the ongoing technology investment agenda that management expects to pursue while also driving margin expansion. ³⁴

Future: “seamless analytics” ambition as the likely AI-adjacent frontier

Management’s described strategic end-state is a seamless analytical platform enabling clients to evaluate risk across public and private markets on a unified technology platform. ² They emphasize that this is a major, near-term priority and that the acquisition of Preqin (plus eFront and Aladdin capabilities) is meant to accelerate that platform direction. ¹²

While the excerpts do not explicitly say “AI will do X” within that future platform, the described direction suggests the future impact of AI would be to enhance and scale cross-asset analytics and risk evaluation—because management’s stated goal is integration of data/analytics across markets and delivery of a common client experience. ²

Bottom line

• Aladdin: Momentum is being driven by technology-led growth and continued client acceleration in tech spend, plus a trend toward fewer, more integrated providers spanning public and private markets. ¹
• Preqin/eFront: Demand is being supported by regulatory and private-market volatility, with transparency needs (e.g., benchmarking and underlying exposure clarity) acting as accelerants. ¹
• Synergies: The excerpts emphasize platform integration and cross-client expansion from combining Preqin with Aladdin/eFront, and they frame progress toward a seamless public/private analytics destination, though without specific quantified synergy realization. ¹²
• AI: AI is acknowledged as part of the broader technology investment balance (alongside margin and operational leverage priorities), but the excerpts do not provide specific AI performance metrics for these units. ³⁴