Manager - AI and Business Intelligence (Techno-Functional)

S&C Global Network - AI -AI Labs- Manager

Manager – Applied Intelligence

AI4BI Techno-Functional (GenAI for BI) Manager

Accenture Applied Intelligence practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition.

As part of our Analytics practice, you will join a worldwide network of smart and driven colleagues experienced in leading tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.

Manager in Applied Intelligence – AI4BI Techno-Functional

An AI4BI Techno-Functional Manager leads discovery, solution design and delivery for GenAI-enabled BI initiatives. They run client working sessions, translate business needs into a prioritized backlog and roadmap, and manage implementation across semantic layer, BI consumption, and GenAI/RAG-based conversational and proactive insights—ensuring quality, governance, and adoption.

Duties and Responsibilities

• Lead AI4BI delivery for one or more workstreams (conversational BI, proactive insights, semantic layer/metrics, agentic automation).
• Run workshops to capture BI pain points and requirements; convert into user stories, acceptance criteria, and technical backlog.
• Define solution design across BI + GenAI components: RAG/grounding, tool/function calling concepts, evaluation, guardrails and fallback behaviors.
• Coordinate delivery across engineering, BI developers, data teams, and client stakeholders; manage scope, sprint planning, risks, and dependencies.
• Build client-ready artifacts: solution approach, architecture overview, delivery plan, governance model, and adoption plan.
• Drive testing and quality: GenAI evaluation metrics, regression test suites for prompts/retrieval, UAT support, and production readiness.
• Enable adoption: demos, training, documentation, stakeholder comms, and feedback loops to improve accuracy and usefulness.
• Provide day-to-day leadership to team members; ensure consistent delivery standards and best practices.