AI Transformation Manager

Job Description & Summary

The opportunity

Convert business priorities into high-value AI products and agentic workflows, owning discovery, process redesign, product direction, agile backlog and benefits realization.

What you will be doing

• Lead value-discovery and process-design workshops with business and technology stakeholders.
• Map current workflows, decisions, hand-offs, pain points, controls and performance baselines.
• Prioritize agentic use cases based on value, feasibility, risk and time to impact.
• Act as product owner or product-management lead for client delivery, maintaining outcomes, roadmap and backlog.
• Define business cases, KPIs, benefit owners and measurement approaches.
• Coordinate user adoption, operating-model changes and transition to business ownership.

What we need from you

• 7+ years in management consulting, digital transformation, product management or process improvement.
• Strong experience in business cases, process redesign, agile delivery and executive facilitation.
• Ability to translate business needs into clear product outcomes and acceptance criteria.
• Working understanding of AI, agents, data dependencies, human oversight and automation.

Relevant AI technologies and tooling

• Working knowledge of agentic solution concepts, including tool calling, workflow orchestration, memory, retrieval-augmented generation, human-in-the-loop controls, evaluation and observability.
• Ability to convert a business process into agent roles, tools, decision points, structured inputs and outputs, exception paths, acceptance criteria and measurable value hypotheses.
• Familiarity with platforms and frameworks used by delivery teams, such as LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, OpenAI Agents SDK, Microsoft Copilot Studio and workflow automation platforms.
• Experience using Agile product-management tooling such as Azure DevOps or Jira to manage epics, user stories, acceptance criteria, dependencies, releases and benefits measures.

Measures of success

• Value of prioritized use cases
• Backlog quality and stakeholder alignment
• Speed from discovery to usable release
• Benefits measured after deployment
• Client adoption and satisfaction

Key interfaces

• Other members of the AI Transformation & Agentic Systems Practice
• PwC sector, functional, cloud, cyber, risk, Responsible AI and change specialists
• Client business owners, product owners, technology teams and operational users
• Technology alliance and implementation partners where relevant

Contribution to the practice

• Support proposals, client workshops and market development appropriate to seniority.
• Contribute reusable methods, patterns, code, assets and lessons learned.
• Coach colleagues and participate in the capability’s continuous learning agenda.
• Uphold PwC quality, independence, confidentiality and risk-management requirements.

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