Senior Analyst, AI Business & Transformation

Position Summary

The AI Business Analyst is the strategic bridge between business stakeholders and the AI Transformation engineering team. This role identifies high-value automation opportunities across the organization, translates business challenges into actionable engineering requirements, and produces executive-ready communications that demonstrate the team's impact and ROI. Leveraging AI tools natively in their own daily workflow, this analyst operates as both a domain expert and an AI power user - helping the organization understand what is possible while ensuring the engineering team builds what actually matters.

Essential Functions

• Conduct structured discovery sessions with business unit leaders and operational teams to identify manual processes, bottlenecks, and automation opportunities with measurable business impact.
• Translate business requirements into clear, actionable engineering specifications the AI engineering team can build against - including agent scope, data inputs and outputs, success criteria, edge cases, and security considerations.
• Use AI tools natively (including Anthropic Claude, Microsoft Copilot, and other LLMs) to draft executive summaries, business cases, use case briefs, ROI analyses, and presentation materials for senior leadership.
• Maintain and manage the team's use case pipeline: prioritizing opportunities by business impact and technical feasibility, tracking progress from discovery through deployment, and communicating status to stakeholders.
• Serve as the primary point of contact for business units seeking AI transformation support - qualifying inbound requests, setting appropriate expectations, and managing the engagement model with external teams.
• Develop and maintain standard templates for use case intake, requirements documentation, agent specification, and executive reporting to accelerate the team's ability to move from idea to build.
• Collaborate with the AI governance team to ensure all proposed use cases align with organizational AI policies, data handling guidelines, responsible AI principles, and compliance requirements.
• Build and maintain stakeholder relationships across business units, IT, and senior leadership - facilitating alignment and removing communication-driven blockers that slow the team.
• Track business outcomes delivered by deployed AI agents and automation - working alongside the team's analytical tools to validate that implemented solutions achieve stated ROI.

Qualification, Education, Knowledge, Skills

• Education: Bachelor's degree in Business Administration, Information Systems, Healthcare Administration, Operations, or related field. Advanced degree a plus but not required.
• Experience: 3+ years in a business analyst, management consultant, operations analyst, project manager, or similar role with significant cross-functional stakeholder engagement. Experience working alongside IT or technology teams is strongly preferred.
• Demonstrated, hands-on daily use of AI tools (Claude, ChatGPT, Copilot, or equivalent) may offset traditional experience requirements for exceptional candidates.
• Knowledge, Skills & Abilities: Demonstrated, hands-on proficiency using AI tools (Claude, ChatGPT, Microsoft Copilot, or similar) to produce professional-quality documents, analyses, executive presentations, and communications. Exceptional written communication skills - ability to craft compelling, concise executive narratives from complex technical and operational concepts. Process analysis and workflow documentation skills: ability to map current-state business processes, identify friction points and waste, and articulate clear future-state requirements. Familiarity with enterprise platforms such as ServiceNow, Microsoft 365, or ERP systems at a functional user level - sufficient to understand integration potential and data flows. Working understanding of AI/ML concepts including large language models, autonomous agents, automation, and data pipelines - sufficient to hold credible conversations with both engineers and executive leaders. Understanding of AI security and responsible use considerations: data privacy, access control, appropriate use policies, and the importance of organizational AI governance guardrails. Excellent stakeholder management, facilitation, and meeting leadership skills - comfortable leading discovery workshops with both technical and non-technical audiences. Highly organized with the ability to manage a portfolio of parallel initiatives across different business units and stages of maturity. Self-starter mentality - comfortable in a fast-moving, emerging-practice environment where the playbook is being written in real time. Genuine intellectual curiosity about AI and automation, evidenced by personal experimentation, self-directed learning, or a clear track record of bringing AI tools into previous work.