AI Business Analyst

Role: AI Business Analyst The AI Business Analyst plays a critical role in bridging business needs and AI-enabled solutions, ensuring that use cases are well-defined, feasible, and aligned to real business value. This role combines strong analytical capability with an understanding of AI/ML to shape, validate, and deliver impactful solutions. Key Responsibilities Translate business needs into clear, structured requirements for AI and analytics solutions (e.g., decision support, predictive models, recommendations, and GenAI copilots).

Lead core business analysis activities, including requirements definition, gap analysis, process mapping, and supporting test design and execution. Define both functional and non-functional requirements for AI capabilities, including: Performance, accuracy, and reliability expectations Explainability and transparency requirements Auditability, logging, and traceability standards Assess feasibility, risks, and data readiness for AI/ML/GenAI use cases. Collaborate with data owners, stewards, and architects to identify required data sources, understand data lineage, and evaluate data constraints.

Work closely with data scientists, engineers, and AI teams to define realistic test scenarios and acceptance criteria, including edge cases and thresholds for “good enough” performance. Shape and support experiments and pilots (e.g., MVPs, A/B testing) to validate AI use cases in a controlled and measurable way. Analyse the impact of AI solutions on business processes and roles, including identifying opportunities for automation vs. augmentation.

Ensure AI use cases align with data privacy, security, and regulatory requirements (e.g., GDPR and sector-specific standards). Required Skills & Experience Proven experience in identifying, analysing, prioritising, and validating business and user requirements for AI or data-driven solutions. Experience conducting options analysis, feasibility assessments, impact analysis, and value estimation to support business case development.

Strong communication skills, with the ability to produce clear, engaging, and insightful reports and presentations. Ability to translate complex business problems into actionable insights for both technical and non-technical stakeholders. Strong stakeholder engagement skills, with experience working across business and technology teams.

Desirable Experience within the Energy & Utilities sector. Familiarity with AI/ML concepts and lifecycle (e.g., model development, evaluation, deployment, and monitoring).