AI Enablement and Strategy Lead – AI and Intelligent Solutions, VP
Plano, TXFull-timePosted Jul 20, 2026
Drive and architect an enterprise-scale AI enablement program across Securities Services Operations. Set strategy, secure sponsorship, design adoption models, and deliver workforce productivity solutions—including Microsoft Copilot, LLM chat tools, speech-to-text, and agent builders—to materially enhance productivity, control, and user experience. Operate as a management consultant–strategy hybrid: define the north star, build the case for change, design adoption pathways, and land measurable outcomes and OKRs with urgency and precision, all while aligning to firmwide strategy.
Job Responsibilities- Define and drive the AI strategy: Establish a clear, risk-aware roadmap for AI adoption across custody, fund services, settlements, and corporate actions; prioritize value pools using hypothesis-led approaches; articulate the case for change and investment theses; secure alignment from senior stakeholders and control partners.
- Lead program execution end-to-end: Stand up operating models and decision forums; secure funding and vendor alignment; orchestrate cross-functional workstreams across Technology, Risk, Legal, and Operations; accelerate pace and remove blockers; hold owners accountable to outcomes and milestones.
- Scale core AI capabilities: Deploy Copilot for knowledge work, LLM chat tools for research and decision support, speech-to-text for call documentation, and agent builders for operational tasks; define adoption archetypes, role-based enablement, performance baselines, and risk controls to ensure safe, sustained adoption.
- Build the enablement engine: Produce enterprise-grade collateral including playbooks, prompt packs, pattern libraries, and adoption frameworks; deliver training, floor-walking, and communities of practice; equip managers with executive-ready toolkits, KPIs, and coaching materials to embed AI into daily work.
- Horizon scan emerging capabilities and translate into practical adoption: Maintain a strong understanding of emerging AI and productivity technologies; identify practical, high-impact applications; translate tool capabilities into clear business value propositions and adoption plays; convert insights into prioritized recommendations, pilots, and scaled rollouts with measurable outcomes.
- Land change and communications: Create crisp executive narratives, board-ready materials, and compelling PowerPoint storytelling; build leadership alignment and change narratives; partner with 1st and 2nd line stakeholders to drive behavior change, policy updates, and recognition mechanisms.
- Prove value and de-risk: Instrument usage, adoption, and productivity impact; track cycle-time compression and cost-to-serve improvement; deliver executive dashboards and benefits tracking tied to the business case; manage model risk, data privacy, and compliance controls in partnership with the second line.
- Demonstrate a strategic operator mindset with ownership: Set direction, challenge entrenched processes, and move from concept to scaled adoption with urgency; make trade-offs and decisions with incomplete data.
- Exhibit AI fluency for operations: Apply working knowledge of Copilot, LLM chat tools, orchestration, agentic AI patterns, prompt engineering, and speech-to-text; understand practical value unlocks and safe integration in Operations.
- Lead complex, cross-functional programs: Set cadence, enforce decision rights, unblock teams, and hold workstreams to outcomes; translate ambiguity into clear priorities, phases, and measurable OKRs.
- Communicate at a consulting-grade level: Deliver exceptional PowerPoint and narrative storytelling; produce sharp executive briefings and board materials; distill complexity into decisive recommendations and secure buy-in.
- Solve problems with structured analysis and rigor: Conduct hypothesis-driven analysis, stakeholder synthesis, value sizing, and pragmatic experimentation; focus on outcomes, not mechanics.
- Apply risk and control acumen: Shape AI guardrails, data privacy considerations, human-in-the-loop controls, and model risk documentation in regulated environments; engage constructively with Risk, Legal, and Compliance.
- Demonstrate leadership and influence: Build credibility with senior leaders and front-line teams; foster communities of practice; coach others; exhibit tenacity, curiosity, and courage to challenge the status quo while maintaining trust.
- Bring 6+ years in strategy, consulting, or transformation roles in financial services, with direct experience deploying AI and automation at scale.
- Demonstrate experience implementing Microsoft Copilot, enterprise LLM chat tools/platforms, or agent builder frameworks in operational settings.
- Produce playbooks, enablement assets, and training curricula; possess strong change management credentials.
- Operate fluently in common delivery and governance methodologies; partner effectively with product and technology teams without running the mechanics.
- Leverage exposure to process mining, automation, and analytics platforms; interpret adoption dashboards and tie to financial outcomes.