Meet a BlackRock Technologist Supercharging Investment Teams With AI

Breaking: BlackRock Names Kirsty Craig Among Five New Tech Fellows, Elevating Female Leadership in AI-Driven Investing

In a move underscoring its push for AI-powered investing and gender diversity, BlackRock has crowned Kirsty craig as one of five new Tech Fellows. Craig, who leads research, data, and AI strategy for portfolio management technology, is the sole woman among the latest cohort and the only fellow working outside the firm’s Aladdin platform this year.

Her appointment spotlights a broader effort to blend portfolio insight with cutting‑edge engineering. Craig now sits at the nexus of investment decisions and the systems that accelerate them, helping BlackRock’s $13.5 trillion franchise stay ahead in an increasingly automated market.

What Asimov Means for BlackRock’s Essential Investing

Craig has been a champion of Asimov, BlackRock’s agentic AI system designed to empower the fundamental equity team. Unveiled at the company’s investor day in June, Asimov acts as a “virtual research analyst,” automating workflows and research tasks that once took weeks or months to complete.

The platform leverages AI to streamline workstreams across the firm’s research environment, speeding up analyses and enabling faster, more informed investment ideas. BlackRock executives describe Asimov as a practical step toward scaling human insight with machine efficiency.

Leadership at the Frontline: Cross‑Functional Impact

Craig’s day‑to‑day role spans software engineers, data scientists, and investment professionals. Her team, numbering about 60, operates across multiple offices to ensure collaboration between traders, portfolio managers, and the technologists who build Aladdin and related systems.

She explains that the key is translating the language of investors into actionable technical plans, and vice versa. “When you bring together diffrent mindsets, you often get misaligned signals. My job is to bridge those perspectives and craft strategies that move the investment pillars forward.”

Visible Leadership in a Diversified BlackRock

Being a woman in a high‑profile tech role is described as a important honor by Craig. Among the current Tech Fellows, five are women, a reflection of BlackRock’s broader diversity efforts. The firm reports that women make up 43.8% of its global workforce and 33.1% of senior leadership, as of early 2025.

Craig also notes that participation in BlackRock’s women and LGBTQ+ groups has sharpened her ability to collaborate across divisions and explain complex topics with impact. She hopes her presence will encourage more junior female technologists to “lean in.”

Beyond the Title: Expanding AI’s Reach

Looking ahead, Craig is eager to steer the technology strategy further into active investing. Her team is exploring how to broaden agentic research to additional domains, including fixed income and macro strategies, expanding the scope of AI‑assisted decision making.

Timeline,Personal Milestones,and Momentum

Craig learned of the honor early in the month when a calendar invite announced the nomination. She says her partner is due to welcome a child in January, a personal milestone that will punctuate a period of rapid professional momentum. For now,celebrations have been measured-meals out and essential preparations like cribs and bottles are already in place.

Key Facts at a Glance

Fact	Detail
Name	Kirsty Craig
Position	Head of Research, Data, and AI Strategy for Portfolio Management Tech
Company	BlackRock
Programme	Tech Fellows
Status in 2025 cohort	Five new fellows; Craig is the only woman and the only fellow outside Aladdin
AI Platform	Asimov, virtual investment analyst for fundamental equity
Investor Day	June (Asimov unveiled)
Team size	About 60 engineers, data engineers, and data scientists
Offices	Edinburgh, San Francisco, Philadelphia
Personal note	Partner due in January; celebrations scaled back for now

Evergreen Insights: What This Signal Means for Finance Technology

• AI in asset management is moving from pilot projects to integrated platforms that touch every stage of research and trading.
• Senior leadership emphasis on diversity signals a long‑term shift toward broader inclusion in technology‑driven finance.

Reader Questions

How might the integration of agentic AI platforms alter the balance between human judgment and machine recommendations in investment decisions?

Will more firms adopt cross‑functional tech fellow programs to diversify leadership and accelerate AI adoption in finance?

Share your thoughts below and tell us how you think AI leadership will shape the future of investing.

Disclaimer: This article covers developments in financial technology and corporate leadership. For investment decisions, consult qualified financial advisors and review official company disclosures.

Research analysts, Portfolio managers 2023 AI‑Enhanced Risk Engine Predictive stress‑testing using Monte‑Carlo simulations accelerated by GPUs Risk‑management teams 2024 Portfolio‑Builder LLM Natural‑language query interface for constructing multi‑asset scenarios Junior analysts, Advisors 2025 Smart‑Trade Execution Bot Real‑time order routing with reinforcement‑learning based cost minimization Trading desks 2025

All tools are built on BlackRock’s secure Azure‑Gov cloud partnership, complying with GDPR, CCPA, and the SEC’s data‑privacy rules.

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Key Benefits for Investment Teams

1. Speed & Scale

• 70 % reduction in data‑collection time; analysts can query 10 TB of news, ESG filings, and satellite imagery in seconds.
• Higher Accuracy
• Predictive error margin for VaR forecasts dropped from 12 bps to 4 bps after AI‑Risk Engine rollout (BlackRock 2024 Technology Report).
• Enhanced Decision‑Making
• Portfolio‑Builder LLM surfaces “what‑if” scenarios that would take weeks to model manually, increasing idea generation by 35 %.
• Cost Efficiency
• Smart‑Trade Execution Bot cuts average transaction cost by 8 bps,saving over $200 M annually across global fund families.

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Practical Tips for Teams Adopting BlackRock AI

1. Start with a “Pilot‑first” Mindset

• Identify a single repetitive workflow (e.g., ESG score aggregation) and run a 4‑week pilot with Aladdin AI Insights.
• Leverage Pre‑Built Prompt Libraries
• Use the curated LLM prompt library to standardize language for risk‑scenario queries; reduces model hallucination risk.
• Integrate Governance Early
• Align AI model outputs with BlackRock’s Model Risk Management framework; document data lineage and version control.
• Upskill via Internal MOOCs
• Enroll in BlackRock’s “AI for finance” courses (available on the internal Learning Hub) before full deployment.
• Monitor Model Drift
• Set up automated drift alerts that compare live prediction distributions against the baseline stored in Azure ML Model Registry.

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Real‑World Impact: Verified Case studies

1. Global Fixed‑Income team – Faster Credit Analysis

• Challenge: Manual parsing of 2,000 quarterly earnings releases per month.
• AI Solution: Aladdin AI Insights coupled with a custom LLM summarizer.
• Outcome: Credit analysts reduced turnaround from 5 days to 12 hours, enabling timely bond‑selection decisions that captured an extra 4 bps of yield (BlackRock internal case study, Q2 2024).

2. ESG‑Focused Equity Fund – Deep‑Learning Sentiment Scoring

• Challenge: Inconsistent ESG metrics across data vendors.
• AI Solution: Multi‑modal model ingesting regulator filings, satellite images of factory emissions, and social‑media sentiment.
• Outcome: ESG scores achieved a 92 % correlation with third‑party verification, leading to a 15 % increase in sustainable‑asset inflows (BlackRock ESG Innovation Report, 2025).

3. Multi‑Asset Trading

Meet a BlackRock Technologist Supercharging Investment Teams With AI

The Technologist Behind the AI Revolution

Name: Dr. Priyanka Sharma – Head of AI Engineering, BlackRock

Background: Ph.D. in Computer science (MIT), 12 years in machine‑learning research, former senior data scientist at Google cloud AI.

Role at BlackRock: Leads the “AI‑First” initiative that embeds generative‑AI models, reinforcement‑learning optimizers, and real‑time data pipelines into the Aladdin ecosystem.

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AI Tools Redefining Investment Workflows

AI Solution	Core Function	Primary Users	Release Year
Aladdin AI Insights	auto‑generation of macro‑economic narratives from unstructured data	Research analysts, Portfolio managers	2023
AI‑Enhanced Risk Engine	Predictive stress‑testing using Monte‑Carlo simulations accelerated by GPUs	Risk‑management teams	2024
Portfolio‑Builder LLM	Natural‑language query interface for constructing multi‑asset scenarios	Junior analysts, Advisors	2025
Smart‑Trade execution Bot	Real‑time order routing with reinforcement‑learning based cost minimization	Trading desks	2025

All tools are built on BlackRock’s secure Azure‑Gov cloud partnership, complying with GDPR, CCPA, and the SEC’s data‑privacy rules.

---

Key Benefits for Investment Teams

1. Speed & scale

• 70 % reduction in data‑collection time; analysts can query 10 TB of news, ESG filings, and satellite imagery in seconds.
• Higher accuracy
• Predictive error margin for VaR forecasts dropped from 12 bps to 4 bps after AI‑Risk Engine rollout (BlackRock 2024 technology Report).
• Enhanced Decision‑Making
• Portfolio‑Builder LLM surfaces “what‑if” scenarios that would take weeks to model manually, increasing idea generation by 35 %.
• Cost Efficiency
• smart‑Trade Execution Bot cuts average transaction cost by 8 bps,saving over $200 M annually across global fund families.

---

Practical Tips for Teams Adopting BlackRock AI

1. Start with a “Pilot‑First” Mindset

• Identify a single repetitive workflow (e.g., ESG score aggregation) and run a 4‑week pilot with Aladdin AI Insights.
• Leverage pre‑Built Prompt Libraries
• Use the curated LLM prompt library to standardize language for risk‑scenario queries; reduces model hallucination risk.
• Integrate Governance Early
• align AI model outputs with BlackRock’s Model risk Management framework; document data lineage and version control.
• Upskill via Internal moocs
• Enroll in BlackRock’s “AI for Finance” courses (available on the internal Learning Hub) before full deployment.
• Monitor Model Drift
• Set up automated drift alerts that compare live prediction distributions against the baseline stored in Azure ML Model Registry.

---

Real‑World Impact: Verified Case Studies

1. Global Fixed‑Income team – Faster Credit Analysis

• Challenge: Manual parsing of 2,000 quarterly earnings releases per month.
• AI Solution: Aladdin AI Insights coupled with a custom LLM summarizer.
• Outcome: Credit analysts reduced turnaround from 5 days to 12 hours, enabling timely bond‑selection decisions that captured an extra 4 bps of yield (BlackRock internal case study, Q2 2024).

2. ESG‑Focused Equity Fund – Deep‑Learning Sentiment Scoring

• Challenge: inconsistent ESG metrics across data vendors.
• AI Solution: Multi‑modal model ingesting regulator filings, satellite images of factory emissions, and social‑media sentiment.
• Outcome: ESG scores achieved a 92 % correlation with third‑party verification, leading to a 15 % increase in sustainable‑asset inflows (BlackRock ESG Innovation Report, 2025).

3. Multi‑Asset Trading Desk – Real‑Time Cost Optimization

• Challenge: Transaction cost volatility across 30 global venues.
• AI Solution: Smart‑trade Execution Bot using reinforcement learning to adjust routing in milliseconds.
• Outcome: Execution cost fell by 8 bps, equivalent to $180 M saved in FY 2025 (BlackRock Trading Analytics Dashboard).

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Future Outlook: AI Roadmap Through 2026

• 2026 Q1: Deployment of “Quantum‑Ready Risk simulations” leveraging hybrid quantum‑classical algorithms for ultra‑high‑dimensional stress tests.
• 2026 Q3: Expansion of “AI‑Embedded Advisory” where client‑facing portals generate personalized portfolio recommendations in real time, fully compliant with fiduciary standards.
• Continuous Learning Loop: Dr. Sharma’s team will integrate federated learning across all BlackRock entities, allowing models to improve from localized data without compromising confidentiality.

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Speedy Reference: SEO‑Amiable Keywords Embedded

• BlackRock AI technologist
• AI‑first investment platform
• Aladdin AI tools
• Generative AI for portfolio management
• real‑time risk analytics
• AI‑enhanced trading execution
• ESG AI scoring BlackRock
• Machine learning in asset management
• Reinforcement learning trade routing
• Federated learning finance

Keywords are woven naturally throughout headings, bullet points, and body copy to align with user intent while preserving readability.