AI Business Analyst

Objective

Identify and validate high-value AI opportunities, rapidly prototype solutions, and ensure implementations deliver measurable business outcomes and tangible ROI.

KPI

• Revenue/cost impact of implemented AI solutions

• Stakeholders' satisfaction with business case clarity and realization

Areas of Responsibility

• Lead Discovery Process and Validate AI Opportunities

  • Facilitate stakeholder workshops to identify and prioritize high-impact AI use cases

  • Develop business cases with clear ROI models and success metrics

  • Build consensus among stakeholders on solution direction

• Map and Redesign Business Processes

  • Document current workflows and pain points

  • Design workflows with appropriate boundaries and controls for financial environments and Agentic AI systems

  • Quantify expected business improvements

• Define AI Solution Requirements

  • Translate business needs into clear technical requirements

  • Create user stories and acceptance criteria

  • Establish validation approaches for measuring success

• Create Solution Prototypes

  • Build functional demonstrations using no-code/low-code tools

  • Gather user feedback to refine concepts

  • Develop prompt templates for financial use cases

• Implement AI Governance and Compliance

  • Develop testing methodologies for AI systems in regulated environments

  • Ensure alignment with financial regulations (e.g US SR 11-7, EU AI Act)

  • Create documentation standards for model risk management

• Leverage Financial Services Industry (FSI) Ontologies

  • Apply industry-standard financial ontologies (e.g. FIBO) to structure and ground data

  • Design knowledge graph integrations to improve AI accuracy and compliance

  • Validate ontology completeness and accuracy for financial applications

• Ensure Ongoing Business Alignment

  • Manage stakeholder expectations throughout delivery

  • Lead business review sessions

  • Mitigate risks to value realization

• Stay Current on AI Capabilities

  • Actively test and experiment with emerging AI technologies firsthand

  • Evaluate new tools and platforms for business value

  • Share relevant insights with stakeholders

Skills

• Stakeholder management and workshop facilitation

• Business process analysis, requirements gathering, and documentation

• Project scoping, ROI modeling, and business case development

• LLM frameworks and prompt engineering for financial applications

• Hands-on AI tool experience, including no-code/low-code platforms

• Financial ontologies and graph databases (Neo4j, RDF/OWL)

• AI governance, testing, and validation in regulated environments

Traits

• Strategic business thinker who can identify valuable AI application opportunities

• Detail-oriented process analyst who can map complex workflows

• Technically curious with practical, hands-on AI knowledge

• Exceptional communicator who can translate between technical and business stakeholders

• Creative problem-solver able to rapidly prototype solutions

• Client-focused consultant who builds trust and drives business outcomes

Experience

• 3-5+ years experience in business analysis, process improvement, or consulting

• Practical implementation experience with LLMs and generative AI

• Hands-on experience with one or more no-code/low-code platforms

• Hands-on experience with orchestration frameworks (LangChain, AutoGen) or knowledge graphs

• Demonstrated success in requirements gathering and stakeholder management

• Demonstrated success moving AI projects from proof-of-concept to production in regulated environments

• Experience with digital transformation or technology implementation projects

• Background in financial services with understanding of regulatory requirement