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Springboard is a six-week internal accelerator run by the AI Studio, designed to help leaders apply AI to one specific, high-impact business challenge within their function. Participants walk away with increased AI fluency, concrete artifacts, and a credible path forward tied to real business impact. Each cohort selects 3 to 5 senior business leaders to participate. Every Springboarder is assigned a dedicated AI Strategist and Technical Partner, forming a focused pod for the duration of the program. While Springboard currently works with senior leaders, it is designed to scale across the organization over time. Week 1: AI Opportunity Mapping. Deeply understand the business challenge, map end-to-end workflows, and identify where AI could create meaningful impact. Develop 3 to 5 validated AI use cases tied to real operational or strategic needs. Weeks 2 to 3: Rapid Prototyping and Iteration. Build and iterate 1 to 2 AI-driven solution concepts in a secure Studio Sandbox using sprint methodology and rapid experimentation to move from 0 to 1 quickly while building executive-level AI fluency. Weeks 4 to 6: Validation and Proposal Readiness. Refine solutions, validate feasibility and business value, and prepare AIRB proposals and handoff materials. Assess expected impact and complete an ecosystem scan comparing build vs. third-party options in partnership with IT. Weeks 6 to 7: Demo Day. Participants present their use case, prototype, and projected impact to enterprise leaders. Presentations inform next steps including pilots, further evaluation, or resourcing recommendations.
Job Responsibility:
Lead structured opportunity mapping conversations with SVP and C-suite executives
Apply domain and industry expertise to translate business challenges into AI-ready use cases
Host structured feedback sessions and reviews with the Springboarder throughout the sprint
Provide clear guidance on how AI can address specific business problems
Serve as the primary feedback channel between the executive and the Technical Lead
Coach the executive through their Demo Day presentation
May need to operate the live prototype during Demo Day
Deliver clear functional requirements to the Technical Partner and Ecosystem Scan lead
Review ecosystem scan results and synthesize findings into a clear build-vs-buy recommendation
Lead development of the Product Requirements Document, ROI and benefits analysis, and AIRB governance materials
Manage and synthesize program outputs across the sprint
Complete the final handoff package including all AI Review Board (AIRB) submission materials
Deliver a written weekly status report every Friday
Attend the weekly AI Strategist sync meeting
Requirements:
Demonstrated experience working directly with SVP and C-suite executives
Deep knowledge of applied AI, including large language models, machine learning, and enterprise AI platforms
Exceptional facilitation skills
Comfort serving as a technical operator during high-stakes presentations
Ability to translate ambiguous business challenges into structured use cases with clear scope, requirements, and success criteria
Familiarity with AI governance frameworks, risk assessment processes, and the considerations governing enterprise AI adoption
Experience with build-vs-buy analysis, vendor evaluation, and POC design
Strong executive communication and coaching skills