Director, Customer Success

Director, Ai Innovation Studios

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 / 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 PoC kickoff.

Handoff conversion rate : % of PoCs that transition to Product / Delivery with clear business cases.

Average (and aggregate) estimated ROI or value of opportunities advanced.

Stakeholder satisfaction and trust (partner NPS or equivalent).

Team health indicators : retention, competency growth, and utilization.

Required Qualifications & Skills

Bachelor's degree in math, computer science or related field.

8+ years of professional experience in consulting, strategy, product discovery, business analysis, or related roles; experience leading teams and client engagements.

Demonstrated track record (3+ years preferred) of discovering, scoping, or delivering AI, automation, or advanced analytics initiatives with measurable business outcomes.

Strong facilitation and consulting skills : proven ability to design and lead workshops, stakeholder interviews, ideation sessions, and executive briefings.

Excellent business acumen and financial literacy : ability to build credible business cases, ROI estimates, and value hypotheses.

Strong people leadership skills with experience managing and developing individual contributors in a hybrid, distributed environment.

Exceptional communication skills : translate complex AI concepts into actionable business language, and craft concise, persuasive artifacts for executives.

Experience with discovery-to-PoC processes and working closely with product managers, data scientists, ML engineers, and delivery teams.

Familiarity with ethical, regulatory, and governance considerations for AI deployments.

Preferred Qualifications

Experience in life sciences, healthcare, or regulated industries.

Prior consulting experience (management consulting or internal strategy / innovation practices).

Hands-on technical familiarity with ML / AI concepts and prototyping approaches (data exploration, simple model prototyping, prompt engineering, or working with ML / LLM teams).

Experience operating within enterprise portfolio governance and prioritization frameworks.

Organizational @context & Operating Expectations

This Director will report to the Executive Director, AI Compass and will partner regularly with Product Management, Portfolio Management, Engagement, Delivery, Security & Privacy, and divisional IT leads.

The role is expected to be both strategically minded and operationally grounded : roughly balancing enabling / mentoring the team and personally leading high-priority engagements.

All team members are U.S.-based and work in a hybrid model; in-person travel to business locations is expected as required (up to 75%).