This plan sets out how to engage Morgan Stanley's leadership across Investment Banking, Technology, Operations, and Executive Finance. It identifies the individuals who hold budget and influence, maps where decisions actually get made, and sequences outreach so that business sponsorship precedes technical scrutiny. Outcome references throughout align to the priority categories from the Outcomes Taxonomy: Talent & Productivity, Client Retention & Relationships, Deal & Transaction Velocity, Operational Resilience, Regulatory & Compliance Excellence, and Capital & Balance Sheet Efficiency.
Where this plan now stands. Morgan Stanley's headline goals are met as of 3Q26 ($10.5T client assets, 22.6% ROTCE, 67% efficiency ratio against a 70% target). The pitch is therefore capacity rather than catch-up: net revenues grew 12% year over year in 3Q26 while non-compensation expense grew 20% and the supplementary leverage ratio fell to 4.8%. Investment Banking remains the beachhead for access and measurability; Equities, then Wealth Management, are the secondary plays where the larger capital and cost case sits.
Primary contacts drawn from the Morgan Stanley leadership roster, ordered by decision authority and relevance to an agentic finance deployment.
| Name | Title | Role in Decision | Relevant Use Cases |
|---|---|---|---|
| Mo Assomull | MD & Global Head of Investment Banking | Executive Sponsor | Thesis-Driven Origination Engine, Relationship Intelligence Map |
| Eddie Molloy | MD, Global Head of Equity Capital Markets | Business Champion | Live Pitch Assembly, CIM Drafting Agent |
| Daniel Tay | MD, Global Head of AI and Fintech Investment Banking | Technical Champion | All AI-enabled IBK use cases |
| Phil Davies | MD, Global Head of Operations | Operations Owner | Deal Room Command Center, Clean Bookings Pipeline |
| Name | Title | Role in Decision | Focus Area |
|---|---|---|---|
| Uri Lichtenfeld | MD, Head of Strategic Technology Partnerships | Platform Decision | Integration architecture, vendor evaluation |
| Shaan Tehal | Global Head of AI & Software Banking | AI Strategy | Enterprise AI roadmap, model selection |
| Evan Damast | MD, Global Head of Data, Analytics & Data AI Platform Infra | Data Infrastructure | Data governance, platform integration |
| Michael Poser | MD, Co-CTO | Executive Tech | Technology strategy alignment |
| Hina Shamsi | Executive Director, Generative AI Strategy & Platforms | GenAI Champion | Generative AI use case prioritization |
| Name | Title | Role in Decision | Focus Area |
|---|---|---|---|
| Sharon Yeshaya | Chief Financial Officer | Budget Authority | Firmwide budget allocation, ROI validation |
| Eric Damiano | Executive Director, Head of Finance Business Management Risk Office | Risk Oversight | Model risk, control frameworks |
Mo Assomull (Global Head of IB) and Eddie Molloy (ECM). IBK leadership controls the budget for deal execution tooling and is directly accountable for league-table share. The Thesis-Driven Origination Engine and Relationship Intelligence Map speak to that mandate in the language of Client Retention & Relationships — specifically the "highest market share in industry groups" ambition.
Uri Lichtenfeld (Strategic Technology Partnerships) and Evan Damast (Data AI Platform). Every deployment passes through technology integration review. Lichtenfeld's remit explicitly covers strategic technology partnerships, which places him at the center of vendor evaluation and platform selection. Expect architecture, data residency, and model governance questions here.
Shaan Tehal (Global Head of AI & Software Banking) and Hina Shamsi (GenAI Strategy). These leaders own the enterprise AI roadmap. The proposition must extend existing generative AI investment rather than compete with it. Framing matters: this is the autonomy layer above copilots, not another copilot.
Sharon Yeshaya (CFO) and Eric Damiano (Risk Office). Final funding requires the CFO to see ROI against operating leverage: the efficiency ratio is 67% against a 70% target, but non-compensation expense is growing faster than revenue. The risk office validates that Operational Resilience and Regulatory & Compliance Excellence controls hold before any expansion past pilot.
Power center: Mo Assomull and Eddie Molloy.
Influence levers: league-table rankings, pitch-to-close conversion, deal timeline compression.
Pressure points: analyst burnout (Talent & Productivity), slow deal launches (Deal & Transaction Velocity), differentiation in origination.
Entry use cases: Pitch Book Assembly Agent, Deal Room Command Center.
Power center: Michael Poser and Evan Damast.
Influence levers: platform architecture, data governance, integration standards, security posture.
Pressure points: third-party vendor dependency (Operational Resilience), AI maturity benchmarking, personalization at scale.
Entry use cases: Intelligent Document Assembly, Autonomous Workflow Orchestration.
Power center: Phil Davies and Eric Damiano.
Influence levers: error reduction, straight-through processing, audit preparation cycles, operational loss events.
Pressure points: settlement fails and booking errors (Operational Resilience), audit prep burden (Regulatory & Compliance Excellence).
Entry use cases: Zero-Touch Trade Capture, Supervisory Surveillance Autopilot.
| Phase | Timeline | Target Audience | Primary Objective |
|---|---|---|---|
| Phase 1 | Months 1–2 | IBK business leaders (Assomull, Tay, Molloy) | Surface two or three pain points tied to firm goals; secure pilot champions |
| Phase 2 | Months 2–4 | Technology partnerships (Lichtenfeld, Damast) and AI strategy (Tehal, Shamsi) | Validate architecture fit; confirm alignment with the existing AI roadmap |
| Phase 3 | Months 4–6 | Pilot team — selected IBK analysts with IT support | Deploy one or two high-impact use cases; measure against documented baselines |
| Phase 4 | Months 6–9 | Operations (Davies), risk (Damiano), and CFO (Yeshaya) | Clear risk and compliance review; convert pilot evidence into funded expansion |
| Phase 5 | Months 9–18 | Equities (Sales & Trading) first, then Wealth Management; Investment Management and Research after | Scale proven use cases into the secondary plays: Capital & Balance Sheet Efficiency in Equities, then Client Retention & Relationships in Wealth Management |
Why IBK first
Opening move. Approach Assomull and Tay with a narrow, specific thesis: pitch and diligence cycles compressed from overnight to hours, tied directly to faster client response and league-table competitiveness. Anchor the conversation in Morgan Stanley's existing Integrated Firm advantage — cap table management and private capital markets at the early stage, IPO execution at the inflection point, family office and trust solutions afterwards. The argument is that agentic finance widens each moment the firm already owns.
| Tactic | Description | Target | Expected Outcome |
|---|---|---|---|
| Champion development | Equip two or three IBK leaders to advocate internally with ROI models and peer benchmarks | Tay, Molloy | Internal advocacy shortens the cycle materially |
| Proof-of-concept pilot | Run Pitch Book Assembly Agent with three to five analysts and measure cycle time against baseline | Analyst team, Davies | Quantified timeline compression against baseline (target 15–25%) |
| Executive alignment workshop | Half-day session mapping agentic finance to the four pillars and to what now binds: capital (SLR 4.8%) and execution cost (non-comp up 20% year over year) | Assomull, Lichtenfeld, Tehal | Shared roadmap and funding intent |
| Coverage gap analysis | Show where the current portfolio underweights Innovation & Strategic Positioning and Cross-Business Synergies, then propose expansion | Maranca Picariello, Shamsi | Positions the engagement as strategic, not transactional |
Approach Assomull and Tay. Run discovery that isolates concrete pain — analyst burnout, pitch turnaround, diligence throughput — and maps each to Talent & Productivity and Deal & Transaction Velocity metrics with named baselines.
Bring in Lichtenfeld and Damast for architecture and data governance review, then Damiano for security and model risk. Output is a documented integration path and a signed-off feasibility position.
Launch Pitch Book Assembly Agent with five analysts. Instrument cycle time, output per analyst, and senior time reallocation. Track Operational Resilience indicators alongside, so the risk narrative builds in parallel with the revenue narrative.
Take measured results to Yeshaya and Damiano. Convert operational gains into a financial argument — faster deal launches translating into incremental revenue, and reduced manual effort protecting operating leverage (efficiency ratio 67% in 3Q26, up from 65% in 2Q26, with non-compensation expense growing faster than revenue).
Extend within IBK to Deal Room Command Center and CIM Drafting Agent. Then move laterally into Equities, activating Capital & Balance Sheet Efficiency and Operational Resilience, and then into Wealth Management, activating Client Retention & Relationships, with Investment Management and the cross-business synergy category after.
| Stakeholder | Primary Concern | Messaging Focus | Metric to Lead With |
|---|---|---|---|
| Mo Assomull Global Head of IB |
League-table share and competitive position | Win more mandates through faster response and sharper origination intelligence; advisory revenue is up 30% year over year, so the constraint is coverage capacity | Pitch-to-close conversion up 10–20% (target) |
| Daniel Tay AI & Fintech IB |
Alignment with existing AI investment | Extends current generative AI work into autonomous execution; integrates with existing data infrastructure | Share of pitch workflow steps executed autonomously (baselined in pilot) |
| Uri Lichtenfeld Technology Partnerships |
Vendor leverage and integration burden | Improves contract economics and reduces dependence on third-party providers for critical workflows | Vendor dependence down 30–50% (target) |
| Sharon Yeshaya Chief Financial Officer |
Return on investment and firmwide budget discipline | Targets are met; fourteen talent and productivity use cases protect operating leverage while non-compensation expense grows faster than revenue (+20% versus +12% in 3Q26) | Coverage bandwidth up 30–50% (target); non-comp growth held below revenue growth |
| Phil Davies Global Head of Operations |
Operational resilience and error reduction | Ten resilience use cases cut error rates sharply while holding availability through market stress; execution cost is rising with volume (brokerage, clearing and exchange fees up 29% in 3Q26) | Error rate down 60–80%; STP at 85–95% (targets) |
| Hina Shamsi Generative AI Strategy |
Portfolio coherence and innovation leadership | Carries generative AI into autonomous workflows and creates protectable method IP | Agentic use cases moved from pilot to production (IP terms agreed up front) |
Metrics in the right-hand column above and in the tactics table are illustrative targets from the use-case matrix. They are not Morgan Stanley disclosures and should be baselined in the pilot before being quoted to the client. Morgan Stanley figures on this page are from the 3Q26 earnings release (October 14, 2026).