Business Analyst - AI Programme

Overview

• The role will involve close collaboration with senior business stakeholders, subject matter experts, product managers, technology and data specialists, and delivery teams to shape and implement AI-enabled solutions. The Business Analyst will support the analysis and redesign of business processes, define requirements and acceptance criteria, and ensure that proposed solutions address business needs while meeting appropriate governance, risk, control and assurance requirements. The Business Analyst will contribute by helping translate programme objectives into actionable business and delivery requirements, supporting the design of AI-enabled capabilities and ensuring that business processes, human oversight and responsible AI considerations are addressed throughout the delivery lifecycle.

Responsibilities

Business Analysis and Requirements Management:

• Lead end-to-end business analysis activities within an assigned AI Programme workstream, from discovery and requirements elicitation through to design, delivery, testing and implementation.
• Engage business stakeholders and subject matter experts to understand business needs, objectives, problems, constraints and expected outcomes.
• Facilitate workshops, interviews and other elicitation activities to establish current-state requirements, challenge assumptions and clarify complex or ambiguous business needs.
• Document, analyse, validate and manage business, functional and non-functional requirements, use cases, user stories and acceptance criteria.
• Translate business requirements, policies, standards and regulatory obligations into clear, actionable requirements for business processes, technology solutions and controls.
• Maintain requirements traceability and support prioritisation, refinement, change control and validation throughout the delivery lifecycle.
• Work with product managers, technology teams and other delivery stakeholders to ensure requirements are understood, feasible, testable and aligned with programme objectives.

Business Process Analysis and Design

• Analyse and document As-Is business processes, identifying inefficiencies, pain points, risks, control weaknesses and opportunities for improvement.
• Develop To-Be process models and workflows that incorporate AI-enabled capabilities and define how people, AI agents and existing systems interact.
• Break complex business activities into logical, measurable steps, identifying tasks suitable for automation, AI assistance or autonomous execution.
• Define process triggers, decision points, business rules, exception handling, escalation routes and hand-offs between AI agents, people and systems.
• Assess the operational and organisational implications of proposed changes, including impacts on roles, responsibilities, procedures, capabilities and ways of working.
• Challenge existing processes and approaches constructively, recommending innovative and practical solutions to business problems.

AI-Enabled Solutions and Agentic AI

• Define business requirements for AI-enabled solutions, translating business objectives into clearly scoped use cases, capabilities, user stories and measurable outcomes.
• Where Agentic AI is in scope, support the decomposition of business workflows into goal-driven activities that AI agents can perform, subject to defined permissions, constraints and oversight.
• Define requirements for AI-agent triggers, decision points, permitted actions, dependencies, exception handling and interactions with users and other systems.
• Distinguish between tasks that can be automated, tasks requiring human review and decisions that must remain subject to human approval.
• Define human-in-the-loop requirements, including intervention points, decision thresholds, escalation paths, override mechanisms and safe fallback processes.
• Collaborate with product managers, technology teams, data specialists and AI practitioners to assess feasibility, refine solution designs and support implementation.
• Define acceptance criteria and validation scenarios to assess whether AI-enabled capabilities meet business needs and perform as intended.
• Responsible AI, Governance and AssuranceTranslate relevant AI policies, standards, governance requirements and risk controls into practical business requirements, process changes and delivery acceptance criteria.
• Work with risk, compliance, governance and technical stakeholders to identify risks associated with AI-enabled processes and define proportionate mitigations and controls.
• Support the definition of requirements for transparency, explainability, accountability, traceability and appropriate human oversight of AI-enabled decisions and actions.
• Identify potential harms and unintended consequences arising from AI-enabled processes, including impacts on individuals, vulnerable groups and relevant stakeholders.
• Where applicable, contribute to requirements for fairness, bias mitigation and the assessment of differential outcomes across relevant demographic or other affected groups.
• Define measurable criteria and evidence requirements to support the validation and ongoing monitoring of AI outputs, decision quality, fairness and control effectiveness.
• Ensure that assumptions, limitations, risks, control requirements and human responsibilities are documented and incorporated into solution and process designs.

Stakeholder Engagement and Delivery Support

• Build effective working relationships with senior business stakeholders, subject matter experts, product managers, architects, developers, data specialists and programme delivery teams.
• Facilitate discussions across business and technical teams, translating complex requirements and design considerations into clear, shared outcomes.
• Challenge stakeholders constructively where requirements are unclear, conflicting, impractical or insufficiently aligned with business objectives, policy or risk considerations.
• Identify, document and escalate risks, issues, assumptions, dependencies and decisions, contributing to their resolution and mitigation.
• Support backlog refinement, solution walkthroughs, test planning, user acceptance testing and implementation readiness.
• Validate delivered outcomes against agreed requirements and acceptance criteria, supporting the resolution of gaps and the assessment of proposed changes.
• Maintain clear and accurate analysis artefacts and communicate progress, findings, recommendations and outstanding decisions to relevant stakeholders.

Qualifications

• Bachelor's Degree in Computer Science, Information Systems, or other related field, or equivalent work experience.
• Relevant Business Analysis qualifications, such as BCS or IIBA certification, would be beneficial.

Essential skills

• Proven ability to elicit, analyse, document, validate and manage business requirements, use cases, user stories and acceptance criteria.
• Strong facilitation skills, including the ability to challenge business subject matter experts, investigate ambiguous requirements and develop clear As-Is and To-Be process models.
• Strong business acumen and the ability to rapidly develop an understanding of unfamiliar business domains, policies, processes and operating models.
• Ability to translate policies, standards and business rules into requirements that can be implemented through processes, procedures, systems and controls.
• Strong analytical, problem-solving and critical-thinking skills, with the confidence to challenge existing approaches and identify innovative solutions.
• Ability to work effectively in uncertain or evolving environments, managing competing priorities and maintaining focus on business outcomes.
• Understanding of AI agents, agent orchestration, tool use, workflow automation and the interaction between AI systems, business processes and human users.
• Understanding of responsible AI principles, AI governance, risk management, assurance and the translation of policy requirements into practical controls.
• Familiarity with Agile product delivery, backlog management, iterative development and collaborative testing approaches.

Experience

• Professional attitude, has developed a reputation as a trusted advisor.
• Good problem solving skills, has experience in proposing different options and solutions for approaching and resolving issues.
• Adaptable and responds positively to changing business issues, sees change as an opportunity to improve performance.
• Experience working in complex, regulated environments and engaging confidently with senior stakeholders is essential. Experience defining and implementing AI-enabled solutions, particularly Agentic AI, would be highly desirable.
• Experience delivering analysis within complex stakeholder environments within financial services, or a regulatory organisation or another complex, highly governed environment.
• Demonstrable experience translating business needs into functional outcomes and working collaboratively with business and technology delivery teams.
• Experience identifying and managing risks, issues, assumptions, dependencies and change impacts, and contributing to practical mitigation approaches.
• Experience supporting solution design, testing, acceptance and implementation, ensuring that delivered outcomes meet agreed business requirements.