Director, Customer Success

Job Description

The Director, AI Innovation Studios leads a small, high-impact team of consultants, analysts, and facilitators that drives discovery and early incubation of AI opportunities across the enterprise. This is a hands-on director-level role that combines client-facing consulting and workshop facilitation with people leadership, operational ownership of a studio team, and accountability for moving well-scoped opportunities into rapid proofs-of-concept (PoCs), prototypes, and handoff to Product or Delivery teams. The Director will translate business challenges into measurable AI use cases, create compelling business cases and success criteria, and ensure rigorous, ethical, and outcome-focused execution across discovery and early delivery phases.

Key responsibilities

Practice leadership & strategy

• Contribute to the vision and operating model for the AI Innovation Studios aligned to APEX/Compass priorities and the Chief AI Officer’s strategy.

• Define Studio methodologies, templates, toolkits, intake and prioritization criteria, and measurable success metrics for discovery engagements and rapid PoCs.

• Maintain relationships with adjacent APEX functions (Product Management, Portfolio Management, Engagement, Process Intelligence, Data Science/AI engineering) to enable efficient handoffs and access to technical expertise.

Team leadership & talent development

• Lead, coach, and grow a compact team of 5–7 full-time consultants, analysts, and facilitators — all direct reports — cultivating a high-trust, collaborative, and delivery-focused culture.

• Hire, develop, and retain Studio practitioners; run performance management, career development, and workforce planning for the team.

• Balance hands-on participation in engagements with enabling team members to lead discovery and PoC work autonomously.

Client engagement & discovery

• Serve as primary consultant for high-priority discovery engagements with business-area leaders and Divisional IT leads: design and run opportunity identification workshops, rapid discovery sprints, process & data analysis, stakeholder alignment sessions, and ideation activities.

• Translate workshop outputs into clearly scoped opportunity assessments: problem statement, proposed AI approach, expected benefits, cost/effort estimate, success criteria and risks.

• Act as a trusted advisor to divisional partners, ensuring Studios’ engagements shift thinking from “possible” to “actionable.”

Rapid prototyping & PoC oversight

• Own initiation and oversight of rapid PoCs and prototypes generated from discovery: set hypotheses, define acceptance criteria, coordinate technical resources, and monitor progress against timelines and outcomes.

• Ensure PoCs produce measurable evidence (metrics, demos, validated assumptions) to support go/no-go decisions and handoff to Product/Delivery.

• Partner with Product Management and Delivery to create clear transition plans, technical readiness checklists, and business case updates.

Governance, prioritization & portfolio alignment

• Operate within Compass’ portfolio governance and prioritization frameworks: triage incoming Studio requests, recommend investment and sequencing decisions, and ensure alignment to enterprise priorities and capacity.

• Track and report Studio pipeline health, conversion rates, time-to-PoC, ROI estimates, and stakeholder satisfaction to the ED of AI Compass and other executive stakeholders.

Ethics, risk & adoption

• Embed best practices for safe, ethical, equitable, and regulatory-compliant AI in all discovery and PoC activities.

• Identify adoption risks and change-management needs early; help create stakeholder engagement plans, success criteria, and measures to accelerate adoption and value realization.

Methods, tools & partnerships

• Lead use of a broad array of discovery tools and workshop methods (design thinking, business analysis, process mapping, prioritization frameworks, Miro/MURAL, etc.).

• Coordinate with internal APEX subject-matter experts (process intelligence, data science, ML engineers, security, privacy, legal) and manage occasional engagement of external partners/vendors for specialized capabilities.

Success metrics

• Number of qualified AI opportunities identified per quarter and per business area.

• Pipeline conversion rate: % of discovery engagements that progress to funded PoC or product incubation.

• Time-to-PoC: median time from intake to Po