At Blackstone, some of the most consequential work happens far from the spotlight. Across time zones and geographies, Legal & Compliance teams review investor disclosures, regulatory filings, and deal documents—materials where accuracy is governed by a nonnegotiable, zero-defect culture.

As the organization grew larger and more diversified, the complexity of ensuring accuracy across more products and jurisdictions escalated. Blackstone’s assets under management had doubled in the previous five years alone, while the organization was producing 25,000 investor-facing materials annually.

Chief Legal Officer John Finley saw an opportunity for the function to future-proof itself—reimagining investor communications as a scalable, value-driving capability. This ambition was further reinforced by Blackstone President and Chief Operating Officer Jon Gray, who labeled the effort “L&C 3.0.” Finley, Global Chief Compliance Officer Marshall S. Sprung, and the rest of the leadership team challenged themselves to think about how to deliver for a firm three times the size without tripling spend. They believed AI would be core to the solution. The harder question? Where AI could create real value—and how leaders could set teams up for success.

To answer that question, Blackstone’s Legal & Compliance team chose to start with one of the most complex and high-stakes areas: investor communications.

Map the full life cycle of investor communications

Mapping the full process exposed unclear ownership, repeated escalations, and missing precedent—so teams could stop re-solving the same issues and move work faster.

Pinpoint critical moments for human oversight

By identifying where judgment truly adds value, Blackstone reduced unnecessary escalations and focused experts on high-risk, investor-critical decisions.

Embed AI as the first-pass reviewer

AI now reviews routine materials, flags anomalies, and routes work to the right experts—helping teams handle 25 percent more volume with up to 50 percent higher productivity.

Working with McKinsey, Blackstone set out to redesign the investor communications process within Legal & Compliance from the ground up. The goal was not to transform with technology for technology’s sake, but to first build a model that could scale with the firm’s growing size and complexity—and only then leverage technology to accelerate the process.

Mapping the full life cycle of investor communications

Our joint Blackstone–McKinsey team began by mapping the end-to-end life cycle of an investor communication—from first draft to final approval. What emerged was not just duplicative reviews of similar language and recurring disclosure elements but other pain points: unclear ownership, repeated escalations, version confusion across inboxes, and time lost.

Teams asked difficult questions: Where did human judgment truly add value? Which reviews repeated frequently with little variation? Did control functions manage risk or simply add layers of bureaucratic dead weight? And where did escalation protect quality versus simply slowing decisions?

Interviews across Legal & Compliance, Investor Communications, and business partners revealed a common pattern: Team members often lacked the clarity or tools needed to make decisions without precedent, leading to frequent escalations. The result was re-solving familiar questions instead of building on prior learnings.

At the same time, as is natural in any evolving organization, a steady flow of new and departing colleagues meant reviewers often changed, resetting institutional memory along the way. Every transition risked slowing turnaround times and reintroducing inconsistency—particularly across regions operating in different time zones.

To address these challenges, the team redesigned both the workflow and the underlying decision-making system.

Pinpointing critical moments for human oversight

Together, we redesigned investor communications workflows to concentrate human judgment on novel, high-risk, and investor-critical decisions. The new model codified precedent into structured decision rules and embedded them directly into the workflow. Repeatable reviews were standardized, and materials that had already passed scrutiny multiple times could now advance automatically, with explicit guardrails and clear escalation paths—including alerting teams when a human analyst needed to be involved.

This redesign also extended to the operating model—clarifying roles, streamlining handoffs, and aligning a global, follow-the-sun delivery model to demand—so that speed and quality reinforced each other rather than traded off.

Only then did technology enter the picture.

Embedding AI as the first-pass reviewer

AI was embedded directly into day-to-day workflows, not layered on top. Rather than adding another dashboard, it became the first-pass reviewer—triaging volume, checking consistency, detecting anomalies across thousands of documents, and escalating what required legal judgment. Work no longer waited for clarification; standardized triage and AI-enabled routing directed questions to the right expert the first time.

Blackstone’s approach meant that technology did not replace human judgment, but instead freed up senior experts to focus on complex, high-value decisions while ensuring consistency and speed across routine work. By reinforcing a deliberately redesigned decision system, Blackstone Legal & Compliance built an investor communications review capability that could scale with confidence—and serve as a durable lever for growth.

“We weren’t interested in AI as an experiment. We wanted to know whether it could raise the ceiling on how fast and how well the firm operates—starting with the hardest problems, not the easiest,” Finley said.

The integrated redesign of workflow, talent, and technology has delivered measurable results.

Today, operational efficiencies and agentic AI have allowed Blackstone Legal & Compliance to be ready for the 25 percent expected increase in investor-facing material volumes by 2027. In practical terms, the expected reviewer productivity gains of 30%+ means more materials cleared in parallel, fewer bottlenecks at senior levels, and faster turnaround without compromising quality and review integrity. Blackstone Legal & Compliance is on track to realize an estimated $5 million in annual run rate savings by 2027.

The day-to-day experience changed as well. Analysts who once reconstructed prior decisions now see relevant precedent surfaced more seamlessly via the automated AI platform. Senior lawyers who previously reviewed routine language now spend their time resolving more critical regulatory questions. Instead of chasing approvals across inboxes, teams now track status transparently within a shared workflow.

Work is dynamically allocated based on demand and complexity through AI-driven triage and routing. This has introduced a new operational manager role responsible for orchestrating workflows, overseeing AI quality metrics, and optimizing capacity and quality across regions.

Beyond the numbers, the shift expanded how Legal & Compliance saw its role—as proactive risk adviser and judgment center. Finley noted that beyond increasing productivity, AI adoption has helped future-proof the organization, creating more resilience to address macro market shifts.

“Trust is our currency,” he said. “Any use of AI had to strengthen that trust—with regulators, with investors, and with our people. That meant being explicit about where AI could perform repeatable, rules-based reviews at scale and where human judgment remains essential.”

As McKinsey Partner Naina Dhingra explains, Blackstone’s breakthrough wasn’t AI on its own. “AI accelerated results because the work had already been redesigned around clear decision ownership and repeatable processes,” she says. “Technology doesn’t fix broken processes—it amplifies what’s there. Blackstone had the foresight to reimagine the work itself first, then apply AI to scale and strengthen it.”

Today, Blackstone continues to extend AI across legal processes and the broader organization. But the principle remains unchanged: AI is not a shortcut. It is embedded into how people work and how decisions flow—so speed, scale, and trust advance together.