Senior Business Analyst: AI & Intelligent Automation

Introduction

Turn vague business problems into shaped, sized, buildable AI and automation use cases, and

stay with them through delivery until they are live, adopted and measured.

The role sits at the front of the funnel and the back of it. At the front: process discovery,

feasibility, data availability, benefit sizing, and the honest call on whether a use case deserves to

be built at all. At the back: requirements, test design, user acceptance testing, cutover and

hypercare. In between, it is the connective tissue between business owners who know the

process and engineers who know the platform.

As the estate moves from rules-based automation toward agentic, data-driven solutions, this role

shapes that shift at process level, identifying which workflows should be re-architected around

agents rather than automated as they stand, and which should not be touched at all.

Duties & Responsibilities

Use Case Shaping and Demand Management

• Conduct discovery workshops with business stakeholders to analyse processes, identify pain points, and perform root-cause analysis.

• Assess current processes, costs and value opportunities to define the problem before recommending solutions.

• Evaluate the feasibility of AI and automation initiatives based on data quality, technical fit, process maturity and organisational readiness.

• Recommend the most appropriate solution, including agentic AI, machine learning, workflow automation, process improvement or no-build options.

• Develop business cases using quantified baselines, clearly documented assumptions and realistic benefit estimates.

• Manage the demand pipeline and prepare use cases for prioritisation and governance.

Process and Data Analysis

• Develop As-Is and To-Be process models (BPMN or equivalent) that capture workflows, decision points, exceptions and handoffs.

• Break down business processes into tasks suitable for AI and automation solution design.

• Analyse and validate data sources, including lineage, ownership, quality, completeness and accessibility.

• Document business rules, decision logic, edge cases and exception handling requirements.

Requirements and Delivery Support

• Gather and document functional and non-functional requirements, user stories and acceptance criteria.

• Define solution requirements including performance, availability, accuracy, scalability, audit and retention standards.

• Support Agile delivery through backlog refinement, sprint planning, demonstrations and defect resolution.

• Develop test scenarios, coordinate User Acceptance Testing (UAT) and manage business sign-off.

• Support implementation, hypercare and operational handover, including the development of SOPs, runbooks and user documentation.

Value and Measurement

• Establish pre-implementation performance baselines for all use cases.

• Collaborate with Data Science to define benefit measurement methodologies.

• Monitor post-implementation benefits and report realised value against agreed targets.

Cloud and Platform Fluency

• Apply an understanding of cloud platforms, data architecture, APIs and integration patterns when shaping solutions.

• Consider infrastructure, model selection and consumption costs during solution design.

• Work with Technology teams to identify and resolve environment, access and integration dependencies.

Governance and Risk

• Ensure all use cases comply with POPIA, data privacy, security, AI governance and audit requirements.

• Define AI decision authority, human approval requirements and audit trail standards for agentic solutions.

• Prepare and maintain governance documentation and supporting compliance artefacts.

Team Contribution

• Mentor and support junior and mid-level Business Analysts.

• Promote best practices in business analysis, discovery and requirements gathering.

• Maintain and enhance templates, feasibility assessments, benefit estimation methods and Definition of Ready standards.

Desired Experience & Qualification

Essential

• Bachelor’s degree in Information Systems, Engineering, Computer Science, Business, or a related field.

• 6+ years of Business Analysis experience, including at least 2 years supporting AI, machine learning, data or intelligent automation initiatives.

• Proven experience delivering use cases from problem definition through to production with measurable business outcomes.

• Working knowledge of cloud platforms (GCP or AWS), including data and AI services, APIs, integration patterns and consumption-based cost models.

• Strong SQL skills with the ability to analyse datasets, validate data sources and interpret results independently.

• Understanding of AI solution patterns, including machine learning, LLM-based systems, retrieval and grounding, agent orchestration, evaluation methods and AI guardrails.

• Experience with business process modelling using BPMN or equivalent methodologies.

• Experience working in Agile product or squad-based delivery environments.

Preferred

• Business Analysis certification (CBAP, CCBA or IIBA equivalent).

• Experience with intelligent automation technologies, including Robotic Process Automation (RPA), Intelligent Document Processing (IDP) and workflow orchestration.

• Knowledge of Lean, Six Sigma or process mining methodologies.

• Experience within telecommunications, financial services or other large-scale operational environments.