BlackRock Launches AI "Auto Commentary" to Streamline Advisor-Client Conversations
BlackRock's Aladdin Wealth platform has rolled out Auto Commentary, a generative AI feature that turns complex portfolio analytics, firm CIO outlooks, and client preferences into concise, client-ready narratives. The goal: help advisors deliver more personalised insights with less prep time and more consistency across teams.
Morgan Stanley Wealth Management will be first to implement through its Portfolio Risk Platform, combining BlackRock's risk analytics with Morgan Stanley data to produce advisor-ready commentary at scale.
What Auto Commentary Does
- Summarises portfolio risk, performance drivers, and exposures in plain language.
- Blends firm-level CIO views with client goals and preferences for relevance.
- Analyzes hundreds of data points and outputs concise narratives advisors can use in reviews, emails, or reports.
- Cuts time spent gathering, reconciling, and rewriting data-freeing capacity for client conversations.
Why This Matters for Management
- Scale personalised advice without increasing headcount.
- Standardise messaging and quality across branches and books of business.
- Shorten prep cycles for reviews and market updates.
- Support stronger client engagement in volatile markets with clearer, faster commentary.
Inside the First Deployment
Morgan Stanley Wealth Management is integrating the feature into its Portfolio Risk Platform, pairing Aladdin Wealth risk analytics with proprietary client and portfolio data. This setup gives advisors a unified view of risk and a consistent way to communicate it through AI-authored summaries. Learn more about the firm's broader advisory capabilities at Morgan Stanley Wealth Management.
Leadership Considerations
- Policy and compliance: Define approval workflows, disclosures, and archiving for AI-generated text.
- Data governance: Confirm data sources, permissions, and lineage to avoid drift or gaps.
- Advisor enablement: Provide training on prompt inputs, context-setting, and final reviews.
- Measurement: Track prep-time reduction, client engagement rates, and meeting outcomes.
What to Do Next
- Identify top use cases: portfolio reviews, quarterly updates, and event-driven notes.
- Pilot with a controlled advisor group; compare time-to-deliver and client response vs. baseline.
- Create a content library: CIO views, house language, and disclosure templates for consistency.
- Set KPIs: hours saved per advisor per week, coverage of client book, and NPS/retention movement.
BlackRock signals an ongoing push to apply AI where it matters in wealth: faster insight, consistent narratives, and more time for meaningful client conversations. For leaders, the advantage comes from pairing strong data foundations with clear governance and disciplined rollout.
Upgrade team capability: If you are building advisor or analyst skills for AI-assisted commentary and reporting, explore curated AI tools for finance to accelerate adoption and workflow design.
