Senior Business Analyst – AI Innovation
About Our Team
Digital Business Solutions (DBS) delivers innovation and solves customer and business problems by leveraging the power of technology, data, and — increasingly — AI. Within DBS, the AI Innovation team focuses specifically on identifying and delivering agentic and generative AI capabilities across our Salesforce ecosystem and adjacent platforms. We partner with customers, authors, editors, and Elsevier colleagues to drive intelligent automation, frictionless personalised experiences, and streamlined processes that support cost optimisation and growth. We provide the expertise to understand business challenges and translate them into practical, responsible AI-enabled solutions.
About the Role
The Senior Business Analyst will work with business units and technology teams to identify, scope, and deliver AI innovation opportunities across our Salesforce platform landscape — including Salesforce Agentforce, Data Cloud (Data 360), and Model Context Protocol (MCP)-based integrations, as well as adjacent AI tooling. The role focuses on hunting for value opportunities for sales teams; understanding the data and process foundations required to ground AI agents; and defining requirements and functional specifications that bridge business needs with emerging AI capabilities.
Responsibilities
Partner with business and product teams to identify opportunities where AI agents, automation, and data unification can remove friction, reduce cost, or improve customer/employee experience
Document current-state business processes and design future-state processes that incorporate Salesforce Agentforce agents, Data Cloud (Data 360), and MCP-based integrations
Gather business requirements, high-level user stories, and acceptance criteria for AI agent workflows — including agent actions, guardrails, escalation paths, and human-in-the-loop checkpoints
Assess data readiness for AI use cases (data quality, identity resolution, harmonisation) in partnership with data engineering teams supporting Data 360
Plan and facilitate workshops to scope AI/agentic use cases, evaluate feasibility, and align stakeholders on priority and sequencing
Work with technology teams (Salesforce, data engineering, AI/ML engineers) to produce detailed user stories and acceptance criteria that support development and QA, including for Agentforce agent builds and MCP server/tool integrations
Maintain stakeholder expectations, communicate trade-offs of AI-driven solutions (accuracy, latency, cost, risk), and raise issues to project/product managers as needed
Develop "trusted advisor" relationships with senior stakeholders through effective communication about AI capabilities, limitations, and responsible use
Perform analysis on existing systems and processes to identify where AI/agentic solutions are technically and commercially viable versus where traditional automation is a better fit
Track the evolving Agentforce, Data Cloud, and MCP/agentic-AI landscape, and translate relevant developments into concrete opportunities for the business
Support change management and user adoption for AI-driven process changes, including documentation and enablement materials
Requirements
Proven experience in process modelling (BPMN standard), eliciting business requirements, and translating them into clear user stories and acceptance criteria
Hands-on experience with the Salesforce platform (Sales Cloud / Service Cloud); working knowledge of, or strong interest in, Salesforce Agentforce and Data Cloud (Data 360)
Working familiarity with core AI/agentic concepts — prompt engineering, retrieval-augmented generation (RAG), tool/function calling, and Model Context Protocol (MCP) — sufficient to translate business needs into technical requirements
Understanding of data architecture fundamentals (data unification, identity resolution, data quality) as they relate to grounding AI agents on trustworthy data
Solid understanding of software development…