AI Business Analyst

The AI Business Analyst helps clients define business needs, prioritize AI and data use cases, and give delivery teams clear, testable requirements. Working with client stakeholders and Coretek technical specialists, this role connects proposed solutions to measurable business outcomes and maintains that connection through delivery, business validation, and handover.

The role supports projects and workstreams within a Forward Deployed Pod. Activities and capacity follow the agreed engagement scope and allocation.

Key Responsibilities

• Lead discovery sessions to understand business objectives, stakeholder needs, intended users, current processes, constraints, and measures of success.
• Map current and proposed processes, including handoffs, business rules, exceptions, and changes to roles, decisions, controls, and downstream work.
• Define and prioritize use cases with stakeholders. Document the business problem, expected outcomes, value, dependencies, and constraints. Support minimum viable product definition and release planning where included in scope.
• Translate business, functional, data, and reporting needs into requirements, user stories, and testable acceptance criteria. Work with technical leads to capture security, performance, and integration needs.
• Document readiness for AI, analytics, and automation use cases, including data sources, ownership, access, quality considerations, expected outputs, user interactions, exceptions, human review, and validation criteria.
• Review requirements with business and technical teams, resolve ambiguity, and confirm that proposed designs address approved requirements. Record decisions and assumptions and maintain traceability to outcomes, delivery scope, and acceptance criteria.
• Support backlog refinement and assess proposed changes. Explain effects on scope, effort, dependencies, and outcomes. Communicate progress and outstanding actions regularly, and raise blockers and risks with a recommended next action.
• Develop business cases using agreed baselines, cost and benefit assumptions, and outcome measures when included in scope. Support scoped adoption and readiness assessments of stakeholder impacts, process changes, and adoption risks.
• Support user acceptance testing by defining business scenarios, coordinating stakeholder reviews, and recording results, unresolved issues, and items requiring client acceptance.
• Prepare business process and user guidance and a clear handover of approved requirements, decisions, known limitations, open actions, and assigned ownership.

• Experience facilitating business discovery, working with stakeholders, and documenting current and future processes.
• Ability to turn business needs into prioritized requirements, user stories, business rules, and testable acceptance criteria.
• Ability to clarify business and data requirements for AI, analytics, reporting, or automation use cases with technical specialists.
• Skill in documenting data ownership, access and quality considerations, expected user interactions, exceptions, and human review needs.
• Experience maintaining requirements traceability, decision records, and change-impact assessments through delivery.
• Ability to define business acceptance scenarios, summarize validation results, and prepare practical process documentation and handover materials.
• Clear communication, workshop facilitation, and stakeholder-management skills, including explaining dependencies, risks, and unresolved decisions to business and technical audiences.

What Success Looks Like

Client stakeholders and delivery teams share a clear understanding of the business need, agreed priorities, and acceptance criteria. Requirements remain traceable as delivery progresses. Business validation results and unresolved issues are documented, and the receiving team has usable process guidance, editable artifacts, and clear ownership of remaining actions.

Role Within the Pod

The AI Business Analyst coordinates priorities with the project or workstream lead and collaborates with architects, data and AI engineers, security resources, and other delivery specialists. Technical leads own design and implementation. Client-designated owners retain product priorities, business decisions, risk and compliance decisions, and acceptance authority. The analyst supports those decisions with documented requirements and evidence.